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Metrics for Inpatient Glycemic Control
Data collection, analysis, and presentation are key to the success of any hospital glycemic control initiative. Such efforts enable the management team to track improvements in processes and outcomes, make necessary changes to their quality improvement efforts, justify the provision of necessary time and resources, and share their results with others. Reliable metrics for assessing glycemic control and frequency of hypoglycemia are essential to accomplish these tasks and to assess whether interventions result in more benefit than harm. Hypoglycemia metrics must be especially convincing because fear of hypoglycemia remains a major source of clinical inertia, impeding efforts to improve glucose control.
Currently, there are no official standards or guidelines for formulating metrics on the quality of inpatient glycemic control. This creates several problems. First, different metrics vary in their biases and in their responsiveness to change. Thus, use of a poor metric could lead to either a falsely positive or falsely negative impression that a quality improvement intervention is in fact improving glycemic control. Second, the proliferation of different measures and analytical plans in the research and quality improvement literature make it very difficult for hospitals to compare baseline performance, determine need for improvement, and understand which interventions may be most effective.
A related article in this supplement provides the rationale for improved inpatient glycemic control. That article argues that the current state of inpatient glycemic control, with the frequent occurrence of severe hyperglycemia and irrational insulin ordering, cannot be considered acceptable, especially given the large body of data (albeit largely observational) linking hyperglycemia to negative patient outcomes. However, regardless of whether one is an advocate or skeptic of tighter glucose control in the intensive care unit (ICU) and especially the non‐ICU setting, there is no question that standardized, valid, and reliable metrics are needed to compare efforts to improve glycemic control, better understand whether such control actually improves patient care, and closely monitor patient safety.
This article provides a summary of practical suggestions to assess glycemic control, insulin use patterns, and safety (hypoglycemia and severe hyperglycemia). In particular, we discuss the pros and cons of various measurement choices. We conclude with a tiered summary of recommendations for practical metrics that we hope will be useful to individual improvement teams. This article is not a consensus statement but rather a starting place that we hope will begin to standardize measurement across institutions and advance the dialogue on this subject. To more definitely address this problem, we call on the American Association of Clinical Endocrinologists (AACE), American Diabetes Association (ADA), Society of Hospital Medicine (SHM), and others to agree on consensus standards regarding metrics for the quality of inpatient glycemic control.
MEASURING GLYCEMIC CONTROL: GLUCOMETRICS
Glucometrics may be defined as the systematic analysis of blood glucose (BG) dataa phrase initially coined specifically for the inpatient setting. There are numerous ways to do these analyses, depending on which patients and glucose values are considered, the definitions used for hypoglycemia and hyperglycemia, the unit of measurement (eg, patient, patient‐day, individual glucose value), and the measure of control (eg, mean, median, percent of glucose readings within a certain range). We consider each of these dimensions in turn.
Defining the Target Patient Population
The first decision to be made is which patients to include in your analysis. Choices include the following:
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Patients with a discharge diagnosis of diabetes: this group has face validity and intuitive appeal, is easy to identify retrospectively, and may capture some untested/untreated diabetics, but will miss patients with otherwise undiagnosed diabetes and stress hyperglycemia. It is also subject to the variable accuracy of billing codes.
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Patients with a certain number of point‐of‐care (POC) glucose measurements: this group is also easy to identify, easy to measure, and will include patients with hyperglycemia without a previous diagnosis of diabetes, but will miss patients with untested/untreated hyperglycemia. Also, if glucose levels are checked on normoglycemic, nondiabetic patients, these values may dilute the overall assessment of glycemic control.
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Patients treated with insulin in the hospital: this is a good choice if the purpose is mainly drug safety and avoidance of hypoglycemia, but by definition excludes most untreated patients.
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Patients with 2 or more BG values (laboratory and/or POC) over a certain threshold (eg, >180 mg/dL). This will likely capture more patients with inpatient hyperglycemia, whether or not detected by the medical team, but is subject to wide variations in the frequency and timing of laboratory glucose testing, including whether or not the values are pre‐prandial (note that even preprandial POC glucose measurements are not always in fact fasting values).
Other considerations include the following:
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Are there natural patient subgroups that should be measured and analyzed separately because of different guidelines? For example, there probably should be separate/emndependent inclusion criteria and analyses for critical care and noncritical care units because their glycemic targets and management considerations differ.
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Which patients should be excluded? For example, if targeting subcutaneous insulin use in general hospitalized patients, one might eliminate those patients who are admitted specifically as the result of a diabetes emergency (eg, diabetic ketoacidosis [DKA] and hyperglycemic hyperosmolar state [HHS]), as their marked and prolonged hyperglycemia will skew BG data. Pregnant women should generally be excluded from broad‐based analyses or considered as a discrete category because they have very different targets for BG therapy. Patients with short lengths of stay may be less likely to benefit from tight glucose control and may also be considered for post hoc exclusion. One might also exclude patients with very few evaluable glucose readings (eg, fewer than 5) to ensure that measurement is meaningful for a given patient, keeping in mind that this may also exclude patients with undetected hyperglycemia, as mentioned above. Finally, patients receiving palliative care should also be considered for exclusion if feasible.
Recommendation: Do not limit analyses to only those patients with a diagnosis of diabetes or only those on insulin, which will lead to biased results.
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For noncritical care patients, we recommend a combined approach: adult patients with a diagnosis of diabetes (e. g. using diagnosis‐related group [DRG] codes 294 or 295 or International Classification of Diseases 9th edition [ICD9] codes 250.xx) or with hyperglycemia (eg, 2 or more random laboratory and/or point of care (POC) BG values >180 mg/dL or 2 or more fasting BG values >130 mg/dL), excluding patients with DKA or HHS or who are pregnant.
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For critical care units, we recommend either all patients, or patients with at least mild hyperglycemia (eg, 2 random glucose levels >140 mg/dL). Critical care patients with DKA, HHS, and pregnancy should be evaluated separately if possible.
Which Glucose Values to Include and Exclude
To answer this question, we first need to decide which method to use for BG measurement. There are several ways to measure BG, including the type of sample collected (capillary [fingerstick], arterial, and venous) and the technique used (central laboratory analyzing plasma, central laboratory analyzing whole blood [eg, from an arterial blood gas sample], glucose meter [usually calibrated to plasma], etc.). The POC (eg, capillary, glucose meter) glucose measurements alone are often preferred in the non‐ICU setting because laboratory plasma values generally provide little additional information and typically lower the mean glucose by including redundant fasting values.1 In critical care units, several different methods are often used together, and each merits inclusion. The inherent differences in calibration between the methods do not generally require separate analyses, especially given the frequency of testing in the ICU setting.
The next question is which values to include in analyses. In some situations, it may be most useful to focus on a certain period of hospitalization, such as the day of a procedure and the next 2 days in assessing the impact of the quality of perioperative care, or the first 14 days of a noncritical care stay to keep outliers for length of stay (LOS) from skewing the data. In the non‐ICU setting, it may be reasonable to exclude the first day of hospitalization, as early BG control is impacted by multiple variables beyond direct control of the clinician (eg, glucose control prior to admission, severity of presenting illness) and may not realistically reflect your interventions. (Keep in mind, however, that it may be useful to adjust for the admission glucose value in multivariable models given its importance to clinical outcomes and its strong relationship to subsequent inpatient glucose control.) However, in critical care units, it is reasonable to include the first day's readings in analyses given the high frequency of glucose measurements in this setting and the expectation that glucose control should be achieved within a few hours of starting an intravenous insulin infusion.
If feasible to do so with your institution's data capture methods, you may wish to select only the regularly scheduled (before each meal [qAC] and at bedtime [qHS], or every 6 hours [q6h]) glucose readings for inclusion in the summary data of glycemic control in the non‐ICU setting, thereby reducing bias caused by repeated measurements around extremes of glycemic excursions. An alternative in the non‐ICU setting is to censor glucose readings within 60 minutes of a previous reading.
Recommendation:
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In the non‐ICU setting, we recommend first looking at all POC glucose values and if possible repeating the analyses excluding hospital day 1 and hospital day 15 and beyond, and also excluding glucose values measured within 60 minutes of a previous value.
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In critical care units, we recommend evaluating all glucose readings used to guide care.
Units of Analysis
There are several different units of analysis, each with its own advantages and disadvantages:
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Glucose value: this is the simplest measure and the one with the most statistical power. All glucose values for all patients of interest comprise the denominator. A report might say, for example, that 1% of the 1000 glucose values were <70 mg/dL during a certain period or that the mean of all glucose values collected for the month from patients in noncritical care areas was 160 mg/dL. The potential disadvantages of this approach are that these analyses are less clinically relevant than patient‐level analyses and that patients with many glucose readings and long hospitalizations may skew the data.
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Patient (or the Patient Stay, [ie, the entire hospitalization]): all patients who are monitored make up the denominator. The numerator may be the percentage of patients with any hypoglycemia during their hospital stay or the percentage of patients achieving a certain mean glucose during their hospitalization, for example. This is inherently more clinically meaningful than using glucose value as a unit of analysis. A major disadvantage is not controlling for LOS effects. For example, a hospitalized patient with a long LOS is much more likely to be characterized as having at least 1 hypoglycemic value than is a patient with a shorter LOS. Another shortcoming is that this approach does not correct for uneven distribution of testing. A patient's mean glucose might be calculated on the basis of 8 glucose values on the first day of hospitalization, 4 on the second day, and 1 on the third day. Despite all these shortcomings, reporting by patient remains a popular and valid method of presenting glycemic control results, particularly when complemented by other views and refined to control for the number of readings per day.
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Monitored Patient‐Day: The denominator in this setting is the total number of days a patient glucose level is monitored. The benefits of this method have been described and advocated in the literature.1 As with patient‐level analyses, this measure will be more rigorous and meaningful if the BG measures to be evaluated have been standardized. Typical reports might include percentage of monitored days with any hypoglycemia, or percentage of monitored days with all glucose values in the desired range. This unit of analysis may be considered more difficult to generate and to interpret. On the other hand, it is clinically relevant, less biased by LOS effects, and may be considered the most actionable metric by clinicians. This method provides a good balance when presented with data organized by patient.
The following example uses all 3 units of measurement, in this case to determine the rate of hypoglycemia, demonstrating the different but complementary information that each method provides:
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In 1 month, 3900 POC glucose measurements were obtained from 286 patients representing 986 monitored patient‐days. With hypoglycemia defined as POC BG 60 mg/dL, the results showed the following:
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50 of 3900 measurements (1.4%) were hypoglycemic 22 of 286 patients (7.7%) had 1 hypoglycemic episodes
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40 of 986 monitored days (4.4%) had 1 hypoglycemic episodes.
The metric based on the number of glucose readings could be considered the least clinically relevant because it is unclear how many patients were affected; moreover, it may be based on variable testing patterns among patients, and could be influenced disproportionately by 1 patient with frequent hypoglycemia, many glucose readings, and/or a long LOS. One could argue that the patient‐stay metric is artificially elevated because a single hypoglycemic episode characterizes the entire stay as hypoglycemic. On the other hand, at least it acknowledges the number of patients affected by hypoglycemia. The patient‐day unit of analysis likely provides the most balanced view, one that is clinically relevant and measured over a standard period of time, and less biased by LOS and frequency of testing.
One way to express patient‐day glycemic control that deserves special mention is the patient‐day weighted mean. A mean glucose is calculated for each patient‐day, and then the mean is calculated across all patient‐days. The advantage of this approach is that it corrects for variation in the number of glucose readings each day; all hospital days are weighted equally.
Recommendation:
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In noncritical care units, we recommend a combination of patient‐day and patient‐stay measures.
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In critical care units, it is acceptable to also use glucose reading as the unit of measurement given more frequent and uniform data collection, but it should be complemented by more meaningful patient‐day and patient‐stay measures.
Measures of Control
In addition to deciding the unit(s) of analysis, another issue concerns which measures of control to use. These could include rates of hypoglycemia and hyperglycemia, percentage of glucose readings within various ranges (eg, <70, 70180, >180 mg/dL), mean glucose value, percentage of patient‐days during which the mean glucose is within various ranges, or the in control rate (ie, when all glucose values are within a certain range).
As with the various units of analysis, each of these measures of control has various advantages and disadvantages. For example, mean glucose is easy to report and understand, but masks extreme values. Percentage of glucose values within a certain range (eg, per patient, averaged across patients) presents a more complete picture but is a little harder to understand and will vary depending on the frequency of glucose monitoring. As mentioned above, this latter problem can be corrected in part by including only certain glucose values. Percent of glucose values within range may also be less sensitive to change than mean glucose (eg, a glucose that is lowered from 300 mg/dL to 200 mg/dL is still out of range). We recommend choosing a few, but not all, measures of control in order to get a complete picture of glycemic control. Over time one can then refine the measures being used to meet the needs of the glycemic control team and provide data that will drive the performance improvement process.
In critical care and perioperative settings, interest in glycemic control is often more intense around the time of a particular event such as major surgery or after admission to the ICU. Some measures commonly used in performing such analyses are:
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All values outside a target range within a designated crucial period. For example, the University Healthcare Consortium and other organizations use a simple metric to gauge perioperative glycemic control. They collect the fasting glucose on postoperative days 1 and 2 and then calculate the percentage of postoperative days with any fasting glucose >200 mg/dL. Of course, this is a very liberal target, but it can always be lowered in a stepwise fashion once it is regularly being reached.
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Three‐day blood glucose average. The Portland group uses the mean glucose of each patient for the period that includes the day of coronary artery bypass graft (CABG) surgery and the following 2 days. The 3‐day BG average (3‐BG) correlates very well with patient outcomes and can serve as a well‐defined target.2 It is likely that use of the 3‐BG would work well in other perioperative/trauma settings and could work in the medical ICU as well, with admission to the ICU as the starting point for calculation of the 3‐BG.
Hyperglycemic Index
Measuring the hyperglycemic index (HGI) is a validated method of summarizing glycemic control of ICU patients.3 It is designed to take into account the sometimes uneven distribution of patient testing. Time is plotted on the x‐axis and glucose values on the y‐axis. The HGI is calculated the area under the curve of glycemic values but above the upper limit of normal (ie, 110 mg/dL). Glucose values in the normal or hypoglycemic range are not included in the AUC. Mortality correlated well with this glycemic index. However, a recent observational study of glucometrics in patients hospitalized with acute myocardial infarction found that the simple mean of each patient's glucose values over the entire hospitalization was as predictive of in‐hospital mortality as the HGI or the time‐averaged glucose (AUC for all glucose values).4 In this study, metrics derived from glucose readings for the entire hospitalization were more predictive than those based on the first 24 or 48 hours or on the admission glucose.
Analyses Describing Change in Glycemic Control Over Time in the Hospital
In the critical care setting, this unit of analysis may be as simple as the mean time to reach the glycemic target on your insulin infusion protocol. On noncritical care wards, it is a bit more challenging to characterize the improvement (or clinical inertia) implied by failure of hyperglycemia to lessen as an inpatient stay progresses. One method is to calculate the mean glucose (or percentage of glucose values in a given range) for each patient on hospital day (HD) 1, and repeat for each HD (up to some reasonable limit, such as 5 or 7 days).
Recommendations:
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In noncritical units, we recommend a limited set of complementary measures, such as the patient‐day weighted mean glucose, mean percent of glucose readings per patient that are within a certain range, and percentage of patients whose mean glucose is within a certain range on each hospital day.
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In critical care units, it is often useful to focus measures around a certain critical event such as the 3‐day blood glucose average and to use measures such as the HGI that take advantage of more frequent blood glucose testing.
Definitions of Hyperglycemia and Hypoglycemia
Glucometrics outcomes will obviously depend on the thresholds established for hyperglycemia and hypoglycemia. Many centers define hypoglycemia as 60 mg/dL, whereas the ADA definition, based on physiologic changes that may take place, defines hypoglycemia (at least in the outpatient setting) as 70 mg/dL. Hypoglycemia may be further stratified by severity, with any glucose 40 mg/dL, for instance, defined as severe hypoglycemia.
Similarly, the definition of hyperglycemia (and therefore good control) must also be defined. Based on definitions developed by the ADA and AACE, the state of the medical literature, and current understanding of the pathophysiology of hyperglycemia, thresholds for critical care units include 110 mg/dL, 130 mg/dL, and 140 mg/dL, and options in noncritical care units include 130 mg/dL, 140 mg/dL, and 180 mg/dL. Because these thresholds implicitly assume adverse effects when glucose levels are above them, these levels are subject to revision as data become available confirming the benefits and safety of targeted glycemic control in various settings and patient populations.
Introducing optimal BG targets in a stepped fashion over time should also be considered. Furnary et al.2 have done this in the Portland Project, which tracks glycemic control in cardiac surgery patients receiving intravenous insulin therapy. The initial BG target for this project was <200 mg/dL; it was subsequently lowered stepwise over several years to 150 mg/dL, then to 120 mg/dL, and most recently to 110 mg/dL. This approach allows the safe introduction of targeted glycemic control and promotes acceptance of the concept by physicians and the allied nursing and medical staff.
Recommendations:
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In noncritical care units, it is reasonable to use 40 mg/dL for severe hypoglycemia, 70 mg/dL for hypoglycemia, 130 mg/dL for fasting hyperglycemia, 180 mg/dL for random or postprandial hyperglycemia, and 300 mg/dL for severe hyperglycemia, keeping in mind that these thresholds are arbitrary. In critical care units, values from 110 mg/dL to 140 mg/dL might be better thresholds for hyperglycemia, but it may take time to safely and effectively move an organization toward these lower targets.
Other Considerations Relative to Glucometrics
Yale Glucometrics Website
The Yale Informatics group has put together a Web‐based resource (
Other Analytic Resources
Commercially available software, such as the RALS system (Medical Automation Systems, Inc., Charlottesville, VA) can gather POC glucose measurements directly from devices and provide real‐time reports of glycemic control, stratified by inpatient unit, using user‐defined targets for hypoglycemia and hyperglycemia. While they are no substitute for a dedicated, on‐site data analyst, such systems can be very useful for smaller hospitals with minimal data or information technology support staff.
APPROACHES TO ANALYSIS: RUN CHARTS
Most conventional clinical trials hold interventions fixed for a period of time and compare results with and without the intervention. For quality improvement studies, this is still a valid way to proceed, especially if studied as a randomized controlled trial. Such methods may be preferred when the clinical question is Does this type of intervention work in general? and the desired output is publication in peer‐reviewed journals so that others can learn about and adopt the intervention to their own institution. A before and after study with a similar analytic approach may also be valid, although concerns about temporal trends and cointerventions potentially compromise the validity of such studies. This approach again assumes that an intervention is held fixed over time such that it is clear what patients received during each time period.
If the desired result is improvement at a given institution (the question is Did we improve care?) then it may be preferable to present results over time using run‐charts. In a run chart, the x‐axis is time and the y‐axis the desired metric, such as patient‐day weighted mean glucose. Points in time when interventions were introduced or modified can be highlighted. Run charts have several advantages over before‐and‐after summaries: they do not require interventions remaining fixed and are more compatible with continuous quality improvement methods, it is easier to see the effect of different aspects of the interventions as they occur, one can get a quicker picture of whether something is working, and it is easier to separate out the impact of the intervention from secular trends. Finally, the use of run charts does not imply the absence of statistical rigor. Run charts with statistical process control (SPC) limits5 can easily convey when the observed time trend is unlikely to be due to chance using prespecified P values. (A full discussion of SPC and other methods to study quality improvement interventions is beyond the scope of this article.)
ASSESSING PATTERNS OF INSULIN USE AND ORDER SET UTILIZATION
Besides measuring the impact of quality improvement interventions on glucose control, it is important to measure processes such as proper insulin use. As mentioned in other articles in this supplement, processes are much more sensitive to change than outcomes. Failure to change processes should lead one to make changes to the intervention.
ICU and Perioperative Settings
For ICU and perioperative settings, the major process measure will likely be use of the insulin infusion order set. Designation of BG levels that trigger insulin infusion in these settings should be agreed upon in advance. The number of patients who meet the predefined glycemic criteria would make up the denominator, and the number of patients on the insulin infusion order set would make up the numerator.
NonCritical Care Units
On noncritical care units, measuring the percentage of subcutaneous insulin regimens that contain a basal insulin is a useful way to monitor the impact of an intervention. A more detailed analysis could examine the percentage of patients on simultaneous basal and nutritional insulin (if applicable). An important measure of clinical inertia is to track the percentage of patients who had changes in their insulin regimens on days after hypoglycemic or hyperglycemic excursions. Another important measure is the frequency with which the standardized order set is being used, analogous to the measure of insulin infusion use in the ICU. A final process measure, indirectly related to insulin use, is the frequency of use of oral diabetes agents, especially by patients for whom their use is contraindicated (eg, patients with congestive heart failure who are on thiazolidinediones and patients with renal insufficiency or receiving intravenous contrast continued on metformin).
OTHER CONSIDERATIONS AND METRICS
Examples of other metrics that can be used to track the success of quality improvement efforts include:
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Glucose measurement within 8 hours of hospital admission.
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Glycated hemoglobin (A1C) measurement obtained or available within 30 days of admission to help guide inpatient and especially discharge management.
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Appropriate glucose testing in patients with diabetes or hyperglycemia (eg, 4 times per day in patients not on insulin infusion protocols, at least until 24 hours of euglycemia is documented).
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The percentage of patients on insulin with on‐time tray delivery.
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The timing of subcutaneous insulin administration in relation to glucose testing and nutrition delivery.
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Documentation of carbohydrate intake among patients who are eating.
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Satisfaction of physicians and nurses with order sets or protocols, using standard surveys.
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Physician and nurse knowledge, attitudes, and beliefs about insulin administration, fear of hypoglycemia, treatment of hypoglycemia, and glycemic control in the hospital.
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Patient satisfaction with their diabetes care in the hospital, including the education they received.
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Nursing and physician education/certification in insulin prescribing, insulin administration, and other diabetes care issues.
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Patient outcomes strongly associated with glycemic control, (eg, surgical wound infections, ICU LOS, catheter‐related bloodstream infections).
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Appropriate treatment and documentation of hypoglycemia (eg, in accordance with hospital policy).
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Documentation of severe hypoglycemic events through the hospital's adverse events reporting system (these may actually increase as change comes to the organization and as clinical personnel are more attuned to glycemic control).
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Root causes of hypoglycemic events, which can be used to understand and prevent future events.
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Appropriate transitions from IV to SC insulin regimens, (eg, starting basal insulin prior to discontinuing infusion in patients who have been on an insulin infusion of at least 2 units/hour or who have a known diagnosis of diabetes or A1C >7).
(Survey instruments and other measurement tools are available from the authors upon request.)
SHM GLYCEMIC CONTROL TASK FORCE SUMMARY RECOMMENDATIONS
The SHM Glycemic Control Task Force is working to develop standardized measures of inpatient glucose control and related indicators to track progress of hospital glycemic control initiatives (see the introduction to this supplement for a description of the charge and membership of this task force). The goals of the Task Force's metrics recommendations (Table 1) are several‐fold: (1) create a set of measurements that are complete but not overly burdensome; (2) create realistic measures that can be applied to institutions with different data management capabilities; and (3) allow for comparison across institutions for benchmarking purposes, evaluation of quality improvement projects, and reporting of results for formal research studies in this field.
Measurement Issue | NonCritical Care Units | Critical Care Units | ||
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Tier 1 Recommendations | Tier 2 Recommendations | Tier 1 Recommendations | Tier 2 Recommendations | |
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Patient inclusion and exclusion criteria | All adult patients with POC glucose testing (sampling acceptable). Exclude patients with DKA or HHS or who are pregnant. | All adult patients with diagnosis of diabetes by ICD‐9 code* or by glucose testing: random glucose (POC or laboratory) >180 mg/dL 2 or fasting glucose >130 mg/dL 2, excluding patients with DKA or HHS or who are pregnant. Additional analysis: exclude patients with <5 evaluable glucose readings, patients with LOS <2 days, or receiving palliative care. | All patients in every critical care unit (sampling acceptable). | Patients with DKA, HHS, or pregnancy in separate analyses. All patients in every critical care unit with random glucose (POC or laboratory) >140 mg/dL 2. |
Glucose reading inclusion and exclusion criteria | All POC glucose values. | Additional analysis: exclude glucose values on hospital day 1 and on hospital day 15 and after. Additional analysis: exclude glucose values measured within 60 minutes of a previous value. | All POC and other glucose values used to guide care. | |
Measures of safety | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | ||
Measures of glucose control | Analysis by patient‐day: Percentage of patient‐days with mean <140, <180 mg/dL and/or Percentage of patient‐days with all values <180 mg/dL. | Analysis by patient‐day: Patient day‐weighted mean glucose. | Analysis by glucose reading: Percentage of readings <110, <140 mg/dL. | 3‐BG as above for all patients in critical care units.∥ Hyperglycemic index for all patients in critical care units (AUC of glucose values above target). |
Analysis by patient stay: Percentage of patient stays with mean <140, <180 mg/dL. | Analysis by patient stay: Mean percentage of glucose readings of each patient <180 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with mean <110, <140 mg/dL, and/or Percentage of patient‐days with all values <110, <140 mg/dL. | ||
Analysis by hospital day: Percentage of patients with mean glucose readings <140, <180 mg/dL by hospital day (days 17). | Analysis by patient stay: 3‐day blood glucose average (3‐BG) for selected perioperative patients: Percentage of patients with 3‐BG <110, <140 mg/dL. Mean time (hours) to reach glycemic target (BG <110 or <140 mg/dL) on insulin infusion. | |||
Measures of insulin use | Percentage of patients on any subcutaneous insulin that has a scheduled basal insulin component (glargine, NPH, or detemir). | Percentage of patients with at least 2 POC and/or laboratory glucose readings >180 mg/dL who have a scheduled basal insulin component. Percentage of eating patients with hyperglycemia as defined above with scheduled basal insulin and nutritional insulin. Percentage of patients and patient‐days with any changes in insulin orders the day after 2 or more episodes of hypoglycemia or hyperglycemia (ie, <70 or >180 mg/dL). | Percentage of patients with 2 POC or laboratory glucose readings >140 mg/dL placed on insulin infusion protocol. | |
Other process measures | Glucose measured within 8 hours of hospital admission. | POC glucose testing at least 4 times a day for all patients with diabetes or hyperglycemia as defined above. | Glucose measured within 8 hours of hospital admission. | Appropriateness of hypoglycemia treatment and documentation. |
A1C measurement obtained or available within 30 days of admission. | Measures of adherence to specific components of management protocol. | Frequency of BG testing (eg, per protocol if on insulin infusion; every 68 hours if not). | Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | |
Appropriateness of hypoglycemia treatment and documentation. | Root causes of hypoglycemia. | |||
Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | Appropriate use of IV‐to‐SC insulin transition protocol. | |||
Root causes of hypoglycemia. |
For each domain of glycemic management (glycemic control, safety, and insulin use), the task force chose a set of best measures. They are presented as two tiers of measurement standards, depending on the capabilities of the institution and the planned uses of the data. Tier 1 includes measures that, although they do take time and resources to collect, are feasible for most institutions. Tier 2 measures are recommended for hospitals with easy manipulation of electronic sources of data and for reporting quality‐of‐care measures for widespread publication, that is, in the context of a research study. It should be emphasized that these recommendations are only meant as a guide: the actual measures chosen should meet the needs and capabilities of each institution.
We recognize that few data support the recommendations made by this task force, that such data are needed, and that the field of data collection and analysis for hospital glycemic management is rapidly evolving. The hope is to begin the standardization process, promote dialogue in this field, and eventually reach a consensus in collaboration with the ADA, AACE, and other pertinent stakeholders.
CONCLUSIONS
Like the field of inpatient glycemic management itself, the field of devising metrics to measure the quality of inpatient glycemic control is also in its infancy and quickly evolving. One should not be paralyzed by the lack of consensus regarding measurementthe important point is to pick a few complementary metrics and begin the process. The table of recommendations can hopefully serve as a starting point for many institutions, with a focus on efficacy (glycemic control), safety (hypoglycemia), and process (insulin use patterns). As your institution gains experience with measurement and the field evolves, your metrics will likely change. We recommend keeping all process and outcome data in its raw form so that it can be summarized in different ways over time. It is also important not to wait for the perfect data collection tool before beginning to analyze data: sampling and paper processes are acceptable if automated data collection is not yet possible. Eventually, blood glucose meter readings should be downloaded into a central database that interfaces with hospital data repositories so data can be analyzed in conjunction with patient, service, and unit‐level information. Only with a rigorous measurement process can institutions hope to know whether their changes are resulting in improved care for patients.
- “Glucometrics”—assessing the quality of inpatient glucose management.Diabetes Technol Ther.2006;8:560–569. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland Diabetic Project.Endocr Pract.2004;10(suppl 2):21–33. , , .
- Hyperglycaemic index as a tool to assess glucose control: a retrospective study.Crit Care.2004;8:R122–R127. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Statistical process control as a tool for research and healthcare improvement.Qual Saf Health Care.2003;12:458–464. , , .
Data collection, analysis, and presentation are key to the success of any hospital glycemic control initiative. Such efforts enable the management team to track improvements in processes and outcomes, make necessary changes to their quality improvement efforts, justify the provision of necessary time and resources, and share their results with others. Reliable metrics for assessing glycemic control and frequency of hypoglycemia are essential to accomplish these tasks and to assess whether interventions result in more benefit than harm. Hypoglycemia metrics must be especially convincing because fear of hypoglycemia remains a major source of clinical inertia, impeding efforts to improve glucose control.
Currently, there are no official standards or guidelines for formulating metrics on the quality of inpatient glycemic control. This creates several problems. First, different metrics vary in their biases and in their responsiveness to change. Thus, use of a poor metric could lead to either a falsely positive or falsely negative impression that a quality improvement intervention is in fact improving glycemic control. Second, the proliferation of different measures and analytical plans in the research and quality improvement literature make it very difficult for hospitals to compare baseline performance, determine need for improvement, and understand which interventions may be most effective.
A related article in this supplement provides the rationale for improved inpatient glycemic control. That article argues that the current state of inpatient glycemic control, with the frequent occurrence of severe hyperglycemia and irrational insulin ordering, cannot be considered acceptable, especially given the large body of data (albeit largely observational) linking hyperglycemia to negative patient outcomes. However, regardless of whether one is an advocate or skeptic of tighter glucose control in the intensive care unit (ICU) and especially the non‐ICU setting, there is no question that standardized, valid, and reliable metrics are needed to compare efforts to improve glycemic control, better understand whether such control actually improves patient care, and closely monitor patient safety.
This article provides a summary of practical suggestions to assess glycemic control, insulin use patterns, and safety (hypoglycemia and severe hyperglycemia). In particular, we discuss the pros and cons of various measurement choices. We conclude with a tiered summary of recommendations for practical metrics that we hope will be useful to individual improvement teams. This article is not a consensus statement but rather a starting place that we hope will begin to standardize measurement across institutions and advance the dialogue on this subject. To more definitely address this problem, we call on the American Association of Clinical Endocrinologists (AACE), American Diabetes Association (ADA), Society of Hospital Medicine (SHM), and others to agree on consensus standards regarding metrics for the quality of inpatient glycemic control.
MEASURING GLYCEMIC CONTROL: GLUCOMETRICS
Glucometrics may be defined as the systematic analysis of blood glucose (BG) dataa phrase initially coined specifically for the inpatient setting. There are numerous ways to do these analyses, depending on which patients and glucose values are considered, the definitions used for hypoglycemia and hyperglycemia, the unit of measurement (eg, patient, patient‐day, individual glucose value), and the measure of control (eg, mean, median, percent of glucose readings within a certain range). We consider each of these dimensions in turn.
Defining the Target Patient Population
The first decision to be made is which patients to include in your analysis. Choices include the following:
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Patients with a discharge diagnosis of diabetes: this group has face validity and intuitive appeal, is easy to identify retrospectively, and may capture some untested/untreated diabetics, but will miss patients with otherwise undiagnosed diabetes and stress hyperglycemia. It is also subject to the variable accuracy of billing codes.
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Patients with a certain number of point‐of‐care (POC) glucose measurements: this group is also easy to identify, easy to measure, and will include patients with hyperglycemia without a previous diagnosis of diabetes, but will miss patients with untested/untreated hyperglycemia. Also, if glucose levels are checked on normoglycemic, nondiabetic patients, these values may dilute the overall assessment of glycemic control.
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Patients treated with insulin in the hospital: this is a good choice if the purpose is mainly drug safety and avoidance of hypoglycemia, but by definition excludes most untreated patients.
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Patients with 2 or more BG values (laboratory and/or POC) over a certain threshold (eg, >180 mg/dL). This will likely capture more patients with inpatient hyperglycemia, whether or not detected by the medical team, but is subject to wide variations in the frequency and timing of laboratory glucose testing, including whether or not the values are pre‐prandial (note that even preprandial POC glucose measurements are not always in fact fasting values).
Other considerations include the following:
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Are there natural patient subgroups that should be measured and analyzed separately because of different guidelines? For example, there probably should be separate/emndependent inclusion criteria and analyses for critical care and noncritical care units because their glycemic targets and management considerations differ.
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Which patients should be excluded? For example, if targeting subcutaneous insulin use in general hospitalized patients, one might eliminate those patients who are admitted specifically as the result of a diabetes emergency (eg, diabetic ketoacidosis [DKA] and hyperglycemic hyperosmolar state [HHS]), as their marked and prolonged hyperglycemia will skew BG data. Pregnant women should generally be excluded from broad‐based analyses or considered as a discrete category because they have very different targets for BG therapy. Patients with short lengths of stay may be less likely to benefit from tight glucose control and may also be considered for post hoc exclusion. One might also exclude patients with very few evaluable glucose readings (eg, fewer than 5) to ensure that measurement is meaningful for a given patient, keeping in mind that this may also exclude patients with undetected hyperglycemia, as mentioned above. Finally, patients receiving palliative care should also be considered for exclusion if feasible.
Recommendation: Do not limit analyses to only those patients with a diagnosis of diabetes or only those on insulin, which will lead to biased results.
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For noncritical care patients, we recommend a combined approach: adult patients with a diagnosis of diabetes (e. g. using diagnosis‐related group [DRG] codes 294 or 295 or International Classification of Diseases 9th edition [ICD9] codes 250.xx) or with hyperglycemia (eg, 2 or more random laboratory and/or point of care (POC) BG values >180 mg/dL or 2 or more fasting BG values >130 mg/dL), excluding patients with DKA or HHS or who are pregnant.
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For critical care units, we recommend either all patients, or patients with at least mild hyperglycemia (eg, 2 random glucose levels >140 mg/dL). Critical care patients with DKA, HHS, and pregnancy should be evaluated separately if possible.
Which Glucose Values to Include and Exclude
To answer this question, we first need to decide which method to use for BG measurement. There are several ways to measure BG, including the type of sample collected (capillary [fingerstick], arterial, and venous) and the technique used (central laboratory analyzing plasma, central laboratory analyzing whole blood [eg, from an arterial blood gas sample], glucose meter [usually calibrated to plasma], etc.). The POC (eg, capillary, glucose meter) glucose measurements alone are often preferred in the non‐ICU setting because laboratory plasma values generally provide little additional information and typically lower the mean glucose by including redundant fasting values.1 In critical care units, several different methods are often used together, and each merits inclusion. The inherent differences in calibration between the methods do not generally require separate analyses, especially given the frequency of testing in the ICU setting.
The next question is which values to include in analyses. In some situations, it may be most useful to focus on a certain period of hospitalization, such as the day of a procedure and the next 2 days in assessing the impact of the quality of perioperative care, or the first 14 days of a noncritical care stay to keep outliers for length of stay (LOS) from skewing the data. In the non‐ICU setting, it may be reasonable to exclude the first day of hospitalization, as early BG control is impacted by multiple variables beyond direct control of the clinician (eg, glucose control prior to admission, severity of presenting illness) and may not realistically reflect your interventions. (Keep in mind, however, that it may be useful to adjust for the admission glucose value in multivariable models given its importance to clinical outcomes and its strong relationship to subsequent inpatient glucose control.) However, in critical care units, it is reasonable to include the first day's readings in analyses given the high frequency of glucose measurements in this setting and the expectation that glucose control should be achieved within a few hours of starting an intravenous insulin infusion.
If feasible to do so with your institution's data capture methods, you may wish to select only the regularly scheduled (before each meal [qAC] and at bedtime [qHS], or every 6 hours [q6h]) glucose readings for inclusion in the summary data of glycemic control in the non‐ICU setting, thereby reducing bias caused by repeated measurements around extremes of glycemic excursions. An alternative in the non‐ICU setting is to censor glucose readings within 60 minutes of a previous reading.
Recommendation:
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In the non‐ICU setting, we recommend first looking at all POC glucose values and if possible repeating the analyses excluding hospital day 1 and hospital day 15 and beyond, and also excluding glucose values measured within 60 minutes of a previous value.
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In critical care units, we recommend evaluating all glucose readings used to guide care.
Units of Analysis
There are several different units of analysis, each with its own advantages and disadvantages:
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Glucose value: this is the simplest measure and the one with the most statistical power. All glucose values for all patients of interest comprise the denominator. A report might say, for example, that 1% of the 1000 glucose values were <70 mg/dL during a certain period or that the mean of all glucose values collected for the month from patients in noncritical care areas was 160 mg/dL. The potential disadvantages of this approach are that these analyses are less clinically relevant than patient‐level analyses and that patients with many glucose readings and long hospitalizations may skew the data.
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Patient (or the Patient Stay, [ie, the entire hospitalization]): all patients who are monitored make up the denominator. The numerator may be the percentage of patients with any hypoglycemia during their hospital stay or the percentage of patients achieving a certain mean glucose during their hospitalization, for example. This is inherently more clinically meaningful than using glucose value as a unit of analysis. A major disadvantage is not controlling for LOS effects. For example, a hospitalized patient with a long LOS is much more likely to be characterized as having at least 1 hypoglycemic value than is a patient with a shorter LOS. Another shortcoming is that this approach does not correct for uneven distribution of testing. A patient's mean glucose might be calculated on the basis of 8 glucose values on the first day of hospitalization, 4 on the second day, and 1 on the third day. Despite all these shortcomings, reporting by patient remains a popular and valid method of presenting glycemic control results, particularly when complemented by other views and refined to control for the number of readings per day.
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Monitored Patient‐Day: The denominator in this setting is the total number of days a patient glucose level is monitored. The benefits of this method have been described and advocated in the literature.1 As with patient‐level analyses, this measure will be more rigorous and meaningful if the BG measures to be evaluated have been standardized. Typical reports might include percentage of monitored days with any hypoglycemia, or percentage of monitored days with all glucose values in the desired range. This unit of analysis may be considered more difficult to generate and to interpret. On the other hand, it is clinically relevant, less biased by LOS effects, and may be considered the most actionable metric by clinicians. This method provides a good balance when presented with data organized by patient.
The following example uses all 3 units of measurement, in this case to determine the rate of hypoglycemia, demonstrating the different but complementary information that each method provides:
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In 1 month, 3900 POC glucose measurements were obtained from 286 patients representing 986 monitored patient‐days. With hypoglycemia defined as POC BG 60 mg/dL, the results showed the following:
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50 of 3900 measurements (1.4%) were hypoglycemic 22 of 286 patients (7.7%) had 1 hypoglycemic episodes
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40 of 986 monitored days (4.4%) had 1 hypoglycemic episodes.
The metric based on the number of glucose readings could be considered the least clinically relevant because it is unclear how many patients were affected; moreover, it may be based on variable testing patterns among patients, and could be influenced disproportionately by 1 patient with frequent hypoglycemia, many glucose readings, and/or a long LOS. One could argue that the patient‐stay metric is artificially elevated because a single hypoglycemic episode characterizes the entire stay as hypoglycemic. On the other hand, at least it acknowledges the number of patients affected by hypoglycemia. The patient‐day unit of analysis likely provides the most balanced view, one that is clinically relevant and measured over a standard period of time, and less biased by LOS and frequency of testing.
One way to express patient‐day glycemic control that deserves special mention is the patient‐day weighted mean. A mean glucose is calculated for each patient‐day, and then the mean is calculated across all patient‐days. The advantage of this approach is that it corrects for variation in the number of glucose readings each day; all hospital days are weighted equally.
Recommendation:
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In noncritical care units, we recommend a combination of patient‐day and patient‐stay measures.
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In critical care units, it is acceptable to also use glucose reading as the unit of measurement given more frequent and uniform data collection, but it should be complemented by more meaningful patient‐day and patient‐stay measures.
Measures of Control
In addition to deciding the unit(s) of analysis, another issue concerns which measures of control to use. These could include rates of hypoglycemia and hyperglycemia, percentage of glucose readings within various ranges (eg, <70, 70180, >180 mg/dL), mean glucose value, percentage of patient‐days during which the mean glucose is within various ranges, or the in control rate (ie, when all glucose values are within a certain range).
As with the various units of analysis, each of these measures of control has various advantages and disadvantages. For example, mean glucose is easy to report and understand, but masks extreme values. Percentage of glucose values within a certain range (eg, per patient, averaged across patients) presents a more complete picture but is a little harder to understand and will vary depending on the frequency of glucose monitoring. As mentioned above, this latter problem can be corrected in part by including only certain glucose values. Percent of glucose values within range may also be less sensitive to change than mean glucose (eg, a glucose that is lowered from 300 mg/dL to 200 mg/dL is still out of range). We recommend choosing a few, but not all, measures of control in order to get a complete picture of glycemic control. Over time one can then refine the measures being used to meet the needs of the glycemic control team and provide data that will drive the performance improvement process.
In critical care and perioperative settings, interest in glycemic control is often more intense around the time of a particular event such as major surgery or after admission to the ICU. Some measures commonly used in performing such analyses are:
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All values outside a target range within a designated crucial period. For example, the University Healthcare Consortium and other organizations use a simple metric to gauge perioperative glycemic control. They collect the fasting glucose on postoperative days 1 and 2 and then calculate the percentage of postoperative days with any fasting glucose >200 mg/dL. Of course, this is a very liberal target, but it can always be lowered in a stepwise fashion once it is regularly being reached.
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Three‐day blood glucose average. The Portland group uses the mean glucose of each patient for the period that includes the day of coronary artery bypass graft (CABG) surgery and the following 2 days. The 3‐day BG average (3‐BG) correlates very well with patient outcomes and can serve as a well‐defined target.2 It is likely that use of the 3‐BG would work well in other perioperative/trauma settings and could work in the medical ICU as well, with admission to the ICU as the starting point for calculation of the 3‐BG.
Hyperglycemic Index
Measuring the hyperglycemic index (HGI) is a validated method of summarizing glycemic control of ICU patients.3 It is designed to take into account the sometimes uneven distribution of patient testing. Time is plotted on the x‐axis and glucose values on the y‐axis. The HGI is calculated the area under the curve of glycemic values but above the upper limit of normal (ie, 110 mg/dL). Glucose values in the normal or hypoglycemic range are not included in the AUC. Mortality correlated well with this glycemic index. However, a recent observational study of glucometrics in patients hospitalized with acute myocardial infarction found that the simple mean of each patient's glucose values over the entire hospitalization was as predictive of in‐hospital mortality as the HGI or the time‐averaged glucose (AUC for all glucose values).4 In this study, metrics derived from glucose readings for the entire hospitalization were more predictive than those based on the first 24 or 48 hours or on the admission glucose.
Analyses Describing Change in Glycemic Control Over Time in the Hospital
In the critical care setting, this unit of analysis may be as simple as the mean time to reach the glycemic target on your insulin infusion protocol. On noncritical care wards, it is a bit more challenging to characterize the improvement (or clinical inertia) implied by failure of hyperglycemia to lessen as an inpatient stay progresses. One method is to calculate the mean glucose (or percentage of glucose values in a given range) for each patient on hospital day (HD) 1, and repeat for each HD (up to some reasonable limit, such as 5 or 7 days).
Recommendations:
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In noncritical units, we recommend a limited set of complementary measures, such as the patient‐day weighted mean glucose, mean percent of glucose readings per patient that are within a certain range, and percentage of patients whose mean glucose is within a certain range on each hospital day.
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In critical care units, it is often useful to focus measures around a certain critical event such as the 3‐day blood glucose average and to use measures such as the HGI that take advantage of more frequent blood glucose testing.
Definitions of Hyperglycemia and Hypoglycemia
Glucometrics outcomes will obviously depend on the thresholds established for hyperglycemia and hypoglycemia. Many centers define hypoglycemia as 60 mg/dL, whereas the ADA definition, based on physiologic changes that may take place, defines hypoglycemia (at least in the outpatient setting) as 70 mg/dL. Hypoglycemia may be further stratified by severity, with any glucose 40 mg/dL, for instance, defined as severe hypoglycemia.
Similarly, the definition of hyperglycemia (and therefore good control) must also be defined. Based on definitions developed by the ADA and AACE, the state of the medical literature, and current understanding of the pathophysiology of hyperglycemia, thresholds for critical care units include 110 mg/dL, 130 mg/dL, and 140 mg/dL, and options in noncritical care units include 130 mg/dL, 140 mg/dL, and 180 mg/dL. Because these thresholds implicitly assume adverse effects when glucose levels are above them, these levels are subject to revision as data become available confirming the benefits and safety of targeted glycemic control in various settings and patient populations.
Introducing optimal BG targets in a stepped fashion over time should also be considered. Furnary et al.2 have done this in the Portland Project, which tracks glycemic control in cardiac surgery patients receiving intravenous insulin therapy. The initial BG target for this project was <200 mg/dL; it was subsequently lowered stepwise over several years to 150 mg/dL, then to 120 mg/dL, and most recently to 110 mg/dL. This approach allows the safe introduction of targeted glycemic control and promotes acceptance of the concept by physicians and the allied nursing and medical staff.
Recommendations:
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In noncritical care units, it is reasonable to use 40 mg/dL for severe hypoglycemia, 70 mg/dL for hypoglycemia, 130 mg/dL for fasting hyperglycemia, 180 mg/dL for random or postprandial hyperglycemia, and 300 mg/dL for severe hyperglycemia, keeping in mind that these thresholds are arbitrary. In critical care units, values from 110 mg/dL to 140 mg/dL might be better thresholds for hyperglycemia, but it may take time to safely and effectively move an organization toward these lower targets.
Other Considerations Relative to Glucometrics
Yale Glucometrics Website
The Yale Informatics group has put together a Web‐based resource (
Other Analytic Resources
Commercially available software, such as the RALS system (Medical Automation Systems, Inc., Charlottesville, VA) can gather POC glucose measurements directly from devices and provide real‐time reports of glycemic control, stratified by inpatient unit, using user‐defined targets for hypoglycemia and hyperglycemia. While they are no substitute for a dedicated, on‐site data analyst, such systems can be very useful for smaller hospitals with minimal data or information technology support staff.
APPROACHES TO ANALYSIS: RUN CHARTS
Most conventional clinical trials hold interventions fixed for a period of time and compare results with and without the intervention. For quality improvement studies, this is still a valid way to proceed, especially if studied as a randomized controlled trial. Such methods may be preferred when the clinical question is Does this type of intervention work in general? and the desired output is publication in peer‐reviewed journals so that others can learn about and adopt the intervention to their own institution. A before and after study with a similar analytic approach may also be valid, although concerns about temporal trends and cointerventions potentially compromise the validity of such studies. This approach again assumes that an intervention is held fixed over time such that it is clear what patients received during each time period.
If the desired result is improvement at a given institution (the question is Did we improve care?) then it may be preferable to present results over time using run‐charts. In a run chart, the x‐axis is time and the y‐axis the desired metric, such as patient‐day weighted mean glucose. Points in time when interventions were introduced or modified can be highlighted. Run charts have several advantages over before‐and‐after summaries: they do not require interventions remaining fixed and are more compatible with continuous quality improvement methods, it is easier to see the effect of different aspects of the interventions as they occur, one can get a quicker picture of whether something is working, and it is easier to separate out the impact of the intervention from secular trends. Finally, the use of run charts does not imply the absence of statistical rigor. Run charts with statistical process control (SPC) limits5 can easily convey when the observed time trend is unlikely to be due to chance using prespecified P values. (A full discussion of SPC and other methods to study quality improvement interventions is beyond the scope of this article.)
ASSESSING PATTERNS OF INSULIN USE AND ORDER SET UTILIZATION
Besides measuring the impact of quality improvement interventions on glucose control, it is important to measure processes such as proper insulin use. As mentioned in other articles in this supplement, processes are much more sensitive to change than outcomes. Failure to change processes should lead one to make changes to the intervention.
ICU and Perioperative Settings
For ICU and perioperative settings, the major process measure will likely be use of the insulin infusion order set. Designation of BG levels that trigger insulin infusion in these settings should be agreed upon in advance. The number of patients who meet the predefined glycemic criteria would make up the denominator, and the number of patients on the insulin infusion order set would make up the numerator.
NonCritical Care Units
On noncritical care units, measuring the percentage of subcutaneous insulin regimens that contain a basal insulin is a useful way to monitor the impact of an intervention. A more detailed analysis could examine the percentage of patients on simultaneous basal and nutritional insulin (if applicable). An important measure of clinical inertia is to track the percentage of patients who had changes in their insulin regimens on days after hypoglycemic or hyperglycemic excursions. Another important measure is the frequency with which the standardized order set is being used, analogous to the measure of insulin infusion use in the ICU. A final process measure, indirectly related to insulin use, is the frequency of use of oral diabetes agents, especially by patients for whom their use is contraindicated (eg, patients with congestive heart failure who are on thiazolidinediones and patients with renal insufficiency or receiving intravenous contrast continued on metformin).
OTHER CONSIDERATIONS AND METRICS
Examples of other metrics that can be used to track the success of quality improvement efforts include:
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Glucose measurement within 8 hours of hospital admission.
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Glycated hemoglobin (A1C) measurement obtained or available within 30 days of admission to help guide inpatient and especially discharge management.
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Appropriate glucose testing in patients with diabetes or hyperglycemia (eg, 4 times per day in patients not on insulin infusion protocols, at least until 24 hours of euglycemia is documented).
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The percentage of patients on insulin with on‐time tray delivery.
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The timing of subcutaneous insulin administration in relation to glucose testing and nutrition delivery.
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Documentation of carbohydrate intake among patients who are eating.
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Satisfaction of physicians and nurses with order sets or protocols, using standard surveys.
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Physician and nurse knowledge, attitudes, and beliefs about insulin administration, fear of hypoglycemia, treatment of hypoglycemia, and glycemic control in the hospital.
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Patient satisfaction with their diabetes care in the hospital, including the education they received.
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Nursing and physician education/certification in insulin prescribing, insulin administration, and other diabetes care issues.
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Patient outcomes strongly associated with glycemic control, (eg, surgical wound infections, ICU LOS, catheter‐related bloodstream infections).
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Appropriate treatment and documentation of hypoglycemia (eg, in accordance with hospital policy).
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Documentation of severe hypoglycemic events through the hospital's adverse events reporting system (these may actually increase as change comes to the organization and as clinical personnel are more attuned to glycemic control).
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Root causes of hypoglycemic events, which can be used to understand and prevent future events.
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Appropriate transitions from IV to SC insulin regimens, (eg, starting basal insulin prior to discontinuing infusion in patients who have been on an insulin infusion of at least 2 units/hour or who have a known diagnosis of diabetes or A1C >7).
(Survey instruments and other measurement tools are available from the authors upon request.)
SHM GLYCEMIC CONTROL TASK FORCE SUMMARY RECOMMENDATIONS
The SHM Glycemic Control Task Force is working to develop standardized measures of inpatient glucose control and related indicators to track progress of hospital glycemic control initiatives (see the introduction to this supplement for a description of the charge and membership of this task force). The goals of the Task Force's metrics recommendations (Table 1) are several‐fold: (1) create a set of measurements that are complete but not overly burdensome; (2) create realistic measures that can be applied to institutions with different data management capabilities; and (3) allow for comparison across institutions for benchmarking purposes, evaluation of quality improvement projects, and reporting of results for formal research studies in this field.
Measurement Issue | NonCritical Care Units | Critical Care Units | ||
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Tier 1 Recommendations | Tier 2 Recommendations | Tier 1 Recommendations | Tier 2 Recommendations | |
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Patient inclusion and exclusion criteria | All adult patients with POC glucose testing (sampling acceptable). Exclude patients with DKA or HHS or who are pregnant. | All adult patients with diagnosis of diabetes by ICD‐9 code* or by glucose testing: random glucose (POC or laboratory) >180 mg/dL 2 or fasting glucose >130 mg/dL 2, excluding patients with DKA or HHS or who are pregnant. Additional analysis: exclude patients with <5 evaluable glucose readings, patients with LOS <2 days, or receiving palliative care. | All patients in every critical care unit (sampling acceptable). | Patients with DKA, HHS, or pregnancy in separate analyses. All patients in every critical care unit with random glucose (POC or laboratory) >140 mg/dL 2. |
Glucose reading inclusion and exclusion criteria | All POC glucose values. | Additional analysis: exclude glucose values on hospital day 1 and on hospital day 15 and after. Additional analysis: exclude glucose values measured within 60 minutes of a previous value. | All POC and other glucose values used to guide care. | |
Measures of safety | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | ||
Measures of glucose control | Analysis by patient‐day: Percentage of patient‐days with mean <140, <180 mg/dL and/or Percentage of patient‐days with all values <180 mg/dL. | Analysis by patient‐day: Patient day‐weighted mean glucose. | Analysis by glucose reading: Percentage of readings <110, <140 mg/dL. | 3‐BG as above for all patients in critical care units.∥ Hyperglycemic index for all patients in critical care units (AUC of glucose values above target). |
Analysis by patient stay: Percentage of patient stays with mean <140, <180 mg/dL. | Analysis by patient stay: Mean percentage of glucose readings of each patient <180 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with mean <110, <140 mg/dL, and/or Percentage of patient‐days with all values <110, <140 mg/dL. | ||
Analysis by hospital day: Percentage of patients with mean glucose readings <140, <180 mg/dL by hospital day (days 17). | Analysis by patient stay: 3‐day blood glucose average (3‐BG) for selected perioperative patients: Percentage of patients with 3‐BG <110, <140 mg/dL. Mean time (hours) to reach glycemic target (BG <110 or <140 mg/dL) on insulin infusion. | |||
Measures of insulin use | Percentage of patients on any subcutaneous insulin that has a scheduled basal insulin component (glargine, NPH, or detemir). | Percentage of patients with at least 2 POC and/or laboratory glucose readings >180 mg/dL who have a scheduled basal insulin component. Percentage of eating patients with hyperglycemia as defined above with scheduled basal insulin and nutritional insulin. Percentage of patients and patient‐days with any changes in insulin orders the day after 2 or more episodes of hypoglycemia or hyperglycemia (ie, <70 or >180 mg/dL). | Percentage of patients with 2 POC or laboratory glucose readings >140 mg/dL placed on insulin infusion protocol. | |
Other process measures | Glucose measured within 8 hours of hospital admission. | POC glucose testing at least 4 times a day for all patients with diabetes or hyperglycemia as defined above. | Glucose measured within 8 hours of hospital admission. | Appropriateness of hypoglycemia treatment and documentation. |
A1C measurement obtained or available within 30 days of admission. | Measures of adherence to specific components of management protocol. | Frequency of BG testing (eg, per protocol if on insulin infusion; every 68 hours if not). | Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | |
Appropriateness of hypoglycemia treatment and documentation. | Root causes of hypoglycemia. | |||
Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | Appropriate use of IV‐to‐SC insulin transition protocol. | |||
Root causes of hypoglycemia. |
For each domain of glycemic management (glycemic control, safety, and insulin use), the task force chose a set of best measures. They are presented as two tiers of measurement standards, depending on the capabilities of the institution and the planned uses of the data. Tier 1 includes measures that, although they do take time and resources to collect, are feasible for most institutions. Tier 2 measures are recommended for hospitals with easy manipulation of electronic sources of data and for reporting quality‐of‐care measures for widespread publication, that is, in the context of a research study. It should be emphasized that these recommendations are only meant as a guide: the actual measures chosen should meet the needs and capabilities of each institution.
We recognize that few data support the recommendations made by this task force, that such data are needed, and that the field of data collection and analysis for hospital glycemic management is rapidly evolving. The hope is to begin the standardization process, promote dialogue in this field, and eventually reach a consensus in collaboration with the ADA, AACE, and other pertinent stakeholders.
CONCLUSIONS
Like the field of inpatient glycemic management itself, the field of devising metrics to measure the quality of inpatient glycemic control is also in its infancy and quickly evolving. One should not be paralyzed by the lack of consensus regarding measurementthe important point is to pick a few complementary metrics and begin the process. The table of recommendations can hopefully serve as a starting point for many institutions, with a focus on efficacy (glycemic control), safety (hypoglycemia), and process (insulin use patterns). As your institution gains experience with measurement and the field evolves, your metrics will likely change. We recommend keeping all process and outcome data in its raw form so that it can be summarized in different ways over time. It is also important not to wait for the perfect data collection tool before beginning to analyze data: sampling and paper processes are acceptable if automated data collection is not yet possible. Eventually, blood glucose meter readings should be downloaded into a central database that interfaces with hospital data repositories so data can be analyzed in conjunction with patient, service, and unit‐level information. Only with a rigorous measurement process can institutions hope to know whether their changes are resulting in improved care for patients.
Data collection, analysis, and presentation are key to the success of any hospital glycemic control initiative. Such efforts enable the management team to track improvements in processes and outcomes, make necessary changes to their quality improvement efforts, justify the provision of necessary time and resources, and share their results with others. Reliable metrics for assessing glycemic control and frequency of hypoglycemia are essential to accomplish these tasks and to assess whether interventions result in more benefit than harm. Hypoglycemia metrics must be especially convincing because fear of hypoglycemia remains a major source of clinical inertia, impeding efforts to improve glucose control.
Currently, there are no official standards or guidelines for formulating metrics on the quality of inpatient glycemic control. This creates several problems. First, different metrics vary in their biases and in their responsiveness to change. Thus, use of a poor metric could lead to either a falsely positive or falsely negative impression that a quality improvement intervention is in fact improving glycemic control. Second, the proliferation of different measures and analytical plans in the research and quality improvement literature make it very difficult for hospitals to compare baseline performance, determine need for improvement, and understand which interventions may be most effective.
A related article in this supplement provides the rationale for improved inpatient glycemic control. That article argues that the current state of inpatient glycemic control, with the frequent occurrence of severe hyperglycemia and irrational insulin ordering, cannot be considered acceptable, especially given the large body of data (albeit largely observational) linking hyperglycemia to negative patient outcomes. However, regardless of whether one is an advocate or skeptic of tighter glucose control in the intensive care unit (ICU) and especially the non‐ICU setting, there is no question that standardized, valid, and reliable metrics are needed to compare efforts to improve glycemic control, better understand whether such control actually improves patient care, and closely monitor patient safety.
This article provides a summary of practical suggestions to assess glycemic control, insulin use patterns, and safety (hypoglycemia and severe hyperglycemia). In particular, we discuss the pros and cons of various measurement choices. We conclude with a tiered summary of recommendations for practical metrics that we hope will be useful to individual improvement teams. This article is not a consensus statement but rather a starting place that we hope will begin to standardize measurement across institutions and advance the dialogue on this subject. To more definitely address this problem, we call on the American Association of Clinical Endocrinologists (AACE), American Diabetes Association (ADA), Society of Hospital Medicine (SHM), and others to agree on consensus standards regarding metrics for the quality of inpatient glycemic control.
MEASURING GLYCEMIC CONTROL: GLUCOMETRICS
Glucometrics may be defined as the systematic analysis of blood glucose (BG) dataa phrase initially coined specifically for the inpatient setting. There are numerous ways to do these analyses, depending on which patients and glucose values are considered, the definitions used for hypoglycemia and hyperglycemia, the unit of measurement (eg, patient, patient‐day, individual glucose value), and the measure of control (eg, mean, median, percent of glucose readings within a certain range). We consider each of these dimensions in turn.
Defining the Target Patient Population
The first decision to be made is which patients to include in your analysis. Choices include the following:
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Patients with a discharge diagnosis of diabetes: this group has face validity and intuitive appeal, is easy to identify retrospectively, and may capture some untested/untreated diabetics, but will miss patients with otherwise undiagnosed diabetes and stress hyperglycemia. It is also subject to the variable accuracy of billing codes.
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Patients with a certain number of point‐of‐care (POC) glucose measurements: this group is also easy to identify, easy to measure, and will include patients with hyperglycemia without a previous diagnosis of diabetes, but will miss patients with untested/untreated hyperglycemia. Also, if glucose levels are checked on normoglycemic, nondiabetic patients, these values may dilute the overall assessment of glycemic control.
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Patients treated with insulin in the hospital: this is a good choice if the purpose is mainly drug safety and avoidance of hypoglycemia, but by definition excludes most untreated patients.
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Patients with 2 or more BG values (laboratory and/or POC) over a certain threshold (eg, >180 mg/dL). This will likely capture more patients with inpatient hyperglycemia, whether or not detected by the medical team, but is subject to wide variations in the frequency and timing of laboratory glucose testing, including whether or not the values are pre‐prandial (note that even preprandial POC glucose measurements are not always in fact fasting values).
Other considerations include the following:
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Are there natural patient subgroups that should be measured and analyzed separately because of different guidelines? For example, there probably should be separate/emndependent inclusion criteria and analyses for critical care and noncritical care units because their glycemic targets and management considerations differ.
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Which patients should be excluded? For example, if targeting subcutaneous insulin use in general hospitalized patients, one might eliminate those patients who are admitted specifically as the result of a diabetes emergency (eg, diabetic ketoacidosis [DKA] and hyperglycemic hyperosmolar state [HHS]), as their marked and prolonged hyperglycemia will skew BG data. Pregnant women should generally be excluded from broad‐based analyses or considered as a discrete category because they have very different targets for BG therapy. Patients with short lengths of stay may be less likely to benefit from tight glucose control and may also be considered for post hoc exclusion. One might also exclude patients with very few evaluable glucose readings (eg, fewer than 5) to ensure that measurement is meaningful for a given patient, keeping in mind that this may also exclude patients with undetected hyperglycemia, as mentioned above. Finally, patients receiving palliative care should also be considered for exclusion if feasible.
Recommendation: Do not limit analyses to only those patients with a diagnosis of diabetes or only those on insulin, which will lead to biased results.
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For noncritical care patients, we recommend a combined approach: adult patients with a diagnosis of diabetes (e. g. using diagnosis‐related group [DRG] codes 294 or 295 or International Classification of Diseases 9th edition [ICD9] codes 250.xx) or with hyperglycemia (eg, 2 or more random laboratory and/or point of care (POC) BG values >180 mg/dL or 2 or more fasting BG values >130 mg/dL), excluding patients with DKA or HHS or who are pregnant.
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For critical care units, we recommend either all patients, or patients with at least mild hyperglycemia (eg, 2 random glucose levels >140 mg/dL). Critical care patients with DKA, HHS, and pregnancy should be evaluated separately if possible.
Which Glucose Values to Include and Exclude
To answer this question, we first need to decide which method to use for BG measurement. There are several ways to measure BG, including the type of sample collected (capillary [fingerstick], arterial, and venous) and the technique used (central laboratory analyzing plasma, central laboratory analyzing whole blood [eg, from an arterial blood gas sample], glucose meter [usually calibrated to plasma], etc.). The POC (eg, capillary, glucose meter) glucose measurements alone are often preferred in the non‐ICU setting because laboratory plasma values generally provide little additional information and typically lower the mean glucose by including redundant fasting values.1 In critical care units, several different methods are often used together, and each merits inclusion. The inherent differences in calibration between the methods do not generally require separate analyses, especially given the frequency of testing in the ICU setting.
The next question is which values to include in analyses. In some situations, it may be most useful to focus on a certain period of hospitalization, such as the day of a procedure and the next 2 days in assessing the impact of the quality of perioperative care, or the first 14 days of a noncritical care stay to keep outliers for length of stay (LOS) from skewing the data. In the non‐ICU setting, it may be reasonable to exclude the first day of hospitalization, as early BG control is impacted by multiple variables beyond direct control of the clinician (eg, glucose control prior to admission, severity of presenting illness) and may not realistically reflect your interventions. (Keep in mind, however, that it may be useful to adjust for the admission glucose value in multivariable models given its importance to clinical outcomes and its strong relationship to subsequent inpatient glucose control.) However, in critical care units, it is reasonable to include the first day's readings in analyses given the high frequency of glucose measurements in this setting and the expectation that glucose control should be achieved within a few hours of starting an intravenous insulin infusion.
If feasible to do so with your institution's data capture methods, you may wish to select only the regularly scheduled (before each meal [qAC] and at bedtime [qHS], or every 6 hours [q6h]) glucose readings for inclusion in the summary data of glycemic control in the non‐ICU setting, thereby reducing bias caused by repeated measurements around extremes of glycemic excursions. An alternative in the non‐ICU setting is to censor glucose readings within 60 minutes of a previous reading.
Recommendation:
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In the non‐ICU setting, we recommend first looking at all POC glucose values and if possible repeating the analyses excluding hospital day 1 and hospital day 15 and beyond, and also excluding glucose values measured within 60 minutes of a previous value.
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In critical care units, we recommend evaluating all glucose readings used to guide care.
Units of Analysis
There are several different units of analysis, each with its own advantages and disadvantages:
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Glucose value: this is the simplest measure and the one with the most statistical power. All glucose values for all patients of interest comprise the denominator. A report might say, for example, that 1% of the 1000 glucose values were <70 mg/dL during a certain period or that the mean of all glucose values collected for the month from patients in noncritical care areas was 160 mg/dL. The potential disadvantages of this approach are that these analyses are less clinically relevant than patient‐level analyses and that patients with many glucose readings and long hospitalizations may skew the data.
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Patient (or the Patient Stay, [ie, the entire hospitalization]): all patients who are monitored make up the denominator. The numerator may be the percentage of patients with any hypoglycemia during their hospital stay or the percentage of patients achieving a certain mean glucose during their hospitalization, for example. This is inherently more clinically meaningful than using glucose value as a unit of analysis. A major disadvantage is not controlling for LOS effects. For example, a hospitalized patient with a long LOS is much more likely to be characterized as having at least 1 hypoglycemic value than is a patient with a shorter LOS. Another shortcoming is that this approach does not correct for uneven distribution of testing. A patient's mean glucose might be calculated on the basis of 8 glucose values on the first day of hospitalization, 4 on the second day, and 1 on the third day. Despite all these shortcomings, reporting by patient remains a popular and valid method of presenting glycemic control results, particularly when complemented by other views and refined to control for the number of readings per day.
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Monitored Patient‐Day: The denominator in this setting is the total number of days a patient glucose level is monitored. The benefits of this method have been described and advocated in the literature.1 As with patient‐level analyses, this measure will be more rigorous and meaningful if the BG measures to be evaluated have been standardized. Typical reports might include percentage of monitored days with any hypoglycemia, or percentage of monitored days with all glucose values in the desired range. This unit of analysis may be considered more difficult to generate and to interpret. On the other hand, it is clinically relevant, less biased by LOS effects, and may be considered the most actionable metric by clinicians. This method provides a good balance when presented with data organized by patient.
The following example uses all 3 units of measurement, in this case to determine the rate of hypoglycemia, demonstrating the different but complementary information that each method provides:
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In 1 month, 3900 POC glucose measurements were obtained from 286 patients representing 986 monitored patient‐days. With hypoglycemia defined as POC BG 60 mg/dL, the results showed the following:
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50 of 3900 measurements (1.4%) were hypoglycemic 22 of 286 patients (7.7%) had 1 hypoglycemic episodes
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40 of 986 monitored days (4.4%) had 1 hypoglycemic episodes.
The metric based on the number of glucose readings could be considered the least clinically relevant because it is unclear how many patients were affected; moreover, it may be based on variable testing patterns among patients, and could be influenced disproportionately by 1 patient with frequent hypoglycemia, many glucose readings, and/or a long LOS. One could argue that the patient‐stay metric is artificially elevated because a single hypoglycemic episode characterizes the entire stay as hypoglycemic. On the other hand, at least it acknowledges the number of patients affected by hypoglycemia. The patient‐day unit of analysis likely provides the most balanced view, one that is clinically relevant and measured over a standard period of time, and less biased by LOS and frequency of testing.
One way to express patient‐day glycemic control that deserves special mention is the patient‐day weighted mean. A mean glucose is calculated for each patient‐day, and then the mean is calculated across all patient‐days. The advantage of this approach is that it corrects for variation in the number of glucose readings each day; all hospital days are weighted equally.
Recommendation:
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In noncritical care units, we recommend a combination of patient‐day and patient‐stay measures.
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In critical care units, it is acceptable to also use glucose reading as the unit of measurement given more frequent and uniform data collection, but it should be complemented by more meaningful patient‐day and patient‐stay measures.
Measures of Control
In addition to deciding the unit(s) of analysis, another issue concerns which measures of control to use. These could include rates of hypoglycemia and hyperglycemia, percentage of glucose readings within various ranges (eg, <70, 70180, >180 mg/dL), mean glucose value, percentage of patient‐days during which the mean glucose is within various ranges, or the in control rate (ie, when all glucose values are within a certain range).
As with the various units of analysis, each of these measures of control has various advantages and disadvantages. For example, mean glucose is easy to report and understand, but masks extreme values. Percentage of glucose values within a certain range (eg, per patient, averaged across patients) presents a more complete picture but is a little harder to understand and will vary depending on the frequency of glucose monitoring. As mentioned above, this latter problem can be corrected in part by including only certain glucose values. Percent of glucose values within range may also be less sensitive to change than mean glucose (eg, a glucose that is lowered from 300 mg/dL to 200 mg/dL is still out of range). We recommend choosing a few, but not all, measures of control in order to get a complete picture of glycemic control. Over time one can then refine the measures being used to meet the needs of the glycemic control team and provide data that will drive the performance improvement process.
In critical care and perioperative settings, interest in glycemic control is often more intense around the time of a particular event such as major surgery or after admission to the ICU. Some measures commonly used in performing such analyses are:
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All values outside a target range within a designated crucial period. For example, the University Healthcare Consortium and other organizations use a simple metric to gauge perioperative glycemic control. They collect the fasting glucose on postoperative days 1 and 2 and then calculate the percentage of postoperative days with any fasting glucose >200 mg/dL. Of course, this is a very liberal target, but it can always be lowered in a stepwise fashion once it is regularly being reached.
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Three‐day blood glucose average. The Portland group uses the mean glucose of each patient for the period that includes the day of coronary artery bypass graft (CABG) surgery and the following 2 days. The 3‐day BG average (3‐BG) correlates very well with patient outcomes and can serve as a well‐defined target.2 It is likely that use of the 3‐BG would work well in other perioperative/trauma settings and could work in the medical ICU as well, with admission to the ICU as the starting point for calculation of the 3‐BG.
Hyperglycemic Index
Measuring the hyperglycemic index (HGI) is a validated method of summarizing glycemic control of ICU patients.3 It is designed to take into account the sometimes uneven distribution of patient testing. Time is plotted on the x‐axis and glucose values on the y‐axis. The HGI is calculated the area under the curve of glycemic values but above the upper limit of normal (ie, 110 mg/dL). Glucose values in the normal or hypoglycemic range are not included in the AUC. Mortality correlated well with this glycemic index. However, a recent observational study of glucometrics in patients hospitalized with acute myocardial infarction found that the simple mean of each patient's glucose values over the entire hospitalization was as predictive of in‐hospital mortality as the HGI or the time‐averaged glucose (AUC for all glucose values).4 In this study, metrics derived from glucose readings for the entire hospitalization were more predictive than those based on the first 24 or 48 hours or on the admission glucose.
Analyses Describing Change in Glycemic Control Over Time in the Hospital
In the critical care setting, this unit of analysis may be as simple as the mean time to reach the glycemic target on your insulin infusion protocol. On noncritical care wards, it is a bit more challenging to characterize the improvement (or clinical inertia) implied by failure of hyperglycemia to lessen as an inpatient stay progresses. One method is to calculate the mean glucose (or percentage of glucose values in a given range) for each patient on hospital day (HD) 1, and repeat for each HD (up to some reasonable limit, such as 5 or 7 days).
Recommendations:
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In noncritical units, we recommend a limited set of complementary measures, such as the patient‐day weighted mean glucose, mean percent of glucose readings per patient that are within a certain range, and percentage of patients whose mean glucose is within a certain range on each hospital day.
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In critical care units, it is often useful to focus measures around a certain critical event such as the 3‐day blood glucose average and to use measures such as the HGI that take advantage of more frequent blood glucose testing.
Definitions of Hyperglycemia and Hypoglycemia
Glucometrics outcomes will obviously depend on the thresholds established for hyperglycemia and hypoglycemia. Many centers define hypoglycemia as 60 mg/dL, whereas the ADA definition, based on physiologic changes that may take place, defines hypoglycemia (at least in the outpatient setting) as 70 mg/dL. Hypoglycemia may be further stratified by severity, with any glucose 40 mg/dL, for instance, defined as severe hypoglycemia.
Similarly, the definition of hyperglycemia (and therefore good control) must also be defined. Based on definitions developed by the ADA and AACE, the state of the medical literature, and current understanding of the pathophysiology of hyperglycemia, thresholds for critical care units include 110 mg/dL, 130 mg/dL, and 140 mg/dL, and options in noncritical care units include 130 mg/dL, 140 mg/dL, and 180 mg/dL. Because these thresholds implicitly assume adverse effects when glucose levels are above them, these levels are subject to revision as data become available confirming the benefits and safety of targeted glycemic control in various settings and patient populations.
Introducing optimal BG targets in a stepped fashion over time should also be considered. Furnary et al.2 have done this in the Portland Project, which tracks glycemic control in cardiac surgery patients receiving intravenous insulin therapy. The initial BG target for this project was <200 mg/dL; it was subsequently lowered stepwise over several years to 150 mg/dL, then to 120 mg/dL, and most recently to 110 mg/dL. This approach allows the safe introduction of targeted glycemic control and promotes acceptance of the concept by physicians and the allied nursing and medical staff.
Recommendations:
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In noncritical care units, it is reasonable to use 40 mg/dL for severe hypoglycemia, 70 mg/dL for hypoglycemia, 130 mg/dL for fasting hyperglycemia, 180 mg/dL for random or postprandial hyperglycemia, and 300 mg/dL for severe hyperglycemia, keeping in mind that these thresholds are arbitrary. In critical care units, values from 110 mg/dL to 140 mg/dL might be better thresholds for hyperglycemia, but it may take time to safely and effectively move an organization toward these lower targets.
Other Considerations Relative to Glucometrics
Yale Glucometrics Website
The Yale Informatics group has put together a Web‐based resource (
Other Analytic Resources
Commercially available software, such as the RALS system (Medical Automation Systems, Inc., Charlottesville, VA) can gather POC glucose measurements directly from devices and provide real‐time reports of glycemic control, stratified by inpatient unit, using user‐defined targets for hypoglycemia and hyperglycemia. While they are no substitute for a dedicated, on‐site data analyst, such systems can be very useful for smaller hospitals with minimal data or information technology support staff.
APPROACHES TO ANALYSIS: RUN CHARTS
Most conventional clinical trials hold interventions fixed for a period of time and compare results with and without the intervention. For quality improvement studies, this is still a valid way to proceed, especially if studied as a randomized controlled trial. Such methods may be preferred when the clinical question is Does this type of intervention work in general? and the desired output is publication in peer‐reviewed journals so that others can learn about and adopt the intervention to their own institution. A before and after study with a similar analytic approach may also be valid, although concerns about temporal trends and cointerventions potentially compromise the validity of such studies. This approach again assumes that an intervention is held fixed over time such that it is clear what patients received during each time period.
If the desired result is improvement at a given institution (the question is Did we improve care?) then it may be preferable to present results over time using run‐charts. In a run chart, the x‐axis is time and the y‐axis the desired metric, such as patient‐day weighted mean glucose. Points in time when interventions were introduced or modified can be highlighted. Run charts have several advantages over before‐and‐after summaries: they do not require interventions remaining fixed and are more compatible with continuous quality improvement methods, it is easier to see the effect of different aspects of the interventions as they occur, one can get a quicker picture of whether something is working, and it is easier to separate out the impact of the intervention from secular trends. Finally, the use of run charts does not imply the absence of statistical rigor. Run charts with statistical process control (SPC) limits5 can easily convey when the observed time trend is unlikely to be due to chance using prespecified P values. (A full discussion of SPC and other methods to study quality improvement interventions is beyond the scope of this article.)
ASSESSING PATTERNS OF INSULIN USE AND ORDER SET UTILIZATION
Besides measuring the impact of quality improvement interventions on glucose control, it is important to measure processes such as proper insulin use. As mentioned in other articles in this supplement, processes are much more sensitive to change than outcomes. Failure to change processes should lead one to make changes to the intervention.
ICU and Perioperative Settings
For ICU and perioperative settings, the major process measure will likely be use of the insulin infusion order set. Designation of BG levels that trigger insulin infusion in these settings should be agreed upon in advance. The number of patients who meet the predefined glycemic criteria would make up the denominator, and the number of patients on the insulin infusion order set would make up the numerator.
NonCritical Care Units
On noncritical care units, measuring the percentage of subcutaneous insulin regimens that contain a basal insulin is a useful way to monitor the impact of an intervention. A more detailed analysis could examine the percentage of patients on simultaneous basal and nutritional insulin (if applicable). An important measure of clinical inertia is to track the percentage of patients who had changes in their insulin regimens on days after hypoglycemic or hyperglycemic excursions. Another important measure is the frequency with which the standardized order set is being used, analogous to the measure of insulin infusion use in the ICU. A final process measure, indirectly related to insulin use, is the frequency of use of oral diabetes agents, especially by patients for whom their use is contraindicated (eg, patients with congestive heart failure who are on thiazolidinediones and patients with renal insufficiency or receiving intravenous contrast continued on metformin).
OTHER CONSIDERATIONS AND METRICS
Examples of other metrics that can be used to track the success of quality improvement efforts include:
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Glucose measurement within 8 hours of hospital admission.
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Glycated hemoglobin (A1C) measurement obtained or available within 30 days of admission to help guide inpatient and especially discharge management.
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Appropriate glucose testing in patients with diabetes or hyperglycemia (eg, 4 times per day in patients not on insulin infusion protocols, at least until 24 hours of euglycemia is documented).
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The percentage of patients on insulin with on‐time tray delivery.
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The timing of subcutaneous insulin administration in relation to glucose testing and nutrition delivery.
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Documentation of carbohydrate intake among patients who are eating.
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Satisfaction of physicians and nurses with order sets or protocols, using standard surveys.
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Physician and nurse knowledge, attitudes, and beliefs about insulin administration, fear of hypoglycemia, treatment of hypoglycemia, and glycemic control in the hospital.
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Patient satisfaction with their diabetes care in the hospital, including the education they received.
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Nursing and physician education/certification in insulin prescribing, insulin administration, and other diabetes care issues.
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Patient outcomes strongly associated with glycemic control, (eg, surgical wound infections, ICU LOS, catheter‐related bloodstream infections).
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Appropriate treatment and documentation of hypoglycemia (eg, in accordance with hospital policy).
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Documentation of severe hypoglycemic events through the hospital's adverse events reporting system (these may actually increase as change comes to the organization and as clinical personnel are more attuned to glycemic control).
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Root causes of hypoglycemic events, which can be used to understand and prevent future events.
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Appropriate transitions from IV to SC insulin regimens, (eg, starting basal insulin prior to discontinuing infusion in patients who have been on an insulin infusion of at least 2 units/hour or who have a known diagnosis of diabetes or A1C >7).
(Survey instruments and other measurement tools are available from the authors upon request.)
SHM GLYCEMIC CONTROL TASK FORCE SUMMARY RECOMMENDATIONS
The SHM Glycemic Control Task Force is working to develop standardized measures of inpatient glucose control and related indicators to track progress of hospital glycemic control initiatives (see the introduction to this supplement for a description of the charge and membership of this task force). The goals of the Task Force's metrics recommendations (Table 1) are several‐fold: (1) create a set of measurements that are complete but not overly burdensome; (2) create realistic measures that can be applied to institutions with different data management capabilities; and (3) allow for comparison across institutions for benchmarking purposes, evaluation of quality improvement projects, and reporting of results for formal research studies in this field.
Measurement Issue | NonCritical Care Units | Critical Care Units | ||
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Tier 1 Recommendations | Tier 2 Recommendations | Tier 1 Recommendations | Tier 2 Recommendations | |
| ||||
Patient inclusion and exclusion criteria | All adult patients with POC glucose testing (sampling acceptable). Exclude patients with DKA or HHS or who are pregnant. | All adult patients with diagnosis of diabetes by ICD‐9 code* or by glucose testing: random glucose (POC or laboratory) >180 mg/dL 2 or fasting glucose >130 mg/dL 2, excluding patients with DKA or HHS or who are pregnant. Additional analysis: exclude patients with <5 evaluable glucose readings, patients with LOS <2 days, or receiving palliative care. | All patients in every critical care unit (sampling acceptable). | Patients with DKA, HHS, or pregnancy in separate analyses. All patients in every critical care unit with random glucose (POC or laboratory) >140 mg/dL 2. |
Glucose reading inclusion and exclusion criteria | All POC glucose values. | Additional analysis: exclude glucose values on hospital day 1 and on hospital day 15 and after. Additional analysis: exclude glucose values measured within 60 minutes of a previous value. | All POC and other glucose values used to guide care. | |
Measures of safety | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with 1 or more values <40, <70, and >300 mg/dL. | ||
Measures of glucose control | Analysis by patient‐day: Percentage of patient‐days with mean <140, <180 mg/dL and/or Percentage of patient‐days with all values <180 mg/dL. | Analysis by patient‐day: Patient day‐weighted mean glucose. | Analysis by glucose reading: Percentage of readings <110, <140 mg/dL. | 3‐BG as above for all patients in critical care units.∥ Hyperglycemic index for all patients in critical care units (AUC of glucose values above target). |
Analysis by patient stay: Percentage of patient stays with mean <140, <180 mg/dL. | Analysis by patient stay: Mean percentage of glucose readings of each patient <180 mg/dL. | Analysis by patient‐day: Percentage of patient‐days with mean <110, <140 mg/dL, and/or Percentage of patient‐days with all values <110, <140 mg/dL. | ||
Analysis by hospital day: Percentage of patients with mean glucose readings <140, <180 mg/dL by hospital day (days 17). | Analysis by patient stay: 3‐day blood glucose average (3‐BG) for selected perioperative patients: Percentage of patients with 3‐BG <110, <140 mg/dL. Mean time (hours) to reach glycemic target (BG <110 or <140 mg/dL) on insulin infusion. | |||
Measures of insulin use | Percentage of patients on any subcutaneous insulin that has a scheduled basal insulin component (glargine, NPH, or detemir). | Percentage of patients with at least 2 POC and/or laboratory glucose readings >180 mg/dL who have a scheduled basal insulin component. Percentage of eating patients with hyperglycemia as defined above with scheduled basal insulin and nutritional insulin. Percentage of patients and patient‐days with any changes in insulin orders the day after 2 or more episodes of hypoglycemia or hyperglycemia (ie, <70 or >180 mg/dL). | Percentage of patients with 2 POC or laboratory glucose readings >140 mg/dL placed on insulin infusion protocol. | |
Other process measures | Glucose measured within 8 hours of hospital admission. | POC glucose testing at least 4 times a day for all patients with diabetes or hyperglycemia as defined above. | Glucose measured within 8 hours of hospital admission. | Appropriateness of hypoglycemia treatment and documentation. |
A1C measurement obtained or available within 30 days of admission. | Measures of adherence to specific components of management protocol. | Frequency of BG testing (eg, per protocol if on insulin infusion; every 68 hours if not). | Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | |
Appropriateness of hypoglycemia treatment and documentation. | Root causes of hypoglycemia. | |||
Clinical events of severe hypoglycemia reported through the organization's critical events reporting tool. | Appropriate use of IV‐to‐SC insulin transition protocol. | |||
Root causes of hypoglycemia. |
For each domain of glycemic management (glycemic control, safety, and insulin use), the task force chose a set of best measures. They are presented as two tiers of measurement standards, depending on the capabilities of the institution and the planned uses of the data. Tier 1 includes measures that, although they do take time and resources to collect, are feasible for most institutions. Tier 2 measures are recommended for hospitals with easy manipulation of electronic sources of data and for reporting quality‐of‐care measures for widespread publication, that is, in the context of a research study. It should be emphasized that these recommendations are only meant as a guide: the actual measures chosen should meet the needs and capabilities of each institution.
We recognize that few data support the recommendations made by this task force, that such data are needed, and that the field of data collection and analysis for hospital glycemic management is rapidly evolving. The hope is to begin the standardization process, promote dialogue in this field, and eventually reach a consensus in collaboration with the ADA, AACE, and other pertinent stakeholders.
CONCLUSIONS
Like the field of inpatient glycemic management itself, the field of devising metrics to measure the quality of inpatient glycemic control is also in its infancy and quickly evolving. One should not be paralyzed by the lack of consensus regarding measurementthe important point is to pick a few complementary metrics and begin the process. The table of recommendations can hopefully serve as a starting point for many institutions, with a focus on efficacy (glycemic control), safety (hypoglycemia), and process (insulin use patterns). As your institution gains experience with measurement and the field evolves, your metrics will likely change. We recommend keeping all process and outcome data in its raw form so that it can be summarized in different ways over time. It is also important not to wait for the perfect data collection tool before beginning to analyze data: sampling and paper processes are acceptable if automated data collection is not yet possible. Eventually, blood glucose meter readings should be downloaded into a central database that interfaces with hospital data repositories so data can be analyzed in conjunction with patient, service, and unit‐level information. Only with a rigorous measurement process can institutions hope to know whether their changes are resulting in improved care for patients.
- “Glucometrics”—assessing the quality of inpatient glucose management.Diabetes Technol Ther.2006;8:560–569. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland Diabetic Project.Endocr Pract.2004;10(suppl 2):21–33. , , .
- Hyperglycaemic index as a tool to assess glucose control: a retrospective study.Crit Care.2004;8:R122–R127. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Statistical process control as a tool for research and healthcare improvement.Qual Saf Health Care.2003;12:458–464. , , .
- “Glucometrics”—assessing the quality of inpatient glucose management.Diabetes Technol Ther.2006;8:560–569. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland Diabetic Project.Endocr Pract.2004;10(suppl 2):21–33. , , .
- Hyperglycaemic index as a tool to assess glucose control: a retrospective study.Crit Care.2004;8:R122–R127. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Statistical process control as a tool for research and healthcare improvement.Qual Saf Health Care.2003;12:458–464. , , .
Supporting Inpatient Glycemic Control Programs Now
Medical centers are faced with multiple competing priorities when deciding how to focus their improvement efforts and meet the ever expanding menu of publicly reported and regulatory issues. In this article we expand on the rationale for supporting inpatient glycemic control programs as a priority that should be moved near the top of the list. We review the evidence for establishing glycemic range targets, and also review the limitations of this evidence, acknowledging, as does the American Diabetes Association (ADA), that in both the critical care and non‐critical care venue, glycemic goals must take into account the individual patient's situation as well as hospital system support for achieving these goals.1, 2 We emphasize that inpatient glycemic control programs are needed to address a wide variety of quality and safety issues surrounding the care of the inpatient with diabetes and hyperglycemia, and we wish to elevate the dialogue beyond arguments surrounding adoption of one glycemic target versus another. The Society of Hospital Medicine Glycemic Control Task Force members are not in unanimous agreement with the American Association of Clinical Endocrinologists (AACE)/ADA inpatient glycemic targets. However, we do agree on several other important points, which we will expand on in this article:
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Uncontrolled hyperglycemia and iatrogenic hypoglycemia are common and potentially dangerous situations that are largely preventable with safe and proven methods.
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The current state of care for our inpatients with hyperglycemia is unacceptably poor on a broad scale, with substandard education, communication, coordination, and treatment issues.
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Concerted efforts with changes in the design of the process of care are needed to improve this state of affairs.
DIABETES AND HYPERGLYCEMIA ARE VERY COMMON INPATIENT CONDITIONS
Diabetes mellitus (DM) has reached epidemic proportions in the United States. A reported 9.3% of adults over 20 years of age have diabetes, representing over 20 million persons. Despite increasing awareness, diabetes remains undiagnosed in approximately 30% of these persons.3 Concurrent with the increasing prevalence of diabetes in the U.S. population from 1980 through 2003, the number of hospital discharges with diabetes as any listed diagnosis more than doubled, going from 2.2 to 5.1 million discharges.4 Hospital care for patients with diabetes and hyperglycemia poses a significant health economic burden in the United States, representing over 40 billion dollars in annual direct medical expenditures.5
Hyperglycemia in the hospital may be due to known diabetes, to previously unrecognized diabetes, to prediabetes, and/or to the stress of surgery or illness. Deterioration in glycemic control in the hospital setting is most commonly associated with one or more factors, including stress‐induced release of insulin counterregulatory hormones (catecholamines, cortisol, glucagon, and growth hormone), exogenous administration of high dose glucocorticoids, and suboptimal glycemic management strategies.68 In a Belgian medical intensive care unit (MICU) randomized controlled trial (RCT) of strict versus conventional glycemic control, mean blood glucose (BG) on admission to the unit in the intention to treat group was 162 70 mg/dL (n = 1200),9 and in this group's RCT of 1548 surgical intensive care unit (SICU) patients, BG > 110 mg/dL was observed in over 70% of subjects.10 Mean BG of >145 mg/dL has been reported in 39%11 and BG >200 mg/dL in anywhere from 11% to 31% of intensive care unit (ICU) patients.10, 12 For general medicine and surgery, 1 study of 2030 patients admitted to a teaching hospital revealed that 26% of admissions had a known history of DM and 12% had new hyperglycemia, as evidenced by an admission or in‐hospital fasting BG of 126 mg/dL or more or a random BG of 200 mg/dL or more on 2 or more determinations.13 National and regional estimates on hospital use maintained by the Agency for Healthcare Research and Quality include data concerning diabetes diagnoses alone, without hyperglycemia, and may be displayed by querying its Web site.14 In cardiovascular populations almost 70% of patients having a first myocardial infarction have been reported to have either known DM, previously unrecognized diabetes, or impaired glucose tolerance.15
THE EVIDENCE SUPPORTS INPATIENT GLYCEMIC CONTROL
Evidence: Physiology
The pathophysiologic mechanisms through which hyperglycemia is linked to suboptimal outcomes in the hospital are complex and multifactorial. Although it is beyond the scope of this article to discuss these mechanisms in detail, research has broadly focused in the following areas: (1) immune system dysfunction, associated with a proinflammatory state and impaired white blood cell function; (2) metabolic derangements leading to oxidative stress, release of free fatty acids, reduction in endogenous insulin secretion, and fluid and electrolyte imbalance; and (3) a wide variety of vascular system responses (eg, endothelial dysfunction with impairment of tissue perfusion, a prothrombotic state, increased platelet aggregation, and left ventricular dysfunction).8, 1618
Conversely administration of insulin suppresses or reverses many of these abnormalities including generation of reactive oxygen species (ROS) and activation of inflammatory mechanisms,19 and leads to a fall in C‐reactive protein, which accompanied the clinical benefit of intensive insulin therapy (IIT) in the Leuven, Belgium, ICU population,20 and prevents mitochondrial abnormalities in hepatocytes.21 In the same surgical ICU cohort, Langouche et al.22 report suppression of intracellular adhesion molecule‐1 (ICAM‐1) and E‐selectin, markers of inflammation, and reduction in plasma nitric oxide (NO) and innate nitric oxide (iNOS) expression with insulin administration in patients treated with intravenous (IV) IIT.22 These data further support the role of insulin infusion in suppressing inflammation and endothelial dysfunction. The authors suggest that maintaining normoglycemia with IIT during critical illness protects the endothelium, thereby contributing to prevention of organ failure and death.22 Based on accumulating data in the literature such as that cited above, it has been suggested that a new paradigm in which glucose and insulin are related not only through their metabolic action but also through inflammatory mechanisms offers important potential therapeutic opportunities.19
Evidence: Epidemiology/Observational Studies/Non‐RCT Interventional Studies
A strong association between hospital hyperglycemia and negative outcomes has been reported in numerous observational studies in diverse adult medical and surgical settings. In over 1800 hospital admissions, those with new hyperglycemia had an in‐hospital mortality rate of 16% compared with 3% mortality in patients with known diabetes and 1.7% in normoglycemic patients (P < 0.01). These data suggest that hyperglycemia due to previously unrecognized diabetes may be an independent marker of in‐hospital mortality.13
Hyperglycemia has been linked to adverse outcomes in myocardial infarction, stroke,2328 postoperative nosocomial infection risk, pneumonia, renal transplant, cancer chemotherapy, percutaneous coronary interventions, and cardiac surgery.2938 These observational studies have the usual limitations inherent in their design. Demonstrating a strong association of hyperglycemia with adverse outcomes is not a guarantee that the hyperglycemia is the cause for the poor outcome, as hyperglycemia can reflect a patient under more stress who is at a higher risk for adverse outcome. By the same token, the strong association of hyperglycemia with the risk of poor outcomes seen in these studies does not guarantee that euglycemia would mitigate this risk.
Nonetheless, there are several factors that make the body of evidence for glycemic control more compelling. First, the association has a rational physiologic basis as described above. Second, the associations are consistent across a variety of patient populations and disease entities, and demonstrate a dose‐response relationship. Third, in studies that control for comorbidities and severity of illness, hyperglycemia persists as an independent risk factor for adverse outcomes, whether the patient has a preexisting diagnosis of diabetes or not. Last, non‐RCT interventional studies and RCTs largely reinforce these studies.
The Portland Diabetic Project has reported prospective, nonrandomized data over 17 years on the use of an IV insulin therapy protocol in cardiac surgery patients.38 This program has implemented stepped lowering of target BG, with the most recent data report implementing a goal BG <150 mg/dL.35 The current protocol uses a BG target of 70110 mg/dL, but results have not yet been published.39 Mortality and deep sternal wound infection rates for patients with diabetes who remain on the IV insulin protocol for 3 days have been lowered to levels equivalent to those for nondiabetic patients. This group has also reported reductions in length of stay and cost‐effectiveness of targeted glycemic control in the cardiac surgery population.35 Their data have to a large extent driven a nationwide movement to implement targeted BG control in cardiac surgery patients.
Another large ICU study (mixed medical‐surgical, n = 800 patients) also supports a benefit through targeted BG control (130.7 versus 152.3 mg/dL, P < 0.001) when compared with historical controls. This study demonstrated reduction in in‐hospital mortality (relative risk reduction 29.3%, P = 0.002), duration of ICU stay (10.8%, P = 0.04), acute renal failure (75%, P = 0.03), and blood transfusions (18.7%, P = 0.002),40 representing a similar magnitude of effect as was demonstrated by the Belgian group.
Evidence: RCTs
Evidence is accumulating that demonstrates an advantage in terms of morbidity and mortality when targeted glycemic control using intravenous insulin infusion is implemented in the hospital. The most robust data have been reported from ICU and cardiac surgery settings. The largest randomized, controlled study to date enrolled 1548 patients in a surgical ICU in Leuven, Belgium who were randomized to either intensive (IT) or conventional (CT) insulin therapy. Mean glucose attained was 103 19 and 153 33 mg/dL in each arm, respectively. The intensive insulin group demonstrated a reduction in both ICU (4.6% versus 8.0%) and in‐hospital mortality (7.2% versus 10.9%), as well as bloodstream infections, acute renal failure, transfusions, and polyneuropathy, the latter being reflected by duration of mechanical ventilation (P < 0.01 for all). Although a similar study in an MICU did not achieve statistical significance in the overall intention‐to‐treat analysis, it did demonstrate reductions in mortality (from 52.5% to 43.0%) in patients with at least 3 days of ICU treatment. It should also be noted that in this MICU population hypoglycemia rates were higher and level of glycemic control attained not as rigorous as in the same group's SICU cohort, factors which may have had an impact on observed outcomes. A meta‐analysis of these two Leuven, Belgium, studies demonstrated a reduction in mortality (23.6% versus 20.4%, absolute risk reduction [ARR] 3.2%, P = 0.004)) in all patients treated with IIT, with a larger reduction in mortality (37.9% versus 30.1%, ARR 7.8%, P = 0.002) observed in patients with at least 3 days of IIT, as well as substantial reductions in morbidity.9, 10, 41, 42
Several other studies must be mentioned in this context. A small (n = 61), randomized study in another SICU did not show a mortality benefit, perhaps because the number of subjects was not adequate to reach statistical significance, but did result in a significant reduction in nosocomial infections in patients receiving IIT (BG = 125 versus 179 mg/dL, P < 0.001).43 Two international multicenter studies recently stopped enrollment due to excess rates of hypoglycemia. The Volume Substitution and Insulin Therapy in Severe Sepsis (VISEP) study, in a mixed medical and surgical sepsis population, showed no significant reduction in mortality in the intensively‐treated group. Serious adverse events were reported according to standard definitions. Enrollment was stopped before the full number of subjects had been randomized. Among the 537 evaluable cases, hypoglycemia (BG < 40 mg/dL) was reported as 17.0% in the IT group and 4.1% (P < 0.001) in the control group,44 and the rate of serious adverse events was higher in the IT group (10.9% versus 5.2%, P = 0.01). It is notable that the rate of hypoglycemia was comparable to the 18.7% rate seen in the IT group in the Leuven, Belgium, medical ICU study.9 The Glucontrol study enrolled 855 medical and surgical ICU patients and was similarly terminated because of hypoglycemia (BG < 40 mg/dL) at a rate of 8.6% compared to 2.4% in the control group (P < 0.001). Insulin infusion protocols and outcome data have not yet been published.42, 45
These studies with very high hypoglycemia rates each used an algorithm based on the Leuven, Belgium, protocol. The rates of severe hypoglycemia are 34 that reported by a variety of others achieving similar or identical glycemic targets. Hypoglycemia should not be construed as a reason to not use a standardized insulin infusion protocol. In comparing protocols that have been published, it is apparent that rates of hypoglycemia differ substantially and that performance results of some algorithms are not necessarily replicable across sites.46 Dose‐defining designs can be substantively more sophisticated than those used in the trials mentioned, in some cases incorporating principles of control engineering. The variability of hypoglycemia rates under differing insulin infusion protocols is a compelling reason to devote institutional effort to monitoring the efficacy and safety of the infusion protocols that are used.
High‐level evidence from randomized, controlled trials demonstrating outcomes benefit through targeted BG control outside the ICU is lacking at this point in time, but it must be noted that feasibility is suggested by a recent randomized control trial (RABBIT2) that demonstrated the superiority of basal bolus insulin regimens to sliding scale insulin in securing glycemic control, without any increase in hypoglycemia.47
Summing Up the Evidence
It is clear that hyperglycemia is associated with negative clinical outcomes throughout the hospital, and level A evidence is available to support tight glucose control in the SICU setting. However, in view of the imperfect and incomplete nature of the evidence, controversy persists around how stringent glycemic targets should be in the ICU, on whether glycemic targets should differ between SICU and MICU patients, and especially what the targets should be in the non‐ICU setting. There should be hesitancy to extrapolate glycemic targets to be applied beyond the populations that have been studied with RCTs or to assume benefit for medical conditions that have not been examined for the impact of interventions to control hyperglycemia. Institutions might justifiably choose more liberal targets than those promoted in national recommendations/guidelines2, 4850 until safe attainment of more moderate goals is demonstrated. However, even critics agree that uncontrolled hyperglycemia exceeding 180200 mg/dL in any acute care setting is undesirable. Moreover, strong observational data showing the hazards of hyperglycemia in noncritical care units (even after adjustment for severity of illness) combined with the high rate of adverse drug events associated with insulin use, argue strongly for a standardized approach to treating diabetes and hyperglycemia in the hospital. Even though no RCTs exist demonstrating outcomes benefits of achieving glycemic target on wards, the alternatives to control of hyperglycemia using scheduled insulin therapy are unacceptable. Oral agent therapy is potentially dangerous and within the necessary timeframe is likely to be ineffective; sliding scale management is inferior to basal‐bolus insulin therapy, as shown inan RCT,47 and is unsafe; and on the wards improved glycemic control can be achieved simultaneously with a reduction in hypoglycemia.51
INPATIENT GLYCEMIC CONTROL IS INCREASINGLY INCORPORATED INTO PUBLIC REPORTING, GUIDELINES, REGULATORY AGENCY, AND NATIONAL QUALITY INITIATIVE PRIORITIES
National quality initiatives, public reporting, pay‐for‐performance, and guideline‐based care continue to play an increasingly important role in the U.S. healthcare system. Over the years these initiatives have focused on various disease states (venous thromboembolism, congestive heart failure, community‐acquired pneumonia, etc.) in an attempt to standardize care and improve patient safety and quality. Inpatient hyperglycemic control is also increasingly being incorporated into public reporting, regulatory compliance, and national quality initiatives.
Professional organizations such as the ADA2 and AACE50 have published guidelines supporting improved glycemic control, the safe use of insulin, and other measures to improve care for hyperglycemic inpatients. The AACE has a Web site dedicated to hospital hyperglycemia.52 The Society of Hospital Medicine48 has created a resource room on its Web site and a workbook for improvement49 on optimizing the care of inpatients with hyperglycemia and diabetes. The guidelines and Web sites help raise awareness and educate physicians and healthcare workers in inpatient glucose management. The American Heart Association has incorporated specific recommendation regarding inpatient diabetic management in its Get With the Guidelines.53
The Joint Commission54 has developed an advanced disease‐specific certification on inpatient diabetes. Disease management programs are important components of complex healthcare systems that serve to coordinate chronic care, promote early detection and prevention, and reduce overall healthcare costs. Certification is increasingly important to providers, payers, and healthcare institutions because it demonstrates a commitment to quality and patient safety. The Joint Commission disease‐specific care certification is a patient‐centered model focusing on the delivery of clinical care and relationship between the practitioner and the patient. The evaluation and resulting certification by the Joint Commission is based on 3 core components: (1) an assessment of compliance with consensus‐based national standards; (2) the effective use of established clinical practice guidelines to manage and optimize care; and (3) an organized approach to performance measurement and improved activities.55 For inpatient diabetes, the Joint Commission program has 7 major elements following the ADA recommendations, including general recommendations regarding diabetic documentation, BG targets, preventing hypoglycemia, diabetes care providers, diabetes self‐management education, medical nutrition therapy, and BG monitoring.54 This mirrors the Call to Action Consensus Conference essential elements for successful glycemic control programs.1
Other organizations such as the Surgical Care Improvement Partnership (SCIP) and National Surgical Quality Improvement Program (NSQIP) have included perioperative glycemic control measures, as it impacts surgical wound infections. The University HealthSystem Consortium (UHC) has benchmarking data and endorses perioperative glycemic control measures, whereas the Institute for Healthcare Improvement (IHI) has focused on safe use of insulin practices in its 5 Million Lives campaign.
HOSPITALIZATION IS A MOMENT OF OPPORTUNITY TO ASSESS AND INTERVENE
The benefits of outpatient glycemic control and quality preventive care are well established, and the reduction of adverse consequences of uncontrolled diabetes are a high priority in ambulatory medicine.5658 Hospitalization provides an opportunity to identify previously undiagnosed diabetes or prediabetes and, for patients with known diabetes, to assess and impact upon the long term course of diabetes.
As a first step, unless a recent hemoglobin A1C (HbA1c) is known, among hospitalized hyperglycemic patients an HbA1C should be obtained upon admission. Greci et al.59 showed that an HbA1c level >6.0% was 100% specific (14/14) and 57% sensitive (12/21) for the diagnosis of diabetes. Among patients having known diabetes, an HbA1C elevation on admission may justify intensification of preadmission management at the time of discharge. If discharge and postdischarge adjustments of preadmission regimens are planned in response to admission A1C elevations, then the modified long‐term treatment strategy can improve the A1C in the ambulatory setting.60 Moreover, the event of hospitalization is the ideal teachable moment for patients and their caregivers to improve self‐care activities. Yet floor nurses may be overwhelmed by the tasks of patient education. For ideal patient education, both a nutritionist and a diabetes nurse educator are needed to assess compliance with medication, diet, and other aspects of care.6163 There also is need for outpatient follow‐up education. Finally, at the time of discharge, there is a duty and an opportunity for the diabetes provider to communicate with outpatient care providers about the patient's regimen and glycemic control, and also, based on information gathered during the admission, to convey any evidence that might support the need for a change of long‐term strategy.64 Unfortunately, the opportunity that hospitalization presents to assess, educate, and intervene frequently is underused.1, 8, 51, 65
LARGE GAPS EXIST BETWEEN CURRENT AND OPTIMAL CARE
Despite the evidence that inpatient glycemic control is important for patient outcomes, and despite guidelines recommending tighter inpatient glycemic control, clinical practice has been slow to change. In many institutions, inpatient glycemic management has not improved over the past decade, and large gaps remain between current practice and optimal practice.
Studies of individual institutions provide several insights into gaps in care. For example, Schnipper et al.66 examined practices on the general medicine service of an academic medical center in Boston in 2004. Among 107 prospectively identified patients with a known diagnosis of diabetes or at least 1 glucose reading >200 mg/dL (excluding patients with diabetic ketoacidosis, hyperglycemic hyperosmolar state, or pregnancy), they found scheduled long‐acting insulin prescribed in 43% of patients, scheduled short‐acting/rapid‐acting insulin in only 4% of patients, and 80 of 89 patients (90%) on the same sliding scale insulin regimen despite widely varying insulin requirements. Thirty‐one percent of glucose readings were >180 mg/dL compared with 1.2% of readings <60 mg/dL (but 11% of patients had at least 1 episode of hypoglycemia). Of the 75 patients with at least 1 episode of hyperglycemia or hypoglycemia, only 35% had any change to their insulin regimen during the first 5 days of the hospitalization.
Other studies have confirmed this concept of clinical inertia (ie, recognition of the problem but failure to act).67 A study by Cook et al.68 of all hospitalized non‐ICU patients with diabetes or hyperglycemia and length of stay of 3 days between 2001 and 2004 showed that 20% of patients had persistent hyperglycemia during the hospitalization (defined as a mean glucose >200 mg/dL). Forty‐six percent of patients whose average glucose was in the top tertile did not have their insulin regimen intensified to a combination of short‐acting/rapid‐acting and long‐acting insulin, and 35% of these patients either had no change in their total daily insulin dose or actually had a decrease in their dose when comparing the last 24 hours with the first 24 hours of hospitalization, a concept they term negative therapeutic momentum.
Perhaps the most well‐balanced view of the current state of medical practice comes from the UHC benchmarking project.69 UHC is an alliance of 90 academic health centers. For the diabetes project, each institution reviewed the records of 50 randomly selected patients over 18 years of age with at least a 72‐hour length of stay, 1 of 7 prespecified Diagnosis Related Group (DRG) codes, and at least 2 consecutive glucose readings >180 mg/dL or the receipt of insulin any time during the hospitalization. Patients with a history of pancreatic transplant, pregnant at the time of admission, receiving hospice or comfort care, or receiving insulin for a reason other than glucose management were excluded. The study showed widespread gaps in processes and outcomes (Table 1). Moreover, performance varied widely across hospitals. For example, the morning glucose in the ICU on the second measurement day was 110 mg/dL in 18% of patients for the median‐performing hospital, with a range of 0% to 67% across all 37 measured hospitals. In the non‐ICU setting on the second measurement day, 26% of patients had all BG measurements = 180 mg/dL in the median‐performing hospital, with a range of 7% to 48%. Of note, hypoglycemia was relatively uncommon: in the median hospital, 2.4% of patient‐days had 1 or more BG readings <50 mg/dL (range: 0%8.6%). Finally, in the median‐performing hospital, effective insulin therapy (defined as short‐acting/rapid‐acting and long‐acting subcutaneous insulin, continuous insulin infusion, or subcutaneous insulin pump therapy) was prescribed in 45% of patients, with a range of 12% to 77% across measured hospitals.
Key Performance Measure | Results for Median‐Performing Hospital (%) |
---|---|
| |
Documentation of diabetes | 100 |
Hob A1c assessment within 30 days | 36.1 |
Glucose measurement within 8 hours of admission | 78.6 |
Glucose monitoring 4 times a day | 85.4 |
Median glucose reading > 200 mg/dL | 10.3 |
Effective insulin therapy* | 44.7 |
ICU day 2 morning glucose 110 mg/dL | 17.7 |
Non‐ICU day 2 all glucose readings 180 mg/dL | 26.3 |
Patient‐days with at least 1 glucose reading < 50 mg/dL | 2.4 |
FREQUENT PROBLEMS WITH COMMUNICATION AND COORDINATION
Those who work closely with frontline practitioners striving to improve inpatient glycemic management have noticed other deficiencies in care.1, 70 These include: a lack of coordination between feeding, BG measurement, and insulin administration, leading to mistimed and incorrectly dosed insulin; frequent use of sliding‐scale only regimens despite evidence that they are useless at best and harmful at worst;6, 47, 60, 71 discharge summaries that often do not mention follow‐up plans for hyperglycemic management; incomplete patient educational programs; breakdowns in care at transition points; nursing and medical staffs that are unevenly educated about the proper use of insulin; and patients who are often angry or confused about their diabetes care in the hospital. Collectively, these gaps in care serve as prime targets for any glycemic control program.
HYPOGLYCEMIA IS A PROMINENT INPATIENT SAFETY CONCERN
Hypoglycemia is common in the inpatient setting and is a legitimate safety concern. In a recently reported series of 2174 hospitalized patients receiving antihyperglycemic agents, it was found that 9.5% of patients experienced a total 484 hypoglycemic episodes (defined as 60 mg/dL).72 Hypoglycemia often occurred in the setting of insulin therapy and frequently resulted from a failure to recognize trends in BG readings or other clues that a patient was at risk for developing hypoglycemia.73 A common thread is the risk created by interruption of carbohydrate intake, noted by Fischer et al.73 and once again in the recent ICU study by Vriesendorp et al.74 Sources of error include: lack of coordination between feeding and medication administration, leading to mistiming of insulin action; lack of sufficient frequency in BG monitoring; lack of clarity or uniformity in the writing of orders; failure to recognize changes in insulin requirements due to advanced age, renal failure, liver disease, or change in clinical status; steroid use with subsequent tapering or interruption; changes in feeding; failure to reconcile medications; inappropriate use of oral antihyperglycemic agents, and communication or handoff failures.
It has been difficult to sort out whether hypoglycemia is a marker of severity of illness or whether it is an independent factor leading to poor outcomes. Observational studies lend credibility to the concept that patients having congestive heart failure or myocardial infarction may be at risk for excessive mortality if their average BG resides in the low end of the normal range.7578 Sympathetic activation occurs as the threshold for hypoglycemia is approached, such as occurs at BG = 70 or 72 mg/dL.79 Patients living with BG levels observed to be in the low end of the normal range might experience more severe but unobserved and undocumented episodes of neuroglycopenia. Arrhythmia and fatality have been directly attributed to strict glycemic control.80, 81 We are confronted with the need to interpret well conducted observational studies, evaluating subgroups at risk, and using multivariate analysis to assess the impact of hypoglycemia upon outcomes.82 In such studies, we will need to examine high‐risk subgroups, including cardiac patients, in particular, for the possibility that there is a J‐shaped curve for mortality as a function of average BG.
Unfortunately, clinical inertia exists in response to hypoglycemia just as it does with hyperglycemia. One recent study examined 52 patients who received intravenous 50% dextrose solution for an episode of hypoglycemia.83 Changes to insulin regimens were subsequently made in only 21 patients (40%), and diabetes specialists agreed with the changes for 11 of these patients. The other 31 patients (60%) received no changes in treatment, and diabetes specialists agreed with that decision for only 10 of these patients.
Although some increase in hypoglycemia might be expected with initiation of tight glycemic control efforts, the solution is not to undertreat hyperglycemia. Hyperglycemia creates an unsafe setting for the treatment of illness and disease. Sliding‐scaleonly regimens are ineffective in securing glycemic control and can result in increases in hypoglycemia as well as hyperglycemic excursions.6, 66 Inappropriate withholding of insulin doses can lead to severe glycemic excursions and even iatrogenic diabetic ketoacidosis (DKA). Systems approaches to avoid the errors outlined above can minimize or even reverse the increased risk of hypoglycemia expected with tighter glycemic targets.51
A SYSTEMS APPROACH IS NEEDED FOR THESE MULTIPLE COMPLEX PROBLEMS
Care is of the hyperglycemic inpatient is inherently complex. Previously established treatments are often inappropriate under conditions of altered insulin resistance, changing patterns of nutrition and carbohydrate exposure, comorbidities, concomitant medications, and rapidly changing medical and surgical status. Patients frequently undergo changes in the route and amount of nutritional exposure, including discrete meals, continuous intravenous dextrose, nil per orem (nothing by mouth status; NPO) status, grazing on nutritional supplements or liquid diets with or without meals, bolus enteral feedings, overnight enteral feedings with daytime grazing, total parenteral nutrition, continuous peritoneal dialysis, and overnight cycling of peritoneal dialysis. Relying on individual expertise and vigilance to negotiate this complex terrain without safeguards, protocols, standardization of orders, and other systems change is impractical and unwise.
Transitions across care providers and locations lead to multiple opportunities for breakdown in the quality, consistency, and safety of care.64, 65 At the time of ward transfer or change of patient status, previous medication and monitoring orders sometimes are purged. At the time of discharge, there may be risk of continuation of anti‐hyperglycemic therapy, initiated to cover medical stress, in doses that will subsequently be unsafe.
In the face of this complexity, educational programs alone will not suffice to improve care. Institutional commitment and systems changes are essential.
MARKED IMPROVEMENT IS POSSIBLE AND TOOLS EXIST: A ROADMAP IS IN PLACE
Fortunately, a roadmap is in place to help us achieve better glycemic control, improve insulin management, and address the long list of current deficiencies in care. This is imperative to develop consistent processes in order to achieve maximum patient quality outcomes that effective glycemic management offers. This roadmap entails 4 components: (1) national awareness, (2) national guidelines, (3) consensus statements, and (4) effective tools. As mentioned above, the first two components of this roadmap are now in place.
As these national guidelines become more widely accepted, the next step will be the incorporation of this into programs like Pay‐for Performance and the Physician Quality Reporting Initiative (PQRI), which will impact reimbursement to both hospitals and providers.
Regarding the third component, a recent multidisciplinary consensus conference1 outlined the essential elements needed for successful implementation of an inpatient glycemic control program which include:
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An appropriate level of administrative support.
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Formation of a multidisciplinary steering committee to drive the development of initiatives and empowered to enact change.
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Assessment of current processes, quality of care, and barriers to practice change.
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Development and implementation of interventions including standardized order sets, protocols, policies and algorithms with associated educational programs.
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Metrics for evaluation of glycemic control, hypoglycemia, insulin use patterns, and other aspects of care.
Finally, extensive resources and effective tools are now available to help institutions achieve better inpatient glucose control. The Society of Hospital Medicine (SHM), in conjunction with the ADA, AACE, the American College of Physicians (ACP), the Case Management Society of America (CMSA), the American Society of Consultant Pharmacists, nursing, and diabetic educators have all partnered to produce a comprehensive guide to effective implementation of glycemic control and preventing hypoglycemia.49 This comprehensive workbook is a proven performance improvement framework and is available on the SHM Web site.48 Details and examples of all essential elements are covered in this workbook along with opportunities for marked improvement bolstered by integration of high reliability design features and attention to effective implementation techniques. The remainder of this supplement crystallizes a substantial portion of this material. The AACE has also recently offered a valuable web‐based resource to encourage institutional glycemic control efforts.49
GLYCEMIC CONTROL INITIATIVES CAN BE COST‐EFFECTIVE
Achieving optimal glycemic control safely requires monitoring, education, and other measures, which can be expensive, labor intensive, and require coordination of the services of many hospital divisions. This incremental expense has been shown to be cost‐effective in a variety of settings.1, 84, 85 The costs of glycemic control initiatives have demonstrated a good return on investment via:
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Improved LOS, readmission rates, morbidity, and mortality.
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Improved documentation of patient acuity and related payment for acuity.
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Income generated via incremental physician and allied health professional billing.
CONCLUSION AND SUMMARY
Evidence exists that appropriate management of hyperglycemia improves outcomes, whereas the current state of affairs is that most medical centers currently manage this suboptimally. This is concerning given the magnitude of diabetes and hyperglycemia in our inpatient setting in the United States. To bring awareness to this issue, multiple initiatives (guidelines, certification programs, workbooks, etc.) are available by various organizations including the ADA, AACE, SCIP, NSQIP, IHI, UHC, the Joint Commission, and SHM. However, this is not enough. Change occurs at the local level, and institutional prioritization and support is needed to empower a multidisciplinary steering committee, with appropriate administrative support, to standardize and improve systems in the face of substantial cultural issues and complex barriers. Improved data collection and reporting, incremental monitoring, creation of metrics, and improved documentation are an absolutely necessary necessity to achieve breakthrough levels of improvement.
Now the time is right to make an assertive effort to improve inpatient glycemic control and related issues, and push for appropriate support at your institution to help achieve this in the interest of patient safety and optimal outcomes.
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- Prevalence of diabetes and impaired fasting glucose in adults in the U.S. population: National Health And Nutrition Examination Survey 1999–2002.Diabetes Care.2006;29:1263–1268. , , , et al.
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- Glucose metabolism in patients with acute myocardial infarction and no previous diagnosis of diabetes mellitus: a prospective study.Lancet.2002;359:2140–2144. , , , et al.
- Mechanism by which hyperglycemia plays a role in the setting of acute cardiovascular illness.Rev Cardiovasc Med.2006;7(Suppl 2):S35–S43. .
- Stress hyperglycaemia is an independent predictor of left ventricular remodelling after first anterior myocardial infarction in non‐diabetic patients.Eur Heart J.2007;28:546–552. , , , , , , et al.
- Implications and treatment of acute hyperglycemia in the setting of acute myocardial infarction.Circulation.2007;115:e436–e439. , .
- Insulin infusion in acute illness.J Clin Invest.2005;115:2069–2072. , , , , .
- Intensive insulin therapy exerts antiinflammatory effects in critically ill patients and counteracts the adverse effect of low mannose‐gind lectin levels.J Clin Endocrinol Metab.2003;88:1082–1088. , , , , .
- Protection of hepatocyte mitochondrial ultrastructure and function by strict blood glucose control with insulin in critically ill patients.Lancet.2005;365:53–59. , , , , , .
- Intensive insulin therapy protects the endothelium of critically ill patients.J Clin Invest.2005;115:2277–2286. , , , et al.
- The association between hyperglycaemia on admission and 180‐day mortality in acute myocardial infarction patients with and without diabetes.Diabet Med.2005;22:1321–1325. , , , .
- Admission glucose and mortality in elderly patients hospitalized with acute myocardial infarction: implications for patients with and without recognized diabetes.Circulation.2005;111:3078–3086. , , , et al.
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- Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773–778. , , , .
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- Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:2426–2432. , , , , .
- Perioperative glycemic control and the risk of infectious complications in a cohort of adults with diabetes.Diabetes Care.1999;22:1408–1414. , , , .
- Early postoperative glucose control predicts nosocomial infection rate in diabetic patients.JPEN J Parenter Enteral Nutr.1998;22:77–81. , , , et al.
- The relation between hyperglycemia and outcomes in 2,471 patients admitted to the hospital with community‐acquired pneumonia.Diabetes Care.2005;28:810–815. , , , , , .
- Early peri‐operative glycaemic control and allograft rejection in patients with diabetes mellitus: a pilot study.Transplantation.2001;72:1321–1324. , , , , .
- Relation between the duration of remission and hyperglycemia during induction chemotherapy for acute lymphocytic leukemia with a hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone/methotrexate‐cytarabine regimen.Cancer.2004;100:1179–1185. , , , et al.
- Effect of fasting glucose levels on mortality rate in patients with and without diabetes mellitus and coronary artery disease undergoing percutaneous coronary intervention.Am Heart J.2003;146:351–358. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland diabetic project.Endocr Pract.2004;10(Suppl 2):21–33. , , .
- Intraoperative hyperglycemia and perioperative outcomes in cardiac surgery patients.Mayo Clin Proc.2005;80:862–866. , , , et al.
- The association of diabetes and glucose control with surgical‐site infections among cardiothoracic surgery patients.Infect Control Hosp Epidemiol.2001;22:607–612. , , , , .
- Glucose control lowers the risk of wound infection in diabetics after open heart operations.Ann Thorac Surg.1997;63:356–361. , , .
- The Portland Protocol. Available at: http://www.providence.org/oregon/grograms_and_services/heart/portlandprotocol/. Accessed September2007.
- Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:992–1000. .
- Intensive insulin therapy in mixed medical/surgical intensive care units: benefit versus harm.Diabetes.2006;55:3151–3159. , , , et al.
- Tight blood glucose control with insulin in the ICU: facts and controversies.Chest.2007;132:268–278. , , .
- Reduction of nosocomial infections in the surgical intensive‐care unit by strict glycemic control.Endocr Pract.2004;10(Suppl 2):46–52. , .
- Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358:125–139. , , , , , , et al.
- Current controversies around tight glucose control in critically ill patients.Curr Opin Clin Nutr Metab Care.2007;10:206–209. , .
- Designing and implementing insulin infusion protocols and order sets.J Hosp Med.2008;3(5):S42–S54. , , , .
- Randomized study of basal‐bolus insulin therapy in the inpatient management of patients with type 2 diabetes (RABBIT 2 trial).Diabetes Care.2007;30:2181–2186. , , , , , , et al.
- Society of Hospital Medicine. Glycemic control resource room. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/GlycemicControl.cfm. Accessed November2007.
- Society of Hospital Medicine. Workbook for improvement: improving glycemic control, preventing hypoglycemia, and optimizing care of the inpatient with hyperglycemia and diabetes. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/pdf/GC_Workbook.pdf. Accessed November2007.
- American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10:77–82. , , , et al.
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm.J Hosp Med.2008. In press. , , , , .
- American Association of Clinical Endocrinologists Inpatient Glycemic Control Resource Center.2007. Available at: http://resources.aace.com/index.asp. Accessed December 2007.
- American Heart Association. Get With the Guidelines. Available at: http://www.americanheart.org/getwiththeguidelines. Accessed November2007.
- Joint Commission. Disease Specific‐Care Certification. Available at:http://www.jointcommission.org/CertificationPrograms. Accessed November2007.
- The Joint Commission Disease‐Specific Certification Program. Range JE. Oncology issues. July/August2007:40–41.
- Anonymous.The Diabetes Control and Complications Trial Research Group (DCCT). The effect of intensive treatment of diabetes on the development and progression of long‐term complications in insulin‐dependent diabetes mellitus.N Engl J Med.1993;329:977–986.
- Intensive blood‐glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type, 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.Lancet.1998;352:837–853.
- Intensified multifactorial intervention in patients with type 2 diabetes mellitus and microalbuminuria: the Steno type 2 randomised study.Lancet.1999;353:617–622. , , , .
- Utility of HbA1c levels for diabetes case finding in hospitalized patients with hyperglycemia.Diabetes Care.2003;26:1064–1068. , , , et al.
- Eliminating inpatient sliding‐scale insulin: a reeducation project with medical house staff.Diabetes Care.2005;28:1008–1011. , , , .
- Advanced carbohydrate counting. In:Practical Carbohydrate Counting: A How‐to‐Teach Guide for Health Professionals.Alexandria, VA:American Diabetes Association;2001:26–28. , .
- The evidence for the effectiveness of medical nutrition therapy in diabetes management.Diabetes Care.2002;25:608–613. , , , , .
- Inpatient management of diabetes and hyperglycemia: implications for nutrition practice and the food and nutrition professional.J Am Diet Assoc.2007;107:105–111. , , , et al.
- The transition from insulin infusions to long‐term diabetes therapy: the argument for insulin analogs.Semin Thorac Cardiovasc Surg.2006;18:366–378. .
- Transitions paper.J Hosp Med.2008. .
- Inpatient management of diabetes and hyperglycemia among general medicine patients at a large teaching hospital.J Hosp Med.2006;1:145–150. , , , , .
- Clinical inertia.Ann Intern Med.2001;135:825–834. , , , et al.
- Diabetes care in hospitalized noncritically ill patients: more evidence for clinical inertia and negative therapeutic momentum.J Hosp Med.2007;2:203–211. , , , et al.
- University HealthSystem Consortium.Glycemic control 2005 findings and conclusions. Presented at: Glycemic Control 2005 Knowledge Transfer Meeting; 2005 August 19,2005; Chicago, IL.
- Glycemic chaos (not glycemic control) still the rule for inpatient care: how do we stop the insanity?J Hosp Med.2006;1:141–144. , .
- Management of diabetes mellitus in hospitalized patients: efficiency and effectiveness of sliding‐scale insulin therapy.Pharmacotherapy.2006;26:1421–1432. , , , , .
- Hypoglycemia in hospitalized patients treated with antihyperglycemic agents.J Hosp Med.2007;2:234–240. , , , , , .
- Hypoglycemia in hospitalized patients.N Engl J Med.1986;315:1245–1250. , , .
- Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96–101. , , , et al.
- Association between hyper‐ and hypoglycaemia and 2 year all‐cause mortality risk in diabetic patients with acute coronary events.Eur Heart J.2005;26:1255–1261. , , , .
- U‐shaped relationship of blood glucose with adverse outcomes among patients with ST‐segment elevation myocardial infarction.J Am Coll Cardiol.2005;46:178–180. , , , et al.
- An unexpected inverse relationship between HbA1c levels and mortality in patients with diabetes and advanced systolic heart failure.Am Heart J.2006;151:91. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Hypoglycemia in diabetes.Diabetes Care.2003;26:1902–1912. , , .
- Hypoglycemia and cardiac arrest in a critically ill patient on strict glycemic control.Anesth Analg.2006;102:549–551. , , .
- Tight glycemic control in critically injured trauma patients.Ann Surg.2007;246:605–610; discussion 10–12. , , , , , .
- Severe hypoglycemia in critically ill patients: risk factors and outcomes.Crit Care Med.2007;35:2262–2267. , .
- Provider response to insulin‐induced hypoglycemia in hospitalized patients.J Hosp Med.2007;2:258–260. , , , .
- Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(Suppl 3):43–48. , .
- Impact of endocrine and diabetes team consultation on hospital length of stay for patients with diabetes.Am J Med.1995;99:22–28. , , , .
Medical centers are faced with multiple competing priorities when deciding how to focus their improvement efforts and meet the ever expanding menu of publicly reported and regulatory issues. In this article we expand on the rationale for supporting inpatient glycemic control programs as a priority that should be moved near the top of the list. We review the evidence for establishing glycemic range targets, and also review the limitations of this evidence, acknowledging, as does the American Diabetes Association (ADA), that in both the critical care and non‐critical care venue, glycemic goals must take into account the individual patient's situation as well as hospital system support for achieving these goals.1, 2 We emphasize that inpatient glycemic control programs are needed to address a wide variety of quality and safety issues surrounding the care of the inpatient with diabetes and hyperglycemia, and we wish to elevate the dialogue beyond arguments surrounding adoption of one glycemic target versus another. The Society of Hospital Medicine Glycemic Control Task Force members are not in unanimous agreement with the American Association of Clinical Endocrinologists (AACE)/ADA inpatient glycemic targets. However, we do agree on several other important points, which we will expand on in this article:
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Uncontrolled hyperglycemia and iatrogenic hypoglycemia are common and potentially dangerous situations that are largely preventable with safe and proven methods.
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The current state of care for our inpatients with hyperglycemia is unacceptably poor on a broad scale, with substandard education, communication, coordination, and treatment issues.
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Concerted efforts with changes in the design of the process of care are needed to improve this state of affairs.
DIABETES AND HYPERGLYCEMIA ARE VERY COMMON INPATIENT CONDITIONS
Diabetes mellitus (DM) has reached epidemic proportions in the United States. A reported 9.3% of adults over 20 years of age have diabetes, representing over 20 million persons. Despite increasing awareness, diabetes remains undiagnosed in approximately 30% of these persons.3 Concurrent with the increasing prevalence of diabetes in the U.S. population from 1980 through 2003, the number of hospital discharges with diabetes as any listed diagnosis more than doubled, going from 2.2 to 5.1 million discharges.4 Hospital care for patients with diabetes and hyperglycemia poses a significant health economic burden in the United States, representing over 40 billion dollars in annual direct medical expenditures.5
Hyperglycemia in the hospital may be due to known diabetes, to previously unrecognized diabetes, to prediabetes, and/or to the stress of surgery or illness. Deterioration in glycemic control in the hospital setting is most commonly associated with one or more factors, including stress‐induced release of insulin counterregulatory hormones (catecholamines, cortisol, glucagon, and growth hormone), exogenous administration of high dose glucocorticoids, and suboptimal glycemic management strategies.68 In a Belgian medical intensive care unit (MICU) randomized controlled trial (RCT) of strict versus conventional glycemic control, mean blood glucose (BG) on admission to the unit in the intention to treat group was 162 70 mg/dL (n = 1200),9 and in this group's RCT of 1548 surgical intensive care unit (SICU) patients, BG > 110 mg/dL was observed in over 70% of subjects.10 Mean BG of >145 mg/dL has been reported in 39%11 and BG >200 mg/dL in anywhere from 11% to 31% of intensive care unit (ICU) patients.10, 12 For general medicine and surgery, 1 study of 2030 patients admitted to a teaching hospital revealed that 26% of admissions had a known history of DM and 12% had new hyperglycemia, as evidenced by an admission or in‐hospital fasting BG of 126 mg/dL or more or a random BG of 200 mg/dL or more on 2 or more determinations.13 National and regional estimates on hospital use maintained by the Agency for Healthcare Research and Quality include data concerning diabetes diagnoses alone, without hyperglycemia, and may be displayed by querying its Web site.14 In cardiovascular populations almost 70% of patients having a first myocardial infarction have been reported to have either known DM, previously unrecognized diabetes, or impaired glucose tolerance.15
THE EVIDENCE SUPPORTS INPATIENT GLYCEMIC CONTROL
Evidence: Physiology
The pathophysiologic mechanisms through which hyperglycemia is linked to suboptimal outcomes in the hospital are complex and multifactorial. Although it is beyond the scope of this article to discuss these mechanisms in detail, research has broadly focused in the following areas: (1) immune system dysfunction, associated with a proinflammatory state and impaired white blood cell function; (2) metabolic derangements leading to oxidative stress, release of free fatty acids, reduction in endogenous insulin secretion, and fluid and electrolyte imbalance; and (3) a wide variety of vascular system responses (eg, endothelial dysfunction with impairment of tissue perfusion, a prothrombotic state, increased platelet aggregation, and left ventricular dysfunction).8, 1618
Conversely administration of insulin suppresses or reverses many of these abnormalities including generation of reactive oxygen species (ROS) and activation of inflammatory mechanisms,19 and leads to a fall in C‐reactive protein, which accompanied the clinical benefit of intensive insulin therapy (IIT) in the Leuven, Belgium, ICU population,20 and prevents mitochondrial abnormalities in hepatocytes.21 In the same surgical ICU cohort, Langouche et al.22 report suppression of intracellular adhesion molecule‐1 (ICAM‐1) and E‐selectin, markers of inflammation, and reduction in plasma nitric oxide (NO) and innate nitric oxide (iNOS) expression with insulin administration in patients treated with intravenous (IV) IIT.22 These data further support the role of insulin infusion in suppressing inflammation and endothelial dysfunction. The authors suggest that maintaining normoglycemia with IIT during critical illness protects the endothelium, thereby contributing to prevention of organ failure and death.22 Based on accumulating data in the literature such as that cited above, it has been suggested that a new paradigm in which glucose and insulin are related not only through their metabolic action but also through inflammatory mechanisms offers important potential therapeutic opportunities.19
Evidence: Epidemiology/Observational Studies/Non‐RCT Interventional Studies
A strong association between hospital hyperglycemia and negative outcomes has been reported in numerous observational studies in diverse adult medical and surgical settings. In over 1800 hospital admissions, those with new hyperglycemia had an in‐hospital mortality rate of 16% compared with 3% mortality in patients with known diabetes and 1.7% in normoglycemic patients (P < 0.01). These data suggest that hyperglycemia due to previously unrecognized diabetes may be an independent marker of in‐hospital mortality.13
Hyperglycemia has been linked to adverse outcomes in myocardial infarction, stroke,2328 postoperative nosocomial infection risk, pneumonia, renal transplant, cancer chemotherapy, percutaneous coronary interventions, and cardiac surgery.2938 These observational studies have the usual limitations inherent in their design. Demonstrating a strong association of hyperglycemia with adverse outcomes is not a guarantee that the hyperglycemia is the cause for the poor outcome, as hyperglycemia can reflect a patient under more stress who is at a higher risk for adverse outcome. By the same token, the strong association of hyperglycemia with the risk of poor outcomes seen in these studies does not guarantee that euglycemia would mitigate this risk.
Nonetheless, there are several factors that make the body of evidence for glycemic control more compelling. First, the association has a rational physiologic basis as described above. Second, the associations are consistent across a variety of patient populations and disease entities, and demonstrate a dose‐response relationship. Third, in studies that control for comorbidities and severity of illness, hyperglycemia persists as an independent risk factor for adverse outcomes, whether the patient has a preexisting diagnosis of diabetes or not. Last, non‐RCT interventional studies and RCTs largely reinforce these studies.
The Portland Diabetic Project has reported prospective, nonrandomized data over 17 years on the use of an IV insulin therapy protocol in cardiac surgery patients.38 This program has implemented stepped lowering of target BG, with the most recent data report implementing a goal BG <150 mg/dL.35 The current protocol uses a BG target of 70110 mg/dL, but results have not yet been published.39 Mortality and deep sternal wound infection rates for patients with diabetes who remain on the IV insulin protocol for 3 days have been lowered to levels equivalent to those for nondiabetic patients. This group has also reported reductions in length of stay and cost‐effectiveness of targeted glycemic control in the cardiac surgery population.35 Their data have to a large extent driven a nationwide movement to implement targeted BG control in cardiac surgery patients.
Another large ICU study (mixed medical‐surgical, n = 800 patients) also supports a benefit through targeted BG control (130.7 versus 152.3 mg/dL, P < 0.001) when compared with historical controls. This study demonstrated reduction in in‐hospital mortality (relative risk reduction 29.3%, P = 0.002), duration of ICU stay (10.8%, P = 0.04), acute renal failure (75%, P = 0.03), and blood transfusions (18.7%, P = 0.002),40 representing a similar magnitude of effect as was demonstrated by the Belgian group.
Evidence: RCTs
Evidence is accumulating that demonstrates an advantage in terms of morbidity and mortality when targeted glycemic control using intravenous insulin infusion is implemented in the hospital. The most robust data have been reported from ICU and cardiac surgery settings. The largest randomized, controlled study to date enrolled 1548 patients in a surgical ICU in Leuven, Belgium who were randomized to either intensive (IT) or conventional (CT) insulin therapy. Mean glucose attained was 103 19 and 153 33 mg/dL in each arm, respectively. The intensive insulin group demonstrated a reduction in both ICU (4.6% versus 8.0%) and in‐hospital mortality (7.2% versus 10.9%), as well as bloodstream infections, acute renal failure, transfusions, and polyneuropathy, the latter being reflected by duration of mechanical ventilation (P < 0.01 for all). Although a similar study in an MICU did not achieve statistical significance in the overall intention‐to‐treat analysis, it did demonstrate reductions in mortality (from 52.5% to 43.0%) in patients with at least 3 days of ICU treatment. It should also be noted that in this MICU population hypoglycemia rates were higher and level of glycemic control attained not as rigorous as in the same group's SICU cohort, factors which may have had an impact on observed outcomes. A meta‐analysis of these two Leuven, Belgium, studies demonstrated a reduction in mortality (23.6% versus 20.4%, absolute risk reduction [ARR] 3.2%, P = 0.004)) in all patients treated with IIT, with a larger reduction in mortality (37.9% versus 30.1%, ARR 7.8%, P = 0.002) observed in patients with at least 3 days of IIT, as well as substantial reductions in morbidity.9, 10, 41, 42
Several other studies must be mentioned in this context. A small (n = 61), randomized study in another SICU did not show a mortality benefit, perhaps because the number of subjects was not adequate to reach statistical significance, but did result in a significant reduction in nosocomial infections in patients receiving IIT (BG = 125 versus 179 mg/dL, P < 0.001).43 Two international multicenter studies recently stopped enrollment due to excess rates of hypoglycemia. The Volume Substitution and Insulin Therapy in Severe Sepsis (VISEP) study, in a mixed medical and surgical sepsis population, showed no significant reduction in mortality in the intensively‐treated group. Serious adverse events were reported according to standard definitions. Enrollment was stopped before the full number of subjects had been randomized. Among the 537 evaluable cases, hypoglycemia (BG < 40 mg/dL) was reported as 17.0% in the IT group and 4.1% (P < 0.001) in the control group,44 and the rate of serious adverse events was higher in the IT group (10.9% versus 5.2%, P = 0.01). It is notable that the rate of hypoglycemia was comparable to the 18.7% rate seen in the IT group in the Leuven, Belgium, medical ICU study.9 The Glucontrol study enrolled 855 medical and surgical ICU patients and was similarly terminated because of hypoglycemia (BG < 40 mg/dL) at a rate of 8.6% compared to 2.4% in the control group (P < 0.001). Insulin infusion protocols and outcome data have not yet been published.42, 45
These studies with very high hypoglycemia rates each used an algorithm based on the Leuven, Belgium, protocol. The rates of severe hypoglycemia are 34 that reported by a variety of others achieving similar or identical glycemic targets. Hypoglycemia should not be construed as a reason to not use a standardized insulin infusion protocol. In comparing protocols that have been published, it is apparent that rates of hypoglycemia differ substantially and that performance results of some algorithms are not necessarily replicable across sites.46 Dose‐defining designs can be substantively more sophisticated than those used in the trials mentioned, in some cases incorporating principles of control engineering. The variability of hypoglycemia rates under differing insulin infusion protocols is a compelling reason to devote institutional effort to monitoring the efficacy and safety of the infusion protocols that are used.
High‐level evidence from randomized, controlled trials demonstrating outcomes benefit through targeted BG control outside the ICU is lacking at this point in time, but it must be noted that feasibility is suggested by a recent randomized control trial (RABBIT2) that demonstrated the superiority of basal bolus insulin regimens to sliding scale insulin in securing glycemic control, without any increase in hypoglycemia.47
Summing Up the Evidence
It is clear that hyperglycemia is associated with negative clinical outcomes throughout the hospital, and level A evidence is available to support tight glucose control in the SICU setting. However, in view of the imperfect and incomplete nature of the evidence, controversy persists around how stringent glycemic targets should be in the ICU, on whether glycemic targets should differ between SICU and MICU patients, and especially what the targets should be in the non‐ICU setting. There should be hesitancy to extrapolate glycemic targets to be applied beyond the populations that have been studied with RCTs or to assume benefit for medical conditions that have not been examined for the impact of interventions to control hyperglycemia. Institutions might justifiably choose more liberal targets than those promoted in national recommendations/guidelines2, 4850 until safe attainment of more moderate goals is demonstrated. However, even critics agree that uncontrolled hyperglycemia exceeding 180200 mg/dL in any acute care setting is undesirable. Moreover, strong observational data showing the hazards of hyperglycemia in noncritical care units (even after adjustment for severity of illness) combined with the high rate of adverse drug events associated with insulin use, argue strongly for a standardized approach to treating diabetes and hyperglycemia in the hospital. Even though no RCTs exist demonstrating outcomes benefits of achieving glycemic target on wards, the alternatives to control of hyperglycemia using scheduled insulin therapy are unacceptable. Oral agent therapy is potentially dangerous and within the necessary timeframe is likely to be ineffective; sliding scale management is inferior to basal‐bolus insulin therapy, as shown inan RCT,47 and is unsafe; and on the wards improved glycemic control can be achieved simultaneously with a reduction in hypoglycemia.51
INPATIENT GLYCEMIC CONTROL IS INCREASINGLY INCORPORATED INTO PUBLIC REPORTING, GUIDELINES, REGULATORY AGENCY, AND NATIONAL QUALITY INITIATIVE PRIORITIES
National quality initiatives, public reporting, pay‐for‐performance, and guideline‐based care continue to play an increasingly important role in the U.S. healthcare system. Over the years these initiatives have focused on various disease states (venous thromboembolism, congestive heart failure, community‐acquired pneumonia, etc.) in an attempt to standardize care and improve patient safety and quality. Inpatient hyperglycemic control is also increasingly being incorporated into public reporting, regulatory compliance, and national quality initiatives.
Professional organizations such as the ADA2 and AACE50 have published guidelines supporting improved glycemic control, the safe use of insulin, and other measures to improve care for hyperglycemic inpatients. The AACE has a Web site dedicated to hospital hyperglycemia.52 The Society of Hospital Medicine48 has created a resource room on its Web site and a workbook for improvement49 on optimizing the care of inpatients with hyperglycemia and diabetes. The guidelines and Web sites help raise awareness and educate physicians and healthcare workers in inpatient glucose management. The American Heart Association has incorporated specific recommendation regarding inpatient diabetic management in its Get With the Guidelines.53
The Joint Commission54 has developed an advanced disease‐specific certification on inpatient diabetes. Disease management programs are important components of complex healthcare systems that serve to coordinate chronic care, promote early detection and prevention, and reduce overall healthcare costs. Certification is increasingly important to providers, payers, and healthcare institutions because it demonstrates a commitment to quality and patient safety. The Joint Commission disease‐specific care certification is a patient‐centered model focusing on the delivery of clinical care and relationship between the practitioner and the patient. The evaluation and resulting certification by the Joint Commission is based on 3 core components: (1) an assessment of compliance with consensus‐based national standards; (2) the effective use of established clinical practice guidelines to manage and optimize care; and (3) an organized approach to performance measurement and improved activities.55 For inpatient diabetes, the Joint Commission program has 7 major elements following the ADA recommendations, including general recommendations regarding diabetic documentation, BG targets, preventing hypoglycemia, diabetes care providers, diabetes self‐management education, medical nutrition therapy, and BG monitoring.54 This mirrors the Call to Action Consensus Conference essential elements for successful glycemic control programs.1
Other organizations such as the Surgical Care Improvement Partnership (SCIP) and National Surgical Quality Improvement Program (NSQIP) have included perioperative glycemic control measures, as it impacts surgical wound infections. The University HealthSystem Consortium (UHC) has benchmarking data and endorses perioperative glycemic control measures, whereas the Institute for Healthcare Improvement (IHI) has focused on safe use of insulin practices in its 5 Million Lives campaign.
HOSPITALIZATION IS A MOMENT OF OPPORTUNITY TO ASSESS AND INTERVENE
The benefits of outpatient glycemic control and quality preventive care are well established, and the reduction of adverse consequences of uncontrolled diabetes are a high priority in ambulatory medicine.5658 Hospitalization provides an opportunity to identify previously undiagnosed diabetes or prediabetes and, for patients with known diabetes, to assess and impact upon the long term course of diabetes.
As a first step, unless a recent hemoglobin A1C (HbA1c) is known, among hospitalized hyperglycemic patients an HbA1C should be obtained upon admission. Greci et al.59 showed that an HbA1c level >6.0% was 100% specific (14/14) and 57% sensitive (12/21) for the diagnosis of diabetes. Among patients having known diabetes, an HbA1C elevation on admission may justify intensification of preadmission management at the time of discharge. If discharge and postdischarge adjustments of preadmission regimens are planned in response to admission A1C elevations, then the modified long‐term treatment strategy can improve the A1C in the ambulatory setting.60 Moreover, the event of hospitalization is the ideal teachable moment for patients and their caregivers to improve self‐care activities. Yet floor nurses may be overwhelmed by the tasks of patient education. For ideal patient education, both a nutritionist and a diabetes nurse educator are needed to assess compliance with medication, diet, and other aspects of care.6163 There also is need for outpatient follow‐up education. Finally, at the time of discharge, there is a duty and an opportunity for the diabetes provider to communicate with outpatient care providers about the patient's regimen and glycemic control, and also, based on information gathered during the admission, to convey any evidence that might support the need for a change of long‐term strategy.64 Unfortunately, the opportunity that hospitalization presents to assess, educate, and intervene frequently is underused.1, 8, 51, 65
LARGE GAPS EXIST BETWEEN CURRENT AND OPTIMAL CARE
Despite the evidence that inpatient glycemic control is important for patient outcomes, and despite guidelines recommending tighter inpatient glycemic control, clinical practice has been slow to change. In many institutions, inpatient glycemic management has not improved over the past decade, and large gaps remain between current practice and optimal practice.
Studies of individual institutions provide several insights into gaps in care. For example, Schnipper et al.66 examined practices on the general medicine service of an academic medical center in Boston in 2004. Among 107 prospectively identified patients with a known diagnosis of diabetes or at least 1 glucose reading >200 mg/dL (excluding patients with diabetic ketoacidosis, hyperglycemic hyperosmolar state, or pregnancy), they found scheduled long‐acting insulin prescribed in 43% of patients, scheduled short‐acting/rapid‐acting insulin in only 4% of patients, and 80 of 89 patients (90%) on the same sliding scale insulin regimen despite widely varying insulin requirements. Thirty‐one percent of glucose readings were >180 mg/dL compared with 1.2% of readings <60 mg/dL (but 11% of patients had at least 1 episode of hypoglycemia). Of the 75 patients with at least 1 episode of hyperglycemia or hypoglycemia, only 35% had any change to their insulin regimen during the first 5 days of the hospitalization.
Other studies have confirmed this concept of clinical inertia (ie, recognition of the problem but failure to act).67 A study by Cook et al.68 of all hospitalized non‐ICU patients with diabetes or hyperglycemia and length of stay of 3 days between 2001 and 2004 showed that 20% of patients had persistent hyperglycemia during the hospitalization (defined as a mean glucose >200 mg/dL). Forty‐six percent of patients whose average glucose was in the top tertile did not have their insulin regimen intensified to a combination of short‐acting/rapid‐acting and long‐acting insulin, and 35% of these patients either had no change in their total daily insulin dose or actually had a decrease in their dose when comparing the last 24 hours with the first 24 hours of hospitalization, a concept they term negative therapeutic momentum.
Perhaps the most well‐balanced view of the current state of medical practice comes from the UHC benchmarking project.69 UHC is an alliance of 90 academic health centers. For the diabetes project, each institution reviewed the records of 50 randomly selected patients over 18 years of age with at least a 72‐hour length of stay, 1 of 7 prespecified Diagnosis Related Group (DRG) codes, and at least 2 consecutive glucose readings >180 mg/dL or the receipt of insulin any time during the hospitalization. Patients with a history of pancreatic transplant, pregnant at the time of admission, receiving hospice or comfort care, or receiving insulin for a reason other than glucose management were excluded. The study showed widespread gaps in processes and outcomes (Table 1). Moreover, performance varied widely across hospitals. For example, the morning glucose in the ICU on the second measurement day was 110 mg/dL in 18% of patients for the median‐performing hospital, with a range of 0% to 67% across all 37 measured hospitals. In the non‐ICU setting on the second measurement day, 26% of patients had all BG measurements = 180 mg/dL in the median‐performing hospital, with a range of 7% to 48%. Of note, hypoglycemia was relatively uncommon: in the median hospital, 2.4% of patient‐days had 1 or more BG readings <50 mg/dL (range: 0%8.6%). Finally, in the median‐performing hospital, effective insulin therapy (defined as short‐acting/rapid‐acting and long‐acting subcutaneous insulin, continuous insulin infusion, or subcutaneous insulin pump therapy) was prescribed in 45% of patients, with a range of 12% to 77% across measured hospitals.
Key Performance Measure | Results for Median‐Performing Hospital (%) |
---|---|
| |
Documentation of diabetes | 100 |
Hob A1c assessment within 30 days | 36.1 |
Glucose measurement within 8 hours of admission | 78.6 |
Glucose monitoring 4 times a day | 85.4 |
Median glucose reading > 200 mg/dL | 10.3 |
Effective insulin therapy* | 44.7 |
ICU day 2 morning glucose 110 mg/dL | 17.7 |
Non‐ICU day 2 all glucose readings 180 mg/dL | 26.3 |
Patient‐days with at least 1 glucose reading < 50 mg/dL | 2.4 |
FREQUENT PROBLEMS WITH COMMUNICATION AND COORDINATION
Those who work closely with frontline practitioners striving to improve inpatient glycemic management have noticed other deficiencies in care.1, 70 These include: a lack of coordination between feeding, BG measurement, and insulin administration, leading to mistimed and incorrectly dosed insulin; frequent use of sliding‐scale only regimens despite evidence that they are useless at best and harmful at worst;6, 47, 60, 71 discharge summaries that often do not mention follow‐up plans for hyperglycemic management; incomplete patient educational programs; breakdowns in care at transition points; nursing and medical staffs that are unevenly educated about the proper use of insulin; and patients who are often angry or confused about their diabetes care in the hospital. Collectively, these gaps in care serve as prime targets for any glycemic control program.
HYPOGLYCEMIA IS A PROMINENT INPATIENT SAFETY CONCERN
Hypoglycemia is common in the inpatient setting and is a legitimate safety concern. In a recently reported series of 2174 hospitalized patients receiving antihyperglycemic agents, it was found that 9.5% of patients experienced a total 484 hypoglycemic episodes (defined as 60 mg/dL).72 Hypoglycemia often occurred in the setting of insulin therapy and frequently resulted from a failure to recognize trends in BG readings or other clues that a patient was at risk for developing hypoglycemia.73 A common thread is the risk created by interruption of carbohydrate intake, noted by Fischer et al.73 and once again in the recent ICU study by Vriesendorp et al.74 Sources of error include: lack of coordination between feeding and medication administration, leading to mistiming of insulin action; lack of sufficient frequency in BG monitoring; lack of clarity or uniformity in the writing of orders; failure to recognize changes in insulin requirements due to advanced age, renal failure, liver disease, or change in clinical status; steroid use with subsequent tapering or interruption; changes in feeding; failure to reconcile medications; inappropriate use of oral antihyperglycemic agents, and communication or handoff failures.
It has been difficult to sort out whether hypoglycemia is a marker of severity of illness or whether it is an independent factor leading to poor outcomes. Observational studies lend credibility to the concept that patients having congestive heart failure or myocardial infarction may be at risk for excessive mortality if their average BG resides in the low end of the normal range.7578 Sympathetic activation occurs as the threshold for hypoglycemia is approached, such as occurs at BG = 70 or 72 mg/dL.79 Patients living with BG levels observed to be in the low end of the normal range might experience more severe but unobserved and undocumented episodes of neuroglycopenia. Arrhythmia and fatality have been directly attributed to strict glycemic control.80, 81 We are confronted with the need to interpret well conducted observational studies, evaluating subgroups at risk, and using multivariate analysis to assess the impact of hypoglycemia upon outcomes.82 In such studies, we will need to examine high‐risk subgroups, including cardiac patients, in particular, for the possibility that there is a J‐shaped curve for mortality as a function of average BG.
Unfortunately, clinical inertia exists in response to hypoglycemia just as it does with hyperglycemia. One recent study examined 52 patients who received intravenous 50% dextrose solution for an episode of hypoglycemia.83 Changes to insulin regimens were subsequently made in only 21 patients (40%), and diabetes specialists agreed with the changes for 11 of these patients. The other 31 patients (60%) received no changes in treatment, and diabetes specialists agreed with that decision for only 10 of these patients.
Although some increase in hypoglycemia might be expected with initiation of tight glycemic control efforts, the solution is not to undertreat hyperglycemia. Hyperglycemia creates an unsafe setting for the treatment of illness and disease. Sliding‐scaleonly regimens are ineffective in securing glycemic control and can result in increases in hypoglycemia as well as hyperglycemic excursions.6, 66 Inappropriate withholding of insulin doses can lead to severe glycemic excursions and even iatrogenic diabetic ketoacidosis (DKA). Systems approaches to avoid the errors outlined above can minimize or even reverse the increased risk of hypoglycemia expected with tighter glycemic targets.51
A SYSTEMS APPROACH IS NEEDED FOR THESE MULTIPLE COMPLEX PROBLEMS
Care is of the hyperglycemic inpatient is inherently complex. Previously established treatments are often inappropriate under conditions of altered insulin resistance, changing patterns of nutrition and carbohydrate exposure, comorbidities, concomitant medications, and rapidly changing medical and surgical status. Patients frequently undergo changes in the route and amount of nutritional exposure, including discrete meals, continuous intravenous dextrose, nil per orem (nothing by mouth status; NPO) status, grazing on nutritional supplements or liquid diets with or without meals, bolus enteral feedings, overnight enteral feedings with daytime grazing, total parenteral nutrition, continuous peritoneal dialysis, and overnight cycling of peritoneal dialysis. Relying on individual expertise and vigilance to negotiate this complex terrain without safeguards, protocols, standardization of orders, and other systems change is impractical and unwise.
Transitions across care providers and locations lead to multiple opportunities for breakdown in the quality, consistency, and safety of care.64, 65 At the time of ward transfer or change of patient status, previous medication and monitoring orders sometimes are purged. At the time of discharge, there may be risk of continuation of anti‐hyperglycemic therapy, initiated to cover medical stress, in doses that will subsequently be unsafe.
In the face of this complexity, educational programs alone will not suffice to improve care. Institutional commitment and systems changes are essential.
MARKED IMPROVEMENT IS POSSIBLE AND TOOLS EXIST: A ROADMAP IS IN PLACE
Fortunately, a roadmap is in place to help us achieve better glycemic control, improve insulin management, and address the long list of current deficiencies in care. This is imperative to develop consistent processes in order to achieve maximum patient quality outcomes that effective glycemic management offers. This roadmap entails 4 components: (1) national awareness, (2) national guidelines, (3) consensus statements, and (4) effective tools. As mentioned above, the first two components of this roadmap are now in place.
As these national guidelines become more widely accepted, the next step will be the incorporation of this into programs like Pay‐for Performance and the Physician Quality Reporting Initiative (PQRI), which will impact reimbursement to both hospitals and providers.
Regarding the third component, a recent multidisciplinary consensus conference1 outlined the essential elements needed for successful implementation of an inpatient glycemic control program which include:
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An appropriate level of administrative support.
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Formation of a multidisciplinary steering committee to drive the development of initiatives and empowered to enact change.
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Assessment of current processes, quality of care, and barriers to practice change.
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Development and implementation of interventions including standardized order sets, protocols, policies and algorithms with associated educational programs.
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Metrics for evaluation of glycemic control, hypoglycemia, insulin use patterns, and other aspects of care.
Finally, extensive resources and effective tools are now available to help institutions achieve better inpatient glucose control. The Society of Hospital Medicine (SHM), in conjunction with the ADA, AACE, the American College of Physicians (ACP), the Case Management Society of America (CMSA), the American Society of Consultant Pharmacists, nursing, and diabetic educators have all partnered to produce a comprehensive guide to effective implementation of glycemic control and preventing hypoglycemia.49 This comprehensive workbook is a proven performance improvement framework and is available on the SHM Web site.48 Details and examples of all essential elements are covered in this workbook along with opportunities for marked improvement bolstered by integration of high reliability design features and attention to effective implementation techniques. The remainder of this supplement crystallizes a substantial portion of this material. The AACE has also recently offered a valuable web‐based resource to encourage institutional glycemic control efforts.49
GLYCEMIC CONTROL INITIATIVES CAN BE COST‐EFFECTIVE
Achieving optimal glycemic control safely requires monitoring, education, and other measures, which can be expensive, labor intensive, and require coordination of the services of many hospital divisions. This incremental expense has been shown to be cost‐effective in a variety of settings.1, 84, 85 The costs of glycemic control initiatives have demonstrated a good return on investment via:
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Improved LOS, readmission rates, morbidity, and mortality.
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Improved documentation of patient acuity and related payment for acuity.
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Income generated via incremental physician and allied health professional billing.
CONCLUSION AND SUMMARY
Evidence exists that appropriate management of hyperglycemia improves outcomes, whereas the current state of affairs is that most medical centers currently manage this suboptimally. This is concerning given the magnitude of diabetes and hyperglycemia in our inpatient setting in the United States. To bring awareness to this issue, multiple initiatives (guidelines, certification programs, workbooks, etc.) are available by various organizations including the ADA, AACE, SCIP, NSQIP, IHI, UHC, the Joint Commission, and SHM. However, this is not enough. Change occurs at the local level, and institutional prioritization and support is needed to empower a multidisciplinary steering committee, with appropriate administrative support, to standardize and improve systems in the face of substantial cultural issues and complex barriers. Improved data collection and reporting, incremental monitoring, creation of metrics, and improved documentation are an absolutely necessary necessity to achieve breakthrough levels of improvement.
Now the time is right to make an assertive effort to improve inpatient glycemic control and related issues, and push for appropriate support at your institution to help achieve this in the interest of patient safety and optimal outcomes.
Medical centers are faced with multiple competing priorities when deciding how to focus their improvement efforts and meet the ever expanding menu of publicly reported and regulatory issues. In this article we expand on the rationale for supporting inpatient glycemic control programs as a priority that should be moved near the top of the list. We review the evidence for establishing glycemic range targets, and also review the limitations of this evidence, acknowledging, as does the American Diabetes Association (ADA), that in both the critical care and non‐critical care venue, glycemic goals must take into account the individual patient's situation as well as hospital system support for achieving these goals.1, 2 We emphasize that inpatient glycemic control programs are needed to address a wide variety of quality and safety issues surrounding the care of the inpatient with diabetes and hyperglycemia, and we wish to elevate the dialogue beyond arguments surrounding adoption of one glycemic target versus another. The Society of Hospital Medicine Glycemic Control Task Force members are not in unanimous agreement with the American Association of Clinical Endocrinologists (AACE)/ADA inpatient glycemic targets. However, we do agree on several other important points, which we will expand on in this article:
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Uncontrolled hyperglycemia and iatrogenic hypoglycemia are common and potentially dangerous situations that are largely preventable with safe and proven methods.
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The current state of care for our inpatients with hyperglycemia is unacceptably poor on a broad scale, with substandard education, communication, coordination, and treatment issues.
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Concerted efforts with changes in the design of the process of care are needed to improve this state of affairs.
DIABETES AND HYPERGLYCEMIA ARE VERY COMMON INPATIENT CONDITIONS
Diabetes mellitus (DM) has reached epidemic proportions in the United States. A reported 9.3% of adults over 20 years of age have diabetes, representing over 20 million persons. Despite increasing awareness, diabetes remains undiagnosed in approximately 30% of these persons.3 Concurrent with the increasing prevalence of diabetes in the U.S. population from 1980 through 2003, the number of hospital discharges with diabetes as any listed diagnosis more than doubled, going from 2.2 to 5.1 million discharges.4 Hospital care for patients with diabetes and hyperglycemia poses a significant health economic burden in the United States, representing over 40 billion dollars in annual direct medical expenditures.5
Hyperglycemia in the hospital may be due to known diabetes, to previously unrecognized diabetes, to prediabetes, and/or to the stress of surgery or illness. Deterioration in glycemic control in the hospital setting is most commonly associated with one or more factors, including stress‐induced release of insulin counterregulatory hormones (catecholamines, cortisol, glucagon, and growth hormone), exogenous administration of high dose glucocorticoids, and suboptimal glycemic management strategies.68 In a Belgian medical intensive care unit (MICU) randomized controlled trial (RCT) of strict versus conventional glycemic control, mean blood glucose (BG) on admission to the unit in the intention to treat group was 162 70 mg/dL (n = 1200),9 and in this group's RCT of 1548 surgical intensive care unit (SICU) patients, BG > 110 mg/dL was observed in over 70% of subjects.10 Mean BG of >145 mg/dL has been reported in 39%11 and BG >200 mg/dL in anywhere from 11% to 31% of intensive care unit (ICU) patients.10, 12 For general medicine and surgery, 1 study of 2030 patients admitted to a teaching hospital revealed that 26% of admissions had a known history of DM and 12% had new hyperglycemia, as evidenced by an admission or in‐hospital fasting BG of 126 mg/dL or more or a random BG of 200 mg/dL or more on 2 or more determinations.13 National and regional estimates on hospital use maintained by the Agency for Healthcare Research and Quality include data concerning diabetes diagnoses alone, without hyperglycemia, and may be displayed by querying its Web site.14 In cardiovascular populations almost 70% of patients having a first myocardial infarction have been reported to have either known DM, previously unrecognized diabetes, or impaired glucose tolerance.15
THE EVIDENCE SUPPORTS INPATIENT GLYCEMIC CONTROL
Evidence: Physiology
The pathophysiologic mechanisms through which hyperglycemia is linked to suboptimal outcomes in the hospital are complex and multifactorial. Although it is beyond the scope of this article to discuss these mechanisms in detail, research has broadly focused in the following areas: (1) immune system dysfunction, associated with a proinflammatory state and impaired white blood cell function; (2) metabolic derangements leading to oxidative stress, release of free fatty acids, reduction in endogenous insulin secretion, and fluid and electrolyte imbalance; and (3) a wide variety of vascular system responses (eg, endothelial dysfunction with impairment of tissue perfusion, a prothrombotic state, increased platelet aggregation, and left ventricular dysfunction).8, 1618
Conversely administration of insulin suppresses or reverses many of these abnormalities including generation of reactive oxygen species (ROS) and activation of inflammatory mechanisms,19 and leads to a fall in C‐reactive protein, which accompanied the clinical benefit of intensive insulin therapy (IIT) in the Leuven, Belgium, ICU population,20 and prevents mitochondrial abnormalities in hepatocytes.21 In the same surgical ICU cohort, Langouche et al.22 report suppression of intracellular adhesion molecule‐1 (ICAM‐1) and E‐selectin, markers of inflammation, and reduction in plasma nitric oxide (NO) and innate nitric oxide (iNOS) expression with insulin administration in patients treated with intravenous (IV) IIT.22 These data further support the role of insulin infusion in suppressing inflammation and endothelial dysfunction. The authors suggest that maintaining normoglycemia with IIT during critical illness protects the endothelium, thereby contributing to prevention of organ failure and death.22 Based on accumulating data in the literature such as that cited above, it has been suggested that a new paradigm in which glucose and insulin are related not only through their metabolic action but also through inflammatory mechanisms offers important potential therapeutic opportunities.19
Evidence: Epidemiology/Observational Studies/Non‐RCT Interventional Studies
A strong association between hospital hyperglycemia and negative outcomes has been reported in numerous observational studies in diverse adult medical and surgical settings. In over 1800 hospital admissions, those with new hyperglycemia had an in‐hospital mortality rate of 16% compared with 3% mortality in patients with known diabetes and 1.7% in normoglycemic patients (P < 0.01). These data suggest that hyperglycemia due to previously unrecognized diabetes may be an independent marker of in‐hospital mortality.13
Hyperglycemia has been linked to adverse outcomes in myocardial infarction, stroke,2328 postoperative nosocomial infection risk, pneumonia, renal transplant, cancer chemotherapy, percutaneous coronary interventions, and cardiac surgery.2938 These observational studies have the usual limitations inherent in their design. Demonstrating a strong association of hyperglycemia with adverse outcomes is not a guarantee that the hyperglycemia is the cause for the poor outcome, as hyperglycemia can reflect a patient under more stress who is at a higher risk for adverse outcome. By the same token, the strong association of hyperglycemia with the risk of poor outcomes seen in these studies does not guarantee that euglycemia would mitigate this risk.
Nonetheless, there are several factors that make the body of evidence for glycemic control more compelling. First, the association has a rational physiologic basis as described above. Second, the associations are consistent across a variety of patient populations and disease entities, and demonstrate a dose‐response relationship. Third, in studies that control for comorbidities and severity of illness, hyperglycemia persists as an independent risk factor for adverse outcomes, whether the patient has a preexisting diagnosis of diabetes or not. Last, non‐RCT interventional studies and RCTs largely reinforce these studies.
The Portland Diabetic Project has reported prospective, nonrandomized data over 17 years on the use of an IV insulin therapy protocol in cardiac surgery patients.38 This program has implemented stepped lowering of target BG, with the most recent data report implementing a goal BG <150 mg/dL.35 The current protocol uses a BG target of 70110 mg/dL, but results have not yet been published.39 Mortality and deep sternal wound infection rates for patients with diabetes who remain on the IV insulin protocol for 3 days have been lowered to levels equivalent to those for nondiabetic patients. This group has also reported reductions in length of stay and cost‐effectiveness of targeted glycemic control in the cardiac surgery population.35 Their data have to a large extent driven a nationwide movement to implement targeted BG control in cardiac surgery patients.
Another large ICU study (mixed medical‐surgical, n = 800 patients) also supports a benefit through targeted BG control (130.7 versus 152.3 mg/dL, P < 0.001) when compared with historical controls. This study demonstrated reduction in in‐hospital mortality (relative risk reduction 29.3%, P = 0.002), duration of ICU stay (10.8%, P = 0.04), acute renal failure (75%, P = 0.03), and blood transfusions (18.7%, P = 0.002),40 representing a similar magnitude of effect as was demonstrated by the Belgian group.
Evidence: RCTs
Evidence is accumulating that demonstrates an advantage in terms of morbidity and mortality when targeted glycemic control using intravenous insulin infusion is implemented in the hospital. The most robust data have been reported from ICU and cardiac surgery settings. The largest randomized, controlled study to date enrolled 1548 patients in a surgical ICU in Leuven, Belgium who were randomized to either intensive (IT) or conventional (CT) insulin therapy. Mean glucose attained was 103 19 and 153 33 mg/dL in each arm, respectively. The intensive insulin group demonstrated a reduction in both ICU (4.6% versus 8.0%) and in‐hospital mortality (7.2% versus 10.9%), as well as bloodstream infections, acute renal failure, transfusions, and polyneuropathy, the latter being reflected by duration of mechanical ventilation (P < 0.01 for all). Although a similar study in an MICU did not achieve statistical significance in the overall intention‐to‐treat analysis, it did demonstrate reductions in mortality (from 52.5% to 43.0%) in patients with at least 3 days of ICU treatment. It should also be noted that in this MICU population hypoglycemia rates were higher and level of glycemic control attained not as rigorous as in the same group's SICU cohort, factors which may have had an impact on observed outcomes. A meta‐analysis of these two Leuven, Belgium, studies demonstrated a reduction in mortality (23.6% versus 20.4%, absolute risk reduction [ARR] 3.2%, P = 0.004)) in all patients treated with IIT, with a larger reduction in mortality (37.9% versus 30.1%, ARR 7.8%, P = 0.002) observed in patients with at least 3 days of IIT, as well as substantial reductions in morbidity.9, 10, 41, 42
Several other studies must be mentioned in this context. A small (n = 61), randomized study in another SICU did not show a mortality benefit, perhaps because the number of subjects was not adequate to reach statistical significance, but did result in a significant reduction in nosocomial infections in patients receiving IIT (BG = 125 versus 179 mg/dL, P < 0.001).43 Two international multicenter studies recently stopped enrollment due to excess rates of hypoglycemia. The Volume Substitution and Insulin Therapy in Severe Sepsis (VISEP) study, in a mixed medical and surgical sepsis population, showed no significant reduction in mortality in the intensively‐treated group. Serious adverse events were reported according to standard definitions. Enrollment was stopped before the full number of subjects had been randomized. Among the 537 evaluable cases, hypoglycemia (BG < 40 mg/dL) was reported as 17.0% in the IT group and 4.1% (P < 0.001) in the control group,44 and the rate of serious adverse events was higher in the IT group (10.9% versus 5.2%, P = 0.01). It is notable that the rate of hypoglycemia was comparable to the 18.7% rate seen in the IT group in the Leuven, Belgium, medical ICU study.9 The Glucontrol study enrolled 855 medical and surgical ICU patients and was similarly terminated because of hypoglycemia (BG < 40 mg/dL) at a rate of 8.6% compared to 2.4% in the control group (P < 0.001). Insulin infusion protocols and outcome data have not yet been published.42, 45
These studies with very high hypoglycemia rates each used an algorithm based on the Leuven, Belgium, protocol. The rates of severe hypoglycemia are 34 that reported by a variety of others achieving similar or identical glycemic targets. Hypoglycemia should not be construed as a reason to not use a standardized insulin infusion protocol. In comparing protocols that have been published, it is apparent that rates of hypoglycemia differ substantially and that performance results of some algorithms are not necessarily replicable across sites.46 Dose‐defining designs can be substantively more sophisticated than those used in the trials mentioned, in some cases incorporating principles of control engineering. The variability of hypoglycemia rates under differing insulin infusion protocols is a compelling reason to devote institutional effort to monitoring the efficacy and safety of the infusion protocols that are used.
High‐level evidence from randomized, controlled trials demonstrating outcomes benefit through targeted BG control outside the ICU is lacking at this point in time, but it must be noted that feasibility is suggested by a recent randomized control trial (RABBIT2) that demonstrated the superiority of basal bolus insulin regimens to sliding scale insulin in securing glycemic control, without any increase in hypoglycemia.47
Summing Up the Evidence
It is clear that hyperglycemia is associated with negative clinical outcomes throughout the hospital, and level A evidence is available to support tight glucose control in the SICU setting. However, in view of the imperfect and incomplete nature of the evidence, controversy persists around how stringent glycemic targets should be in the ICU, on whether glycemic targets should differ between SICU and MICU patients, and especially what the targets should be in the non‐ICU setting. There should be hesitancy to extrapolate glycemic targets to be applied beyond the populations that have been studied with RCTs or to assume benefit for medical conditions that have not been examined for the impact of interventions to control hyperglycemia. Institutions might justifiably choose more liberal targets than those promoted in national recommendations/guidelines2, 4850 until safe attainment of more moderate goals is demonstrated. However, even critics agree that uncontrolled hyperglycemia exceeding 180200 mg/dL in any acute care setting is undesirable. Moreover, strong observational data showing the hazards of hyperglycemia in noncritical care units (even after adjustment for severity of illness) combined with the high rate of adverse drug events associated with insulin use, argue strongly for a standardized approach to treating diabetes and hyperglycemia in the hospital. Even though no RCTs exist demonstrating outcomes benefits of achieving glycemic target on wards, the alternatives to control of hyperglycemia using scheduled insulin therapy are unacceptable. Oral agent therapy is potentially dangerous and within the necessary timeframe is likely to be ineffective; sliding scale management is inferior to basal‐bolus insulin therapy, as shown inan RCT,47 and is unsafe; and on the wards improved glycemic control can be achieved simultaneously with a reduction in hypoglycemia.51
INPATIENT GLYCEMIC CONTROL IS INCREASINGLY INCORPORATED INTO PUBLIC REPORTING, GUIDELINES, REGULATORY AGENCY, AND NATIONAL QUALITY INITIATIVE PRIORITIES
National quality initiatives, public reporting, pay‐for‐performance, and guideline‐based care continue to play an increasingly important role in the U.S. healthcare system. Over the years these initiatives have focused on various disease states (venous thromboembolism, congestive heart failure, community‐acquired pneumonia, etc.) in an attempt to standardize care and improve patient safety and quality. Inpatient hyperglycemic control is also increasingly being incorporated into public reporting, regulatory compliance, and national quality initiatives.
Professional organizations such as the ADA2 and AACE50 have published guidelines supporting improved glycemic control, the safe use of insulin, and other measures to improve care for hyperglycemic inpatients. The AACE has a Web site dedicated to hospital hyperglycemia.52 The Society of Hospital Medicine48 has created a resource room on its Web site and a workbook for improvement49 on optimizing the care of inpatients with hyperglycemia and diabetes. The guidelines and Web sites help raise awareness and educate physicians and healthcare workers in inpatient glucose management. The American Heart Association has incorporated specific recommendation regarding inpatient diabetic management in its Get With the Guidelines.53
The Joint Commission54 has developed an advanced disease‐specific certification on inpatient diabetes. Disease management programs are important components of complex healthcare systems that serve to coordinate chronic care, promote early detection and prevention, and reduce overall healthcare costs. Certification is increasingly important to providers, payers, and healthcare institutions because it demonstrates a commitment to quality and patient safety. The Joint Commission disease‐specific care certification is a patient‐centered model focusing on the delivery of clinical care and relationship between the practitioner and the patient. The evaluation and resulting certification by the Joint Commission is based on 3 core components: (1) an assessment of compliance with consensus‐based national standards; (2) the effective use of established clinical practice guidelines to manage and optimize care; and (3) an organized approach to performance measurement and improved activities.55 For inpatient diabetes, the Joint Commission program has 7 major elements following the ADA recommendations, including general recommendations regarding diabetic documentation, BG targets, preventing hypoglycemia, diabetes care providers, diabetes self‐management education, medical nutrition therapy, and BG monitoring.54 This mirrors the Call to Action Consensus Conference essential elements for successful glycemic control programs.1
Other organizations such as the Surgical Care Improvement Partnership (SCIP) and National Surgical Quality Improvement Program (NSQIP) have included perioperative glycemic control measures, as it impacts surgical wound infections. The University HealthSystem Consortium (UHC) has benchmarking data and endorses perioperative glycemic control measures, whereas the Institute for Healthcare Improvement (IHI) has focused on safe use of insulin practices in its 5 Million Lives campaign.
HOSPITALIZATION IS A MOMENT OF OPPORTUNITY TO ASSESS AND INTERVENE
The benefits of outpatient glycemic control and quality preventive care are well established, and the reduction of adverse consequences of uncontrolled diabetes are a high priority in ambulatory medicine.5658 Hospitalization provides an opportunity to identify previously undiagnosed diabetes or prediabetes and, for patients with known diabetes, to assess and impact upon the long term course of diabetes.
As a first step, unless a recent hemoglobin A1C (HbA1c) is known, among hospitalized hyperglycemic patients an HbA1C should be obtained upon admission. Greci et al.59 showed that an HbA1c level >6.0% was 100% specific (14/14) and 57% sensitive (12/21) for the diagnosis of diabetes. Among patients having known diabetes, an HbA1C elevation on admission may justify intensification of preadmission management at the time of discharge. If discharge and postdischarge adjustments of preadmission regimens are planned in response to admission A1C elevations, then the modified long‐term treatment strategy can improve the A1C in the ambulatory setting.60 Moreover, the event of hospitalization is the ideal teachable moment for patients and their caregivers to improve self‐care activities. Yet floor nurses may be overwhelmed by the tasks of patient education. For ideal patient education, both a nutritionist and a diabetes nurse educator are needed to assess compliance with medication, diet, and other aspects of care.6163 There also is need for outpatient follow‐up education. Finally, at the time of discharge, there is a duty and an opportunity for the diabetes provider to communicate with outpatient care providers about the patient's regimen and glycemic control, and also, based on information gathered during the admission, to convey any evidence that might support the need for a change of long‐term strategy.64 Unfortunately, the opportunity that hospitalization presents to assess, educate, and intervene frequently is underused.1, 8, 51, 65
LARGE GAPS EXIST BETWEEN CURRENT AND OPTIMAL CARE
Despite the evidence that inpatient glycemic control is important for patient outcomes, and despite guidelines recommending tighter inpatient glycemic control, clinical practice has been slow to change. In many institutions, inpatient glycemic management has not improved over the past decade, and large gaps remain between current practice and optimal practice.
Studies of individual institutions provide several insights into gaps in care. For example, Schnipper et al.66 examined practices on the general medicine service of an academic medical center in Boston in 2004. Among 107 prospectively identified patients with a known diagnosis of diabetes or at least 1 glucose reading >200 mg/dL (excluding patients with diabetic ketoacidosis, hyperglycemic hyperosmolar state, or pregnancy), they found scheduled long‐acting insulin prescribed in 43% of patients, scheduled short‐acting/rapid‐acting insulin in only 4% of patients, and 80 of 89 patients (90%) on the same sliding scale insulin regimen despite widely varying insulin requirements. Thirty‐one percent of glucose readings were >180 mg/dL compared with 1.2% of readings <60 mg/dL (but 11% of patients had at least 1 episode of hypoglycemia). Of the 75 patients with at least 1 episode of hyperglycemia or hypoglycemia, only 35% had any change to their insulin regimen during the first 5 days of the hospitalization.
Other studies have confirmed this concept of clinical inertia (ie, recognition of the problem but failure to act).67 A study by Cook et al.68 of all hospitalized non‐ICU patients with diabetes or hyperglycemia and length of stay of 3 days between 2001 and 2004 showed that 20% of patients had persistent hyperglycemia during the hospitalization (defined as a mean glucose >200 mg/dL). Forty‐six percent of patients whose average glucose was in the top tertile did not have their insulin regimen intensified to a combination of short‐acting/rapid‐acting and long‐acting insulin, and 35% of these patients either had no change in their total daily insulin dose or actually had a decrease in their dose when comparing the last 24 hours with the first 24 hours of hospitalization, a concept they term negative therapeutic momentum.
Perhaps the most well‐balanced view of the current state of medical practice comes from the UHC benchmarking project.69 UHC is an alliance of 90 academic health centers. For the diabetes project, each institution reviewed the records of 50 randomly selected patients over 18 years of age with at least a 72‐hour length of stay, 1 of 7 prespecified Diagnosis Related Group (DRG) codes, and at least 2 consecutive glucose readings >180 mg/dL or the receipt of insulin any time during the hospitalization. Patients with a history of pancreatic transplant, pregnant at the time of admission, receiving hospice or comfort care, or receiving insulin for a reason other than glucose management were excluded. The study showed widespread gaps in processes and outcomes (Table 1). Moreover, performance varied widely across hospitals. For example, the morning glucose in the ICU on the second measurement day was 110 mg/dL in 18% of patients for the median‐performing hospital, with a range of 0% to 67% across all 37 measured hospitals. In the non‐ICU setting on the second measurement day, 26% of patients had all BG measurements = 180 mg/dL in the median‐performing hospital, with a range of 7% to 48%. Of note, hypoglycemia was relatively uncommon: in the median hospital, 2.4% of patient‐days had 1 or more BG readings <50 mg/dL (range: 0%8.6%). Finally, in the median‐performing hospital, effective insulin therapy (defined as short‐acting/rapid‐acting and long‐acting subcutaneous insulin, continuous insulin infusion, or subcutaneous insulin pump therapy) was prescribed in 45% of patients, with a range of 12% to 77% across measured hospitals.
Key Performance Measure | Results for Median‐Performing Hospital (%) |
---|---|
| |
Documentation of diabetes | 100 |
Hob A1c assessment within 30 days | 36.1 |
Glucose measurement within 8 hours of admission | 78.6 |
Glucose monitoring 4 times a day | 85.4 |
Median glucose reading > 200 mg/dL | 10.3 |
Effective insulin therapy* | 44.7 |
ICU day 2 morning glucose 110 mg/dL | 17.7 |
Non‐ICU day 2 all glucose readings 180 mg/dL | 26.3 |
Patient‐days with at least 1 glucose reading < 50 mg/dL | 2.4 |
FREQUENT PROBLEMS WITH COMMUNICATION AND COORDINATION
Those who work closely with frontline practitioners striving to improve inpatient glycemic management have noticed other deficiencies in care.1, 70 These include: a lack of coordination between feeding, BG measurement, and insulin administration, leading to mistimed and incorrectly dosed insulin; frequent use of sliding‐scale only regimens despite evidence that they are useless at best and harmful at worst;6, 47, 60, 71 discharge summaries that often do not mention follow‐up plans for hyperglycemic management; incomplete patient educational programs; breakdowns in care at transition points; nursing and medical staffs that are unevenly educated about the proper use of insulin; and patients who are often angry or confused about their diabetes care in the hospital. Collectively, these gaps in care serve as prime targets for any glycemic control program.
HYPOGLYCEMIA IS A PROMINENT INPATIENT SAFETY CONCERN
Hypoglycemia is common in the inpatient setting and is a legitimate safety concern. In a recently reported series of 2174 hospitalized patients receiving antihyperglycemic agents, it was found that 9.5% of patients experienced a total 484 hypoglycemic episodes (defined as 60 mg/dL).72 Hypoglycemia often occurred in the setting of insulin therapy and frequently resulted from a failure to recognize trends in BG readings or other clues that a patient was at risk for developing hypoglycemia.73 A common thread is the risk created by interruption of carbohydrate intake, noted by Fischer et al.73 and once again in the recent ICU study by Vriesendorp et al.74 Sources of error include: lack of coordination between feeding and medication administration, leading to mistiming of insulin action; lack of sufficient frequency in BG monitoring; lack of clarity or uniformity in the writing of orders; failure to recognize changes in insulin requirements due to advanced age, renal failure, liver disease, or change in clinical status; steroid use with subsequent tapering or interruption; changes in feeding; failure to reconcile medications; inappropriate use of oral antihyperglycemic agents, and communication or handoff failures.
It has been difficult to sort out whether hypoglycemia is a marker of severity of illness or whether it is an independent factor leading to poor outcomes. Observational studies lend credibility to the concept that patients having congestive heart failure or myocardial infarction may be at risk for excessive mortality if their average BG resides in the low end of the normal range.7578 Sympathetic activation occurs as the threshold for hypoglycemia is approached, such as occurs at BG = 70 or 72 mg/dL.79 Patients living with BG levels observed to be in the low end of the normal range might experience more severe but unobserved and undocumented episodes of neuroglycopenia. Arrhythmia and fatality have been directly attributed to strict glycemic control.80, 81 We are confronted with the need to interpret well conducted observational studies, evaluating subgroups at risk, and using multivariate analysis to assess the impact of hypoglycemia upon outcomes.82 In such studies, we will need to examine high‐risk subgroups, including cardiac patients, in particular, for the possibility that there is a J‐shaped curve for mortality as a function of average BG.
Unfortunately, clinical inertia exists in response to hypoglycemia just as it does with hyperglycemia. One recent study examined 52 patients who received intravenous 50% dextrose solution for an episode of hypoglycemia.83 Changes to insulin regimens were subsequently made in only 21 patients (40%), and diabetes specialists agreed with the changes for 11 of these patients. The other 31 patients (60%) received no changes in treatment, and diabetes specialists agreed with that decision for only 10 of these patients.
Although some increase in hypoglycemia might be expected with initiation of tight glycemic control efforts, the solution is not to undertreat hyperglycemia. Hyperglycemia creates an unsafe setting for the treatment of illness and disease. Sliding‐scaleonly regimens are ineffective in securing glycemic control and can result in increases in hypoglycemia as well as hyperglycemic excursions.6, 66 Inappropriate withholding of insulin doses can lead to severe glycemic excursions and even iatrogenic diabetic ketoacidosis (DKA). Systems approaches to avoid the errors outlined above can minimize or even reverse the increased risk of hypoglycemia expected with tighter glycemic targets.51
A SYSTEMS APPROACH IS NEEDED FOR THESE MULTIPLE COMPLEX PROBLEMS
Care is of the hyperglycemic inpatient is inherently complex. Previously established treatments are often inappropriate under conditions of altered insulin resistance, changing patterns of nutrition and carbohydrate exposure, comorbidities, concomitant medications, and rapidly changing medical and surgical status. Patients frequently undergo changes in the route and amount of nutritional exposure, including discrete meals, continuous intravenous dextrose, nil per orem (nothing by mouth status; NPO) status, grazing on nutritional supplements or liquid diets with or without meals, bolus enteral feedings, overnight enteral feedings with daytime grazing, total parenteral nutrition, continuous peritoneal dialysis, and overnight cycling of peritoneal dialysis. Relying on individual expertise and vigilance to negotiate this complex terrain without safeguards, protocols, standardization of orders, and other systems change is impractical and unwise.
Transitions across care providers and locations lead to multiple opportunities for breakdown in the quality, consistency, and safety of care.64, 65 At the time of ward transfer or change of patient status, previous medication and monitoring orders sometimes are purged. At the time of discharge, there may be risk of continuation of anti‐hyperglycemic therapy, initiated to cover medical stress, in doses that will subsequently be unsafe.
In the face of this complexity, educational programs alone will not suffice to improve care. Institutional commitment and systems changes are essential.
MARKED IMPROVEMENT IS POSSIBLE AND TOOLS EXIST: A ROADMAP IS IN PLACE
Fortunately, a roadmap is in place to help us achieve better glycemic control, improve insulin management, and address the long list of current deficiencies in care. This is imperative to develop consistent processes in order to achieve maximum patient quality outcomes that effective glycemic management offers. This roadmap entails 4 components: (1) national awareness, (2) national guidelines, (3) consensus statements, and (4) effective tools. As mentioned above, the first two components of this roadmap are now in place.
As these national guidelines become more widely accepted, the next step will be the incorporation of this into programs like Pay‐for Performance and the Physician Quality Reporting Initiative (PQRI), which will impact reimbursement to both hospitals and providers.
Regarding the third component, a recent multidisciplinary consensus conference1 outlined the essential elements needed for successful implementation of an inpatient glycemic control program which include:
-
An appropriate level of administrative support.
-
Formation of a multidisciplinary steering committee to drive the development of initiatives and empowered to enact change.
-
Assessment of current processes, quality of care, and barriers to practice change.
-
Development and implementation of interventions including standardized order sets, protocols, policies and algorithms with associated educational programs.
-
Metrics for evaluation of glycemic control, hypoglycemia, insulin use patterns, and other aspects of care.
Finally, extensive resources and effective tools are now available to help institutions achieve better inpatient glucose control. The Society of Hospital Medicine (SHM), in conjunction with the ADA, AACE, the American College of Physicians (ACP), the Case Management Society of America (CMSA), the American Society of Consultant Pharmacists, nursing, and diabetic educators have all partnered to produce a comprehensive guide to effective implementation of glycemic control and preventing hypoglycemia.49 This comprehensive workbook is a proven performance improvement framework and is available on the SHM Web site.48 Details and examples of all essential elements are covered in this workbook along with opportunities for marked improvement bolstered by integration of high reliability design features and attention to effective implementation techniques. The remainder of this supplement crystallizes a substantial portion of this material. The AACE has also recently offered a valuable web‐based resource to encourage institutional glycemic control efforts.49
GLYCEMIC CONTROL INITIATIVES CAN BE COST‐EFFECTIVE
Achieving optimal glycemic control safely requires monitoring, education, and other measures, which can be expensive, labor intensive, and require coordination of the services of many hospital divisions. This incremental expense has been shown to be cost‐effective in a variety of settings.1, 84, 85 The costs of glycemic control initiatives have demonstrated a good return on investment via:
-
Improved LOS, readmission rates, morbidity, and mortality.
-
Improved documentation of patient acuity and related payment for acuity.
-
Income generated via incremental physician and allied health professional billing.
CONCLUSION AND SUMMARY
Evidence exists that appropriate management of hyperglycemia improves outcomes, whereas the current state of affairs is that most medical centers currently manage this suboptimally. This is concerning given the magnitude of diabetes and hyperglycemia in our inpatient setting in the United States. To bring awareness to this issue, multiple initiatives (guidelines, certification programs, workbooks, etc.) are available by various organizations including the ADA, AACE, SCIP, NSQIP, IHI, UHC, the Joint Commission, and SHM. However, this is not enough. Change occurs at the local level, and institutional prioritization and support is needed to empower a multidisciplinary steering committee, with appropriate administrative support, to standardize and improve systems in the face of substantial cultural issues and complex barriers. Improved data collection and reporting, incremental monitoring, creation of metrics, and improved documentation are an absolutely necessary necessity to achieve breakthrough levels of improvement.
Now the time is right to make an assertive effort to improve inpatient glycemic control and related issues, and push for appropriate support at your institution to help achieve this in the interest of patient safety and optimal outcomes.
- American College of Endocrinology and American Diabetes Association Consensus Statement on Inpatient Diabetes and Glycemic Control: A call to action.Diabetes Care.2006;29:1955–1962.
- Standards of medical care in diabetes‐‐2008.Diabetes Care.2008;31(Suppl 1):S12–S54.
- Prevalence of diabetes and impaired fasting glucose in adults in the U.S. population: National Health And Nutrition Examination Survey 1999–2002.Diabetes Care.2006;29:1263–1268. , , , et al.
- Centers for Disease Control and Prevention.National Diabetes Fact Sheet: General Information and National Estimates on Diabetes in the United States, 2005.Atlanta, GA:U.S. Department of Health and Human Services, Centers for Disease Control and Prevention,2005. Available at: http://www.cdc.gov/diabetes/pubs/factsheet05.htm. Accessed September 2007.
- Economic costs of diabetes in the US in 2002.Diabetes Care.2003;26:917–932. , , .
- Glycemic control and sliding scale insulin use in medical inpatients with diabetes mellitus.Arch Intern Med.1997;157:545–552. , , .
- Inpatient management of diabetes mellitus.Am J Med.2002;113:317–323. , , .
- Management of diabetes and hyperglycemia in hospitals.Diabetes Care.2004;27:553–591. , , , et al.
- Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354:449–461. , , , et al.
- Intensive insulin therapy in critically ill patients.N Engl J Med.2001;345:1359–1367. , , , et al.
- Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.Mayo Clin Proc.2003;78:1471–1478. .
- Unrecognized diabetes among hospitalized patients.Diabetes Care.1998;21:246–249. , , , , .
- Hyperglycemia: an independent marker of in‐hospital mortality in patients with undiagnosed diabetes.J Clin Endocrinol Metab.2002;87:978–982. , , , , , .
- United States Department of Health and Human Services Agency for Healthcare Research and Quality.2007. Available at: http://hcupnet.ahrq.gov. Accessed December 2007.
- Glucose metabolism in patients with acute myocardial infarction and no previous diagnosis of diabetes mellitus: a prospective study.Lancet.2002;359:2140–2144. , , , et al.
- Mechanism by which hyperglycemia plays a role in the setting of acute cardiovascular illness.Rev Cardiovasc Med.2006;7(Suppl 2):S35–S43. .
- Stress hyperglycaemia is an independent predictor of left ventricular remodelling after first anterior myocardial infarction in non‐diabetic patients.Eur Heart J.2007;28:546–552. , , , , , , et al.
- Implications and treatment of acute hyperglycemia in the setting of acute myocardial infarction.Circulation.2007;115:e436–e439. , .
- Insulin infusion in acute illness.J Clin Invest.2005;115:2069–2072. , , , , .
- Intensive insulin therapy exerts antiinflammatory effects in critically ill patients and counteracts the adverse effect of low mannose‐gind lectin levels.J Clin Endocrinol Metab.2003;88:1082–1088. , , , , .
- Protection of hepatocyte mitochondrial ultrastructure and function by strict blood glucose control with insulin in critically ill patients.Lancet.2005;365:53–59. , , , , , .
- Intensive insulin therapy protects the endothelium of critically ill patients.J Clin Invest.2005;115:2277–2286. , , , et al.
- The association between hyperglycaemia on admission and 180‐day mortality in acute myocardial infarction patients with and without diabetes.Diabet Med.2005;22:1321–1325. , , , .
- Admission glucose and mortality in elderly patients hospitalized with acute myocardial infarction: implications for patients with and without recognized diabetes.Circulation.2005;111:3078–3086. , , , et al.
- Glycometabolic state at admission: important risk marker of mortality in conventionally treated patients with diabetes mellitus and acute myocardial infarction: long‐term results from the Diabetes and Insulin‐Glucose Infusion in Acute Myocardial Infarction (DIGAMI) study.Circulation.1999;99:2626–2632. , , , .
- Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773–778. , , , .
- How important is hyperglycemia during acute brain infarction?Neurologist.2004;10:195–200. , , .
- Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:2426–2432. , , , , .
- Perioperative glycemic control and the risk of infectious complications in a cohort of adults with diabetes.Diabetes Care.1999;22:1408–1414. , , , .
- Early postoperative glucose control predicts nosocomial infection rate in diabetic patients.JPEN J Parenter Enteral Nutr.1998;22:77–81. , , , et al.
- The relation between hyperglycemia and outcomes in 2,471 patients admitted to the hospital with community‐acquired pneumonia.Diabetes Care.2005;28:810–815. , , , , , .
- Early peri‐operative glycaemic control and allograft rejection in patients with diabetes mellitus: a pilot study.Transplantation.2001;72:1321–1324. , , , , .
- Relation between the duration of remission and hyperglycemia during induction chemotherapy for acute lymphocytic leukemia with a hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone/methotrexate‐cytarabine regimen.Cancer.2004;100:1179–1185. , , , et al.
- Effect of fasting glucose levels on mortality rate in patients with and without diabetes mellitus and coronary artery disease undergoing percutaneous coronary intervention.Am Heart J.2003;146:351–358. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland diabetic project.Endocr Pract.2004;10(Suppl 2):21–33. , , .
- Intraoperative hyperglycemia and perioperative outcomes in cardiac surgery patients.Mayo Clin Proc.2005;80:862–866. , , , et al.
- The association of diabetes and glucose control with surgical‐site infections among cardiothoracic surgery patients.Infect Control Hosp Epidemiol.2001;22:607–612. , , , , .
- Glucose control lowers the risk of wound infection in diabetics after open heart operations.Ann Thorac Surg.1997;63:356–361. , , .
- The Portland Protocol. Available at: http://www.providence.org/oregon/grograms_and_services/heart/portlandprotocol/. Accessed September2007.
- Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:992–1000. .
- Intensive insulin therapy in mixed medical/surgical intensive care units: benefit versus harm.Diabetes.2006;55:3151–3159. , , , et al.
- Tight blood glucose control with insulin in the ICU: facts and controversies.Chest.2007;132:268–278. , , .
- Reduction of nosocomial infections in the surgical intensive‐care unit by strict glycemic control.Endocr Pract.2004;10(Suppl 2):46–52. , .
- Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358:125–139. , , , , , , et al.
- Current controversies around tight glucose control in critically ill patients.Curr Opin Clin Nutr Metab Care.2007;10:206–209. , .
- Designing and implementing insulin infusion protocols and order sets.J Hosp Med.2008;3(5):S42–S54. , , , .
- Randomized study of basal‐bolus insulin therapy in the inpatient management of patients with type 2 diabetes (RABBIT 2 trial).Diabetes Care.2007;30:2181–2186. , , , , , , et al.
- Society of Hospital Medicine. Glycemic control resource room. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/GlycemicControl.cfm. Accessed November2007.
- Society of Hospital Medicine. Workbook for improvement: improving glycemic control, preventing hypoglycemia, and optimizing care of the inpatient with hyperglycemia and diabetes. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/pdf/GC_Workbook.pdf. Accessed November2007.
- American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10:77–82. , , , et al.
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm.J Hosp Med.2008. In press. , , , , .
- American Association of Clinical Endocrinologists Inpatient Glycemic Control Resource Center.2007. Available at: http://resources.aace.com/index.asp. Accessed December 2007.
- American Heart Association. Get With the Guidelines. Available at: http://www.americanheart.org/getwiththeguidelines. Accessed November2007.
- Joint Commission. Disease Specific‐Care Certification. Available at:http://www.jointcommission.org/CertificationPrograms. Accessed November2007.
- The Joint Commission Disease‐Specific Certification Program. Range JE. Oncology issues. July/August2007:40–41.
- Anonymous.The Diabetes Control and Complications Trial Research Group (DCCT). The effect of intensive treatment of diabetes on the development and progression of long‐term complications in insulin‐dependent diabetes mellitus.N Engl J Med.1993;329:977–986.
- Intensive blood‐glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type, 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.Lancet.1998;352:837–853.
- Intensified multifactorial intervention in patients with type 2 diabetes mellitus and microalbuminuria: the Steno type 2 randomised study.Lancet.1999;353:617–622. , , , .
- Utility of HbA1c levels for diabetes case finding in hospitalized patients with hyperglycemia.Diabetes Care.2003;26:1064–1068. , , , et al.
- Eliminating inpatient sliding‐scale insulin: a reeducation project with medical house staff.Diabetes Care.2005;28:1008–1011. , , , .
- Advanced carbohydrate counting. In:Practical Carbohydrate Counting: A How‐to‐Teach Guide for Health Professionals.Alexandria, VA:American Diabetes Association;2001:26–28. , .
- The evidence for the effectiveness of medical nutrition therapy in diabetes management.Diabetes Care.2002;25:608–613. , , , , .
- Inpatient management of diabetes and hyperglycemia: implications for nutrition practice and the food and nutrition professional.J Am Diet Assoc.2007;107:105–111. , , , et al.
- The transition from insulin infusions to long‐term diabetes therapy: the argument for insulin analogs.Semin Thorac Cardiovasc Surg.2006;18:366–378. .
- Transitions paper.J Hosp Med.2008. .
- Inpatient management of diabetes and hyperglycemia among general medicine patients at a large teaching hospital.J Hosp Med.2006;1:145–150. , , , , .
- Clinical inertia.Ann Intern Med.2001;135:825–834. , , , et al.
- Diabetes care in hospitalized noncritically ill patients: more evidence for clinical inertia and negative therapeutic momentum.J Hosp Med.2007;2:203–211. , , , et al.
- University HealthSystem Consortium.Glycemic control 2005 findings and conclusions. Presented at: Glycemic Control 2005 Knowledge Transfer Meeting; 2005 August 19,2005; Chicago, IL.
- Glycemic chaos (not glycemic control) still the rule for inpatient care: how do we stop the insanity?J Hosp Med.2006;1:141–144. , .
- Management of diabetes mellitus in hospitalized patients: efficiency and effectiveness of sliding‐scale insulin therapy.Pharmacotherapy.2006;26:1421–1432. , , , , .
- Hypoglycemia in hospitalized patients treated with antihyperglycemic agents.J Hosp Med.2007;2:234–240. , , , , , .
- Hypoglycemia in hospitalized patients.N Engl J Med.1986;315:1245–1250. , , .
- Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96–101. , , , et al.
- Association between hyper‐ and hypoglycaemia and 2 year all‐cause mortality risk in diabetic patients with acute coronary events.Eur Heart J.2005;26:1255–1261. , , , .
- U‐shaped relationship of blood glucose with adverse outcomes among patients with ST‐segment elevation myocardial infarction.J Am Coll Cardiol.2005;46:178–180. , , , et al.
- An unexpected inverse relationship between HbA1c levels and mortality in patients with diabetes and advanced systolic heart failure.Am Heart J.2006;151:91. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Hypoglycemia in diabetes.Diabetes Care.2003;26:1902–1912. , , .
- Hypoglycemia and cardiac arrest in a critically ill patient on strict glycemic control.Anesth Analg.2006;102:549–551. , , .
- Tight glycemic control in critically injured trauma patients.Ann Surg.2007;246:605–610; discussion 10–12. , , , , , .
- Severe hypoglycemia in critically ill patients: risk factors and outcomes.Crit Care Med.2007;35:2262–2267. , .
- Provider response to insulin‐induced hypoglycemia in hospitalized patients.J Hosp Med.2007;2:258–260. , , , .
- Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(Suppl 3):43–48. , .
- Impact of endocrine and diabetes team consultation on hospital length of stay for patients with diabetes.Am J Med.1995;99:22–28. , , , .
- American College of Endocrinology and American Diabetes Association Consensus Statement on Inpatient Diabetes and Glycemic Control: A call to action.Diabetes Care.2006;29:1955–1962.
- Standards of medical care in diabetes‐‐2008.Diabetes Care.2008;31(Suppl 1):S12–S54.
- Prevalence of diabetes and impaired fasting glucose in adults in the U.S. population: National Health And Nutrition Examination Survey 1999–2002.Diabetes Care.2006;29:1263–1268. , , , et al.
- Centers for Disease Control and Prevention.National Diabetes Fact Sheet: General Information and National Estimates on Diabetes in the United States, 2005.Atlanta, GA:U.S. Department of Health and Human Services, Centers for Disease Control and Prevention,2005. Available at: http://www.cdc.gov/diabetes/pubs/factsheet05.htm. Accessed September 2007.
- Economic costs of diabetes in the US in 2002.Diabetes Care.2003;26:917–932. , , .
- Glycemic control and sliding scale insulin use in medical inpatients with diabetes mellitus.Arch Intern Med.1997;157:545–552. , , .
- Inpatient management of diabetes mellitus.Am J Med.2002;113:317–323. , , .
- Management of diabetes and hyperglycemia in hospitals.Diabetes Care.2004;27:553–591. , , , et al.
- Intensive insulin therapy in the medical ICU.N Engl J Med.2006;354:449–461. , , , et al.
- Intensive insulin therapy in critically ill patients.N Engl J Med.2001;345:1359–1367. , , , et al.
- Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.Mayo Clin Proc.2003;78:1471–1478. .
- Unrecognized diabetes among hospitalized patients.Diabetes Care.1998;21:246–249. , , , , .
- Hyperglycemia: an independent marker of in‐hospital mortality in patients with undiagnosed diabetes.J Clin Endocrinol Metab.2002;87:978–982. , , , , , .
- United States Department of Health and Human Services Agency for Healthcare Research and Quality.2007. Available at: http://hcupnet.ahrq.gov. Accessed December 2007.
- Glucose metabolism in patients with acute myocardial infarction and no previous diagnosis of diabetes mellitus: a prospective study.Lancet.2002;359:2140–2144. , , , et al.
- Mechanism by which hyperglycemia plays a role in the setting of acute cardiovascular illness.Rev Cardiovasc Med.2006;7(Suppl 2):S35–S43. .
- Stress hyperglycaemia is an independent predictor of left ventricular remodelling after first anterior myocardial infarction in non‐diabetic patients.Eur Heart J.2007;28:546–552. , , , , , , et al.
- Implications and treatment of acute hyperglycemia in the setting of acute myocardial infarction.Circulation.2007;115:e436–e439. , .
- Insulin infusion in acute illness.J Clin Invest.2005;115:2069–2072. , , , , .
- Intensive insulin therapy exerts antiinflammatory effects in critically ill patients and counteracts the adverse effect of low mannose‐gind lectin levels.J Clin Endocrinol Metab.2003;88:1082–1088. , , , , .
- Protection of hepatocyte mitochondrial ultrastructure and function by strict blood glucose control with insulin in critically ill patients.Lancet.2005;365:53–59. , , , , , .
- Intensive insulin therapy protects the endothelium of critically ill patients.J Clin Invest.2005;115:2277–2286. , , , et al.
- The association between hyperglycaemia on admission and 180‐day mortality in acute myocardial infarction patients with and without diabetes.Diabet Med.2005;22:1321–1325. , , , .
- Admission glucose and mortality in elderly patients hospitalized with acute myocardial infarction: implications for patients with and without recognized diabetes.Circulation.2005;111:3078–3086. , , , et al.
- Glycometabolic state at admission: important risk marker of mortality in conventionally treated patients with diabetes mellitus and acute myocardial infarction: long‐term results from the Diabetes and Insulin‐Glucose Infusion in Acute Myocardial Infarction (DIGAMI) study.Circulation.1999;99:2626–2632. , , , .
- Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview.Lancet.2000;355:773–778. , , , .
- How important is hyperglycemia during acute brain infarction?Neurologist.2004;10:195–200. , , .
- Stress hyperglycemia and prognosis of stroke in nondiabetic and diabetic patients: a systematic overview.Stroke.2001;32:2426–2432. , , , , .
- Perioperative glycemic control and the risk of infectious complications in a cohort of adults with diabetes.Diabetes Care.1999;22:1408–1414. , , , .
- Early postoperative glucose control predicts nosocomial infection rate in diabetic patients.JPEN J Parenter Enteral Nutr.1998;22:77–81. , , , et al.
- The relation between hyperglycemia and outcomes in 2,471 patients admitted to the hospital with community‐acquired pneumonia.Diabetes Care.2005;28:810–815. , , , , , .
- Early peri‐operative glycaemic control and allograft rejection in patients with diabetes mellitus: a pilot study.Transplantation.2001;72:1321–1324. , , , , .
- Relation between the duration of remission and hyperglycemia during induction chemotherapy for acute lymphocytic leukemia with a hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone/methotrexate‐cytarabine regimen.Cancer.2004;100:1179–1185. , , , et al.
- Effect of fasting glucose levels on mortality rate in patients with and without diabetes mellitus and coronary artery disease undergoing percutaneous coronary intervention.Am Heart J.2003;146:351–358. , , , et al.
- Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland diabetic project.Endocr Pract.2004;10(Suppl 2):21–33. , , .
- Intraoperative hyperglycemia and perioperative outcomes in cardiac surgery patients.Mayo Clin Proc.2005;80:862–866. , , , et al.
- The association of diabetes and glucose control with surgical‐site infections among cardiothoracic surgery patients.Infect Control Hosp Epidemiol.2001;22:607–612. , , , , .
- Glucose control lowers the risk of wound infection in diabetics after open heart operations.Ann Thorac Surg.1997;63:356–361. , , .
- The Portland Protocol. Available at: http://www.providence.org/oregon/grograms_and_services/heart/portlandprotocol/. Accessed September2007.
- Effect of an intensive glucose management protocol on the mortality of critically ill adult patients.Mayo Clin Proc.2004;79:992–1000. .
- Intensive insulin therapy in mixed medical/surgical intensive care units: benefit versus harm.Diabetes.2006;55:3151–3159. , , , et al.
- Tight blood glucose control with insulin in the ICU: facts and controversies.Chest.2007;132:268–278. , , .
- Reduction of nosocomial infections in the surgical intensive‐care unit by strict glycemic control.Endocr Pract.2004;10(Suppl 2):46–52. , .
- Intensive insulin therapy and pentastarch resuscitation in severe sepsis.N Engl J Med.2008;358:125–139. , , , , , , et al.
- Current controversies around tight glucose control in critically ill patients.Curr Opin Clin Nutr Metab Care.2007;10:206–209. , .
- Designing and implementing insulin infusion protocols and order sets.J Hosp Med.2008;3(5):S42–S54. , , , .
- Randomized study of basal‐bolus insulin therapy in the inpatient management of patients with type 2 diabetes (RABBIT 2 trial).Diabetes Care.2007;30:2181–2186. , , , , , , et al.
- Society of Hospital Medicine. Glycemic control resource room. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/GlycemicControl.cfm. Accessed November2007.
- Society of Hospital Medicine. Workbook for improvement: improving glycemic control, preventing hypoglycemia, and optimizing care of the inpatient with hyperglycemia and diabetes. Available at: http://www.hospitalmedicine.org/ResourceRoomRedesign/pdf/GC_Workbook.pdf. Accessed November2007.
- American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10:77–82. , , , et al.
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm.J Hosp Med.2008. In press. , , , , .
- American Association of Clinical Endocrinologists Inpatient Glycemic Control Resource Center.2007. Available at: http://resources.aace.com/index.asp. Accessed December 2007.
- American Heart Association. Get With the Guidelines. Available at: http://www.americanheart.org/getwiththeguidelines. Accessed November2007.
- Joint Commission. Disease Specific‐Care Certification. Available at:http://www.jointcommission.org/CertificationPrograms. Accessed November2007.
- The Joint Commission Disease‐Specific Certification Program. Range JE. Oncology issues. July/August2007:40–41.
- Anonymous.The Diabetes Control and Complications Trial Research Group (DCCT). The effect of intensive treatment of diabetes on the development and progression of long‐term complications in insulin‐dependent diabetes mellitus.N Engl J Med.1993;329:977–986.
- Intensive blood‐glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type, 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group.Lancet.1998;352:837–853.
- Intensified multifactorial intervention in patients with type 2 diabetes mellitus and microalbuminuria: the Steno type 2 randomised study.Lancet.1999;353:617–622. , , , .
- Utility of HbA1c levels for diabetes case finding in hospitalized patients with hyperglycemia.Diabetes Care.2003;26:1064–1068. , , , et al.
- Eliminating inpatient sliding‐scale insulin: a reeducation project with medical house staff.Diabetes Care.2005;28:1008–1011. , , , .
- Advanced carbohydrate counting. In:Practical Carbohydrate Counting: A How‐to‐Teach Guide for Health Professionals.Alexandria, VA:American Diabetes Association;2001:26–28. , .
- The evidence for the effectiveness of medical nutrition therapy in diabetes management.Diabetes Care.2002;25:608–613. , , , , .
- Inpatient management of diabetes and hyperglycemia: implications for nutrition practice and the food and nutrition professional.J Am Diet Assoc.2007;107:105–111. , , , et al.
- The transition from insulin infusions to long‐term diabetes therapy: the argument for insulin analogs.Semin Thorac Cardiovasc Surg.2006;18:366–378. .
- Transitions paper.J Hosp Med.2008. .
- Inpatient management of diabetes and hyperglycemia among general medicine patients at a large teaching hospital.J Hosp Med.2006;1:145–150. , , , , .
- Clinical inertia.Ann Intern Med.2001;135:825–834. , , , et al.
- Diabetes care in hospitalized noncritically ill patients: more evidence for clinical inertia and negative therapeutic momentum.J Hosp Med.2007;2:203–211. , , , et al.
- University HealthSystem Consortium.Glycemic control 2005 findings and conclusions. Presented at: Glycemic Control 2005 Knowledge Transfer Meeting; 2005 August 19,2005; Chicago, IL.
- Glycemic chaos (not glycemic control) still the rule for inpatient care: how do we stop the insanity?J Hosp Med.2006;1:141–144. , .
- Management of diabetes mellitus in hospitalized patients: efficiency and effectiveness of sliding‐scale insulin therapy.Pharmacotherapy.2006;26:1421–1432. , , , , .
- Hypoglycemia in hospitalized patients treated with antihyperglycemic agents.J Hosp Med.2007;2:234–240. , , , , , .
- Hypoglycemia in hospitalized patients.N Engl J Med.1986;315:1245–1250. , , .
- Predisposing factors for hypoglycemia in the intensive care unit.Crit Care Med.2006;34:96–101. , , , et al.
- Association between hyper‐ and hypoglycaemia and 2 year all‐cause mortality risk in diabetic patients with acute coronary events.Eur Heart J.2005;26:1255–1261. , , , .
- U‐shaped relationship of blood glucose with adverse outcomes among patients with ST‐segment elevation myocardial infarction.J Am Coll Cardiol.2005;46:178–180. , , , et al.
- An unexpected inverse relationship between HbA1c levels and mortality in patients with diabetes and advanced systolic heart failure.Am Heart J.2006;151:91. , , .
- Glucometrics in patients hospitalized with acute myocardial infarction: defining the optimal outcomes‐based measure of risk.Circulation.2008;117:1018–1027. , , , et al.
- Hypoglycemia in diabetes.Diabetes Care.2003;26:1902–1912. , , .
- Hypoglycemia and cardiac arrest in a critically ill patient on strict glycemic control.Anesth Analg.2006;102:549–551. , , .
- Tight glycemic control in critically injured trauma patients.Ann Surg.2007;246:605–610; discussion 10–12. , , , , , .
- Severe hypoglycemia in critically ill patients: risk factors and outcomes.Crit Care Med.2007;35:2262–2267. , .
- Provider response to insulin‐induced hypoglycemia in hospitalized patients.J Hosp Med.2007;2:258–260. , , , .
- Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(Suppl 3):43–48. , .
- Impact of endocrine and diabetes team consultation on hospital length of stay for patients with diabetes.Am J Med.1995;99:22–28. , , , .