Affiliations
Division of Metabolism, Endocrinology and Nutrition, Harborview Medical Center, University of Washington, Seattle, Washington
Given name(s)
Astrid B.
Family name
Schreuder
Degrees
PhD

Thromboembolism Prophylaxis in Liver Disease

Article Type
Changed
Mon, 01/02/2017 - 19:34
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A descriptive case series of patients with end‐stage liver disease hospitalized with variceal bleeding who received pharmacologic venous thromboembolism prophylaxis

Venous thromboembolism (VTE) is a major cause of morbidity and mortality in hospitalized patients.13 Major efforts are underway to increase appropriate VTE prophylaxis (VTEP)4 and adherence to VTEP guidelines are increasingly used as a quality of care measure. National 2008 VTEP guidelines suggest that all medical patients ill enough to require hospitalization, particularly those requiring admission to the Intensive Care Unit (ICU), have at least a moderate risk of developing VTE and prophylaxis is recommended.4 Hospitalized patients with end‐stage liver disease (ESLD), despite their coagulopathy, are known to be at risk for VTE48 and may be VTEP candidates.

Based on available literature, it is unknown whether pharmacologic VTEP should be utilized in acutely ill, hospitalized patients with ESLD, particularly in those admitted with variceal bleeding. These patients are at high risk for rebleeding, with the highest risk in the first 5 days.9 Early rebleeding, defined as recurrent bleeding within 6 weeks of initial bleed, declined from 47% in the 1980s to 13% by 2000 because of increased early endoscopic intervention and use of medications to prevent rebleeding.911 In multicenter cohort studies, D'Amico and De Franchis12 reported that 13% of patients with variceal bleeding had uncontrolled bleeding, rebleeding, or death within 5 days of admission while Bahmba et al.13 reported a 16% rate of rebleeding within 5 days. We are unaware of prior reports regarding the safety of VTEP in this high‐risk group of patients.

Objective

We sought to describe rebleeding in a series of 22 patients with ESLD admitted with variceal bleeding who received pharmacologic VTEP.

Methods

We identified all patients 18 years and older with upper gastrointestinal bleeding admitted to Harborview Medical Center, a 400‐bed urban county teaching hospital in Seattle, Washington, between January 1, 2003 and December 31, 2005 (Figure 1), just prior to medical center‐wide implementation of a VTEP guideline. Potential cases were identified using administrative data based on 8 discharge diagnoses (Supporting Information Appendix 1) and 10 procedure codes (Supporting Information Appendix 2).14 Inpatient pharmacy data indicating continuous octreotide infusion were used to refine the sample. At our institution, it is a standard of care to initiate octreotide in patients admitted with variceal bleeding. We excluded patients who did not have ESLD (defined as evidence of cirrhosis and associated complications including but not limited to ascites, encephalopathy, variceal bleeding, portal hypertension) documented in their problem list or past medical history and those with no variceal bleeding based on medical record review. We identified cases receiving pharmacologic VTEP, either subcutaneous unfractionated heparin (UFH) or low molecular weight heparin (LMWH), during hospitalization from pharmacy records.

Figure 1
Patient identification: Patients with end‐stage liver disease (ESLD) admitted with variceal bleed who received pharmacologic venous thromboembolism prophylaxis. EGD, esophagogastroduodenoscopy; ICD‐9, International Classification of Disease, Version 9 diagnosis codes; CPT, common procedural terminology (CPT) procedure codes; VTEP, venous thromboembolism prophylaxis.

We obtained demographic and clinical data from administrative billing systems, electronic and paper medical records, and inpatient pharmacy databases and verified transfusion data from the Puget Sound Blood Center. We abstracted esophagogastroduodenoscopy (EGD) findings indicating high risk of rebleeding including variceal grade and stigmata of recent bleeding such as red spots or wales.15, 16 Data were abstracted by the first 3 authors (AS, MS, KJ) and reviewed again by 2 authors (AS, KJ) blinded to the others' abstractions.

We calculated Model for ESLD (MELD) scores on admission. These scores correlate with 3 month mortality in ESLD.17 We tabulated 5 factors shown in some studies to predict bleeding including high International Normalized Ratio (INR) (>1.5), low hematocrit (<25%), low platelet count (<100,000 per microliter), active bleeding at EGD, and transfusion of four or more units of red cells within 24 hours of admission.1013

We defined rebleeding as a decrease in hematocrit of greater than 5 percentage points compared with postresuscitation hematocrit, transfusion of additional red cells more than 48 hours after initial resuscitation, repeat unscheduled EGD, or return to the ICU for therapies related to rebleeding.18 The University of Washington Human Subjects Board approved this study.

Results

Of 224 patients initially identified, 36 received pharmacologic VTEP. We excluded 14 who did not have ESLD (n = 1) or did not have a variceal bleed (n = 13). The remaining 22 patients form the sample described in Figure 1.

The median age of patients was 52 years (range 42‐85) and 77% were men (Table 1). Twenty‐one of 22 patients (95%) were initially admitted to the ICU; median length of stay was 8 days (range 4‐30). Median MELD score on admission was 15 (range 825). On EGD, the number of variceal columns ranged from 1 to 4; 17 patients (77%) had at least 3. A total of 15 patients (68%) had stigmata of recent bleeding and 16 (72%) underwent banding (range 16 bands). All patients had at least 1 bleeding risk factor (Table 1) of which the most common factors observed were initial transfusion of 4 or more units of red cells (50%, n = 11), INR > 1.5 (45%, n = 10), and hematocrit < 25% (45%, n = 10).

Characteristics of Hospitalized Patients with End‐Stage Liver Disease and Variceal Bleeding Who Received Pharmacologic Thromboembolism Prophylaxis (n = 22)
Parameter Range Median Value/% Interquartile Range Mean Standard Deviation
  • Abbreviations: EGD, esophagogastroduodenoscopy; ICU, intesive care unit; INR, International Normalized Ratio; MELD, Model for End‐Stage Liver Disease.

  • Risk factors for rebleeding included high INR (>1.5), low hematocrit (<25%), low platelet count (<100,000/L), active bleeding at EGD, and initial transfusion of four or more units of red cells.811

Age (years) 4285 52 4758 53 9
Sex (men) 17 77%
MELD scores 825 14.5 1120 15 5
Initial ICU admission 21 95%
Hospital length of stay (days) 430 8 9.9 6.7
Initial INR 1.12.4 1.5 1.42.0 1.7 0.4
Initial hematocrit (%) 1444 26 2232 27 8
Initial platelets (thousand/L) 43494 131 83159 147 98
EGD results
Grade 1 3 14%
Grade 2 6 27%
Grade 3 12 55%
Grade 4 1 5%
Stigmata of recent bleeding 15 68%
Number of risk factors for rebleeding*
0 0 0%
1 9 41%
2 7 32%
3 5 23%
4 1 4%
Initial transfusion red blood cells
None 2 9%
13 units 9 41%
4+ units 11 50%
Initial transfusion frozen plasma
None 10 45%
14 units 3 14%
58 units 6 27%
9+ units 4 18%
Initial transfusion platelets
None 13 59%
14 units 4 18%
5+ units 5 23%

A total of 12 patients (55%) received 5000 units of UFH every 8 hours, 8 (36%) received 5000 units UFH every 12 hours, and 2 (9%) received LMWH. VTEP was initiated as early as day of admission and as late as day 19. Median VTEP start date was hospital day 4. Median duration of of VTEP was 5 days.

Only 1 patient (4.5%) rebled after VTEP initiation. The patient received UFH every 8 hours starting on hospital day 6, and rebleeding occurred on day 9. Repeat EGD showed ulcers at banding sites. The patient was restarted on VTEP on hospital day 13 without recurrence of rebleeding. This patient had a MELD score of 24, initial INR >2, hematocrit <25%, had grade 3 varices and stigmata of recent bleeding on EGD, and received 4 units of packed red cells. These values are similar to those of the cohort as a whole (Table 1). This patient also was diagnosed with DVT while receiving VTEP on hospital day 15. This patient's coagulopathy was in the setting of terminal illness; the patient expired on hospital day 25.

One additional patient rebled prior to VTEP initiation on day 3 with repeat EGD showing a bleeding varix. This patient was nevertheless started on VTEP 4 days after rebleeding. Despite use of VTEP, this patient was diagnosed with DVT on hospital day 9 (and may well have had the DVT at the time of VTEP initiation). The patient was transitioned to therapeutic dose heparin which was tolerated without recurrence of rebleeding.

There were no other confirmed cases of DVT in this series. One additional patient underwent angiogram that showed no pulmonary embolism; 2 other patients underwent lower extremity ultrasounds that were negative for DVT.

Discussion

At our medical center, only a few inpatients with ESLD admitted with variceal bleed received VTEP. These patients were seemingly at high risk for bleeding and rebleeding given high MELD scores, variceal bleeding, and presence of at least one clinical factor suggesting bleeding risk, and in several cases 3 or more such factors.13, 18 Despite this, only 1 patient rebled while receiving VTEP. We captured rebleeding rates only during the index hospitalization. We therefore may underestimate early rebleeding rates.1013 Nevertheless, our inpatient data included complete coverage of the earliest period after the index bleeds and the period during which patients were exposed to VTEP, which should be the time of highest rebleeding risk related to VTEP exposure. Interestingly the patient who rebled while on VTEP was also diagnosed with VTE while on VTEP. Two patients (9%) in our sample were diagnosed with VTE.

This case series is limited by its small sample size, retrospective nature, single center observation, and perhaps especially by possible selection bias. We were unable to specifically quantify rebleeding risk. Several authors have identified individual factors associated with rebleeding,1013 these were tabulated for patients in this case series (Table 1) and all patients had at least 1 of these factors. Concurrent infection and hepatic vein pressure gradient have been shown to predict rebleeding;9, 19 we were unable to identify these factors in our data.

There was considerable variability in this case series in timing of VTEP initiation relative to initial bleed. We were unable to characterize provider or patient characteristics that may have influenced the decision to initiate VTEP and timing. The sample size was also too small to comment upon factors associated with choice of UFH versus LMWH and any potential differences in rebleeding risk between the 2. We also did not look at outcomes postindex hospitalization so we can not comment on the extended risk of rebleeding with VTEP after discharge. However, the risk of rebleeding is highest within the first 96 hours13 and all patients in this series were hospitalized at least 4 days. Nonetheless, we captured all patients with ESLD and variceal bleeding exposed to VTEP at a large center over a three‐year period and found rebleeding rates less than what might be expected.

Conclusions

Our observations suggest that some inpatients with ESLD and variceal bleeding may tolerate pharmacologic VTEP. In this small group of patients, VTEP was associated with an unexpectedly low incidence of rebleeding. While this case series does not support broad use of VTEP in this population, the lower‐than‐expected rates of rebleeding suggest that further study of the safety and effectiveness of pharmacologic VTEP in inpatient populations with ESLD may be warranted, particularly given the recommendations of recent national VTE prophylaxis guidelines.4

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References
  1. Aujesky D,Roy PM,Le Manach CP, et al.Validation of a model to predict adverse outcomes in patients with pulmonary embolism.Eur Heart J.2006;27(4):476481.
  2. White RH.The epidemiology of venous thromboembolism.Circulation.2003;107(23 Suppl 1):I4I8.
  3. Anderson FA,Wheeler HB,Goldberg RJ,Hosmer DW,Forcier A.The prevalence of risk factors for venous thromboembolism among hospital patients.Arch Intern Med.1992;152(8):16601664.
  4. Geerts WH,Bergqvist D,Pineo GF, et al.Prevention of venous thromboembolism: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines. 8th Edition.Chest.2008;133(6 Suppl):381S453S.
  5. Northup PG,McMahon MM,Ruhl AP, et al.Coagulopathy does not fully protect hospitalized cirrhosis patients from peripheral venous thromboembolism.Am J Gastroenterol.2006;101(7):15241528; quiz 680.
  6. Amitrano L,Guardascione MA,Brancaccio V,Balzano A.Coagulation disorders in liver disease.Semin Liver Dis.2002;22(1):8396.
  7. Gulley D,Teal E,Suvannasankha A,Chalasani N,Liangpunsakul S.Deep vein thrombosis and pulmonary embolism in cirrhosis patients.Dig Dis Sci.2008;53(11):30123017.
  8. Sogaard KK,Horvath‐Puho E,Gronbaek H,Jepsen P,Vilstrup H,Sorensen HT.Risk of venous thromboembolism in patients with liver disease: a nationwide population‐based case‐control study.Am J Gastroenterol.2009;104(1):96101.
  9. de Franchis R,Dell'Era A.Non‐invasive diagnosis of cirrhosis and the natural history of its complications.Best Pract Res Clin Gastroenterol.2007;21(1):318.
  10. Chalasani N,Kahi C,Francois F,et al.Improved patient survival after acute variceal bleeding: a multicenter, cohort study.Am J Gastroenterol.2003;98(3):653659.
  11. Carbonell N,Pauwels A,Serfaty L,Fourdan O,Levy VG,Poupon R.Improved survival after variceal bleeding in patients with cirrhosis over the past two decades.Hepatology.2004;40(3):652659.
  12. D'Amico G,De Franchis R.Upper digestive bleeding in cirrhosis. Post‐therapeutic outcome and prognostic indicators.Hepatology.2003;38(3):599612.
  13. Bambha K,Kim WR,Pedersen R,Bida JP,Kremers WK,Kamath PS.Predictors of early re‐bleeding and mortality after acute variceal haemorrhage in patients with cirrhosis.Gut.2008;57(6):814820.
  14. Smith MW,Jarma KM,Schleyer AM,Schreuder AB,Goss R,Onstad S.Use of hospital administrative data to assess quality improvement initiatives.J Gen Intern Med.2007;22(Supplement).
  15. Jalan R,Hayes PC.UK guidelines on the management of variceal haemorrhage in cirrhotic patients.Gut.2000,year="2000"2000;46(90003):iii115.
  16. Siringo S,McCormick PA,Mistry P,Kaye G,McIntyre N,Burroughs AK.Prognostic significance of the white nipple sign in variceal bleeding.Gastrointest Endosc.1991;37(1):5155.
  17. Kamath PS,Wiesner RH,Malinchoc M, et al.A model to predict survival in patients with end‐stage liver disease.Hepatology.2001;33(2):464470.
  18. de Franchis R.Evolving consensus in portal hypertension. Report of the Baveno IV consensus workshop on methodology of diagnosis and therapy in portal hypertension.J Hepatol.2005;43(1):167176.
  19. Hou MC,Lin HC,Liu TT, et al.Antibiotic prophylaxis after endoscopic therapy prevents rebleeding in acute variceal hemorrhage: a randomized trial.Hepatology.2004;39(3):746753.
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Issue
Journal of Hospital Medicine - 6(3)
Publications
Page Number
151-155
Legacy Keywords
liver disease, thromboembolism prophylaxis, variceal bleeding
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Article PDF

Venous thromboembolism (VTE) is a major cause of morbidity and mortality in hospitalized patients.13 Major efforts are underway to increase appropriate VTE prophylaxis (VTEP)4 and adherence to VTEP guidelines are increasingly used as a quality of care measure. National 2008 VTEP guidelines suggest that all medical patients ill enough to require hospitalization, particularly those requiring admission to the Intensive Care Unit (ICU), have at least a moderate risk of developing VTE and prophylaxis is recommended.4 Hospitalized patients with end‐stage liver disease (ESLD), despite their coagulopathy, are known to be at risk for VTE48 and may be VTEP candidates.

Based on available literature, it is unknown whether pharmacologic VTEP should be utilized in acutely ill, hospitalized patients with ESLD, particularly in those admitted with variceal bleeding. These patients are at high risk for rebleeding, with the highest risk in the first 5 days.9 Early rebleeding, defined as recurrent bleeding within 6 weeks of initial bleed, declined from 47% in the 1980s to 13% by 2000 because of increased early endoscopic intervention and use of medications to prevent rebleeding.911 In multicenter cohort studies, D'Amico and De Franchis12 reported that 13% of patients with variceal bleeding had uncontrolled bleeding, rebleeding, or death within 5 days of admission while Bahmba et al.13 reported a 16% rate of rebleeding within 5 days. We are unaware of prior reports regarding the safety of VTEP in this high‐risk group of patients.

Objective

We sought to describe rebleeding in a series of 22 patients with ESLD admitted with variceal bleeding who received pharmacologic VTEP.

Methods

We identified all patients 18 years and older with upper gastrointestinal bleeding admitted to Harborview Medical Center, a 400‐bed urban county teaching hospital in Seattle, Washington, between January 1, 2003 and December 31, 2005 (Figure 1), just prior to medical center‐wide implementation of a VTEP guideline. Potential cases were identified using administrative data based on 8 discharge diagnoses (Supporting Information Appendix 1) and 10 procedure codes (Supporting Information Appendix 2).14 Inpatient pharmacy data indicating continuous octreotide infusion were used to refine the sample. At our institution, it is a standard of care to initiate octreotide in patients admitted with variceal bleeding. We excluded patients who did not have ESLD (defined as evidence of cirrhosis and associated complications including but not limited to ascites, encephalopathy, variceal bleeding, portal hypertension) documented in their problem list or past medical history and those with no variceal bleeding based on medical record review. We identified cases receiving pharmacologic VTEP, either subcutaneous unfractionated heparin (UFH) or low molecular weight heparin (LMWH), during hospitalization from pharmacy records.

Figure 1
Patient identification: Patients with end‐stage liver disease (ESLD) admitted with variceal bleed who received pharmacologic venous thromboembolism prophylaxis. EGD, esophagogastroduodenoscopy; ICD‐9, International Classification of Disease, Version 9 diagnosis codes; CPT, common procedural terminology (CPT) procedure codes; VTEP, venous thromboembolism prophylaxis.

We obtained demographic and clinical data from administrative billing systems, electronic and paper medical records, and inpatient pharmacy databases and verified transfusion data from the Puget Sound Blood Center. We abstracted esophagogastroduodenoscopy (EGD) findings indicating high risk of rebleeding including variceal grade and stigmata of recent bleeding such as red spots or wales.15, 16 Data were abstracted by the first 3 authors (AS, MS, KJ) and reviewed again by 2 authors (AS, KJ) blinded to the others' abstractions.

We calculated Model for ESLD (MELD) scores on admission. These scores correlate with 3 month mortality in ESLD.17 We tabulated 5 factors shown in some studies to predict bleeding including high International Normalized Ratio (INR) (>1.5), low hematocrit (<25%), low platelet count (<100,000 per microliter), active bleeding at EGD, and transfusion of four or more units of red cells within 24 hours of admission.1013

We defined rebleeding as a decrease in hematocrit of greater than 5 percentage points compared with postresuscitation hematocrit, transfusion of additional red cells more than 48 hours after initial resuscitation, repeat unscheduled EGD, or return to the ICU for therapies related to rebleeding.18 The University of Washington Human Subjects Board approved this study.

Results

Of 224 patients initially identified, 36 received pharmacologic VTEP. We excluded 14 who did not have ESLD (n = 1) or did not have a variceal bleed (n = 13). The remaining 22 patients form the sample described in Figure 1.

The median age of patients was 52 years (range 42‐85) and 77% were men (Table 1). Twenty‐one of 22 patients (95%) were initially admitted to the ICU; median length of stay was 8 days (range 4‐30). Median MELD score on admission was 15 (range 825). On EGD, the number of variceal columns ranged from 1 to 4; 17 patients (77%) had at least 3. A total of 15 patients (68%) had stigmata of recent bleeding and 16 (72%) underwent banding (range 16 bands). All patients had at least 1 bleeding risk factor (Table 1) of which the most common factors observed were initial transfusion of 4 or more units of red cells (50%, n = 11), INR > 1.5 (45%, n = 10), and hematocrit < 25% (45%, n = 10).

Characteristics of Hospitalized Patients with End‐Stage Liver Disease and Variceal Bleeding Who Received Pharmacologic Thromboembolism Prophylaxis (n = 22)
Parameter Range Median Value/% Interquartile Range Mean Standard Deviation
  • Abbreviations: EGD, esophagogastroduodenoscopy; ICU, intesive care unit; INR, International Normalized Ratio; MELD, Model for End‐Stage Liver Disease.

  • Risk factors for rebleeding included high INR (>1.5), low hematocrit (<25%), low platelet count (<100,000/L), active bleeding at EGD, and initial transfusion of four or more units of red cells.811

Age (years) 4285 52 4758 53 9
Sex (men) 17 77%
MELD scores 825 14.5 1120 15 5
Initial ICU admission 21 95%
Hospital length of stay (days) 430 8 9.9 6.7
Initial INR 1.12.4 1.5 1.42.0 1.7 0.4
Initial hematocrit (%) 1444 26 2232 27 8
Initial platelets (thousand/L) 43494 131 83159 147 98
EGD results
Grade 1 3 14%
Grade 2 6 27%
Grade 3 12 55%
Grade 4 1 5%
Stigmata of recent bleeding 15 68%
Number of risk factors for rebleeding*
0 0 0%
1 9 41%
2 7 32%
3 5 23%
4 1 4%
Initial transfusion red blood cells
None 2 9%
13 units 9 41%
4+ units 11 50%
Initial transfusion frozen plasma
None 10 45%
14 units 3 14%
58 units 6 27%
9+ units 4 18%
Initial transfusion platelets
None 13 59%
14 units 4 18%
5+ units 5 23%

A total of 12 patients (55%) received 5000 units of UFH every 8 hours, 8 (36%) received 5000 units UFH every 12 hours, and 2 (9%) received LMWH. VTEP was initiated as early as day of admission and as late as day 19. Median VTEP start date was hospital day 4. Median duration of of VTEP was 5 days.

Only 1 patient (4.5%) rebled after VTEP initiation. The patient received UFH every 8 hours starting on hospital day 6, and rebleeding occurred on day 9. Repeat EGD showed ulcers at banding sites. The patient was restarted on VTEP on hospital day 13 without recurrence of rebleeding. This patient had a MELD score of 24, initial INR >2, hematocrit <25%, had grade 3 varices and stigmata of recent bleeding on EGD, and received 4 units of packed red cells. These values are similar to those of the cohort as a whole (Table 1). This patient also was diagnosed with DVT while receiving VTEP on hospital day 15. This patient's coagulopathy was in the setting of terminal illness; the patient expired on hospital day 25.

One additional patient rebled prior to VTEP initiation on day 3 with repeat EGD showing a bleeding varix. This patient was nevertheless started on VTEP 4 days after rebleeding. Despite use of VTEP, this patient was diagnosed with DVT on hospital day 9 (and may well have had the DVT at the time of VTEP initiation). The patient was transitioned to therapeutic dose heparin which was tolerated without recurrence of rebleeding.

There were no other confirmed cases of DVT in this series. One additional patient underwent angiogram that showed no pulmonary embolism; 2 other patients underwent lower extremity ultrasounds that were negative for DVT.

Discussion

At our medical center, only a few inpatients with ESLD admitted with variceal bleed received VTEP. These patients were seemingly at high risk for bleeding and rebleeding given high MELD scores, variceal bleeding, and presence of at least one clinical factor suggesting bleeding risk, and in several cases 3 or more such factors.13, 18 Despite this, only 1 patient rebled while receiving VTEP. We captured rebleeding rates only during the index hospitalization. We therefore may underestimate early rebleeding rates.1013 Nevertheless, our inpatient data included complete coverage of the earliest period after the index bleeds and the period during which patients were exposed to VTEP, which should be the time of highest rebleeding risk related to VTEP exposure. Interestingly the patient who rebled while on VTEP was also diagnosed with VTE while on VTEP. Two patients (9%) in our sample were diagnosed with VTE.

This case series is limited by its small sample size, retrospective nature, single center observation, and perhaps especially by possible selection bias. We were unable to specifically quantify rebleeding risk. Several authors have identified individual factors associated with rebleeding,1013 these were tabulated for patients in this case series (Table 1) and all patients had at least 1 of these factors. Concurrent infection and hepatic vein pressure gradient have been shown to predict rebleeding;9, 19 we were unable to identify these factors in our data.

There was considerable variability in this case series in timing of VTEP initiation relative to initial bleed. We were unable to characterize provider or patient characteristics that may have influenced the decision to initiate VTEP and timing. The sample size was also too small to comment upon factors associated with choice of UFH versus LMWH and any potential differences in rebleeding risk between the 2. We also did not look at outcomes postindex hospitalization so we can not comment on the extended risk of rebleeding with VTEP after discharge. However, the risk of rebleeding is highest within the first 96 hours13 and all patients in this series were hospitalized at least 4 days. Nonetheless, we captured all patients with ESLD and variceal bleeding exposed to VTEP at a large center over a three‐year period and found rebleeding rates less than what might be expected.

Conclusions

Our observations suggest that some inpatients with ESLD and variceal bleeding may tolerate pharmacologic VTEP. In this small group of patients, VTEP was associated with an unexpectedly low incidence of rebleeding. While this case series does not support broad use of VTEP in this population, the lower‐than‐expected rates of rebleeding suggest that further study of the safety and effectiveness of pharmacologic VTEP in inpatient populations with ESLD may be warranted, particularly given the recommendations of recent national VTE prophylaxis guidelines.4

Venous thromboembolism (VTE) is a major cause of morbidity and mortality in hospitalized patients.13 Major efforts are underway to increase appropriate VTE prophylaxis (VTEP)4 and adherence to VTEP guidelines are increasingly used as a quality of care measure. National 2008 VTEP guidelines suggest that all medical patients ill enough to require hospitalization, particularly those requiring admission to the Intensive Care Unit (ICU), have at least a moderate risk of developing VTE and prophylaxis is recommended.4 Hospitalized patients with end‐stage liver disease (ESLD), despite their coagulopathy, are known to be at risk for VTE48 and may be VTEP candidates.

Based on available literature, it is unknown whether pharmacologic VTEP should be utilized in acutely ill, hospitalized patients with ESLD, particularly in those admitted with variceal bleeding. These patients are at high risk for rebleeding, with the highest risk in the first 5 days.9 Early rebleeding, defined as recurrent bleeding within 6 weeks of initial bleed, declined from 47% in the 1980s to 13% by 2000 because of increased early endoscopic intervention and use of medications to prevent rebleeding.911 In multicenter cohort studies, D'Amico and De Franchis12 reported that 13% of patients with variceal bleeding had uncontrolled bleeding, rebleeding, or death within 5 days of admission while Bahmba et al.13 reported a 16% rate of rebleeding within 5 days. We are unaware of prior reports regarding the safety of VTEP in this high‐risk group of patients.

Objective

We sought to describe rebleeding in a series of 22 patients with ESLD admitted with variceal bleeding who received pharmacologic VTEP.

Methods

We identified all patients 18 years and older with upper gastrointestinal bleeding admitted to Harborview Medical Center, a 400‐bed urban county teaching hospital in Seattle, Washington, between January 1, 2003 and December 31, 2005 (Figure 1), just prior to medical center‐wide implementation of a VTEP guideline. Potential cases were identified using administrative data based on 8 discharge diagnoses (Supporting Information Appendix 1) and 10 procedure codes (Supporting Information Appendix 2).14 Inpatient pharmacy data indicating continuous octreotide infusion were used to refine the sample. At our institution, it is a standard of care to initiate octreotide in patients admitted with variceal bleeding. We excluded patients who did not have ESLD (defined as evidence of cirrhosis and associated complications including but not limited to ascites, encephalopathy, variceal bleeding, portal hypertension) documented in their problem list or past medical history and those with no variceal bleeding based on medical record review. We identified cases receiving pharmacologic VTEP, either subcutaneous unfractionated heparin (UFH) or low molecular weight heparin (LMWH), during hospitalization from pharmacy records.

Figure 1
Patient identification: Patients with end‐stage liver disease (ESLD) admitted with variceal bleed who received pharmacologic venous thromboembolism prophylaxis. EGD, esophagogastroduodenoscopy; ICD‐9, International Classification of Disease, Version 9 diagnosis codes; CPT, common procedural terminology (CPT) procedure codes; VTEP, venous thromboembolism prophylaxis.

We obtained demographic and clinical data from administrative billing systems, electronic and paper medical records, and inpatient pharmacy databases and verified transfusion data from the Puget Sound Blood Center. We abstracted esophagogastroduodenoscopy (EGD) findings indicating high risk of rebleeding including variceal grade and stigmata of recent bleeding such as red spots or wales.15, 16 Data were abstracted by the first 3 authors (AS, MS, KJ) and reviewed again by 2 authors (AS, KJ) blinded to the others' abstractions.

We calculated Model for ESLD (MELD) scores on admission. These scores correlate with 3 month mortality in ESLD.17 We tabulated 5 factors shown in some studies to predict bleeding including high International Normalized Ratio (INR) (>1.5), low hematocrit (<25%), low platelet count (<100,000 per microliter), active bleeding at EGD, and transfusion of four or more units of red cells within 24 hours of admission.1013

We defined rebleeding as a decrease in hematocrit of greater than 5 percentage points compared with postresuscitation hematocrit, transfusion of additional red cells more than 48 hours after initial resuscitation, repeat unscheduled EGD, or return to the ICU for therapies related to rebleeding.18 The University of Washington Human Subjects Board approved this study.

Results

Of 224 patients initially identified, 36 received pharmacologic VTEP. We excluded 14 who did not have ESLD (n = 1) or did not have a variceal bleed (n = 13). The remaining 22 patients form the sample described in Figure 1.

The median age of patients was 52 years (range 42‐85) and 77% were men (Table 1). Twenty‐one of 22 patients (95%) were initially admitted to the ICU; median length of stay was 8 days (range 4‐30). Median MELD score on admission was 15 (range 825). On EGD, the number of variceal columns ranged from 1 to 4; 17 patients (77%) had at least 3. A total of 15 patients (68%) had stigmata of recent bleeding and 16 (72%) underwent banding (range 16 bands). All patients had at least 1 bleeding risk factor (Table 1) of which the most common factors observed were initial transfusion of 4 or more units of red cells (50%, n = 11), INR > 1.5 (45%, n = 10), and hematocrit < 25% (45%, n = 10).

Characteristics of Hospitalized Patients with End‐Stage Liver Disease and Variceal Bleeding Who Received Pharmacologic Thromboembolism Prophylaxis (n = 22)
Parameter Range Median Value/% Interquartile Range Mean Standard Deviation
  • Abbreviations: EGD, esophagogastroduodenoscopy; ICU, intesive care unit; INR, International Normalized Ratio; MELD, Model for End‐Stage Liver Disease.

  • Risk factors for rebleeding included high INR (>1.5), low hematocrit (<25%), low platelet count (<100,000/L), active bleeding at EGD, and initial transfusion of four or more units of red cells.811

Age (years) 4285 52 4758 53 9
Sex (men) 17 77%
MELD scores 825 14.5 1120 15 5
Initial ICU admission 21 95%
Hospital length of stay (days) 430 8 9.9 6.7
Initial INR 1.12.4 1.5 1.42.0 1.7 0.4
Initial hematocrit (%) 1444 26 2232 27 8
Initial platelets (thousand/L) 43494 131 83159 147 98
EGD results
Grade 1 3 14%
Grade 2 6 27%
Grade 3 12 55%
Grade 4 1 5%
Stigmata of recent bleeding 15 68%
Number of risk factors for rebleeding*
0 0 0%
1 9 41%
2 7 32%
3 5 23%
4 1 4%
Initial transfusion red blood cells
None 2 9%
13 units 9 41%
4+ units 11 50%
Initial transfusion frozen plasma
None 10 45%
14 units 3 14%
58 units 6 27%
9+ units 4 18%
Initial transfusion platelets
None 13 59%
14 units 4 18%
5+ units 5 23%

A total of 12 patients (55%) received 5000 units of UFH every 8 hours, 8 (36%) received 5000 units UFH every 12 hours, and 2 (9%) received LMWH. VTEP was initiated as early as day of admission and as late as day 19. Median VTEP start date was hospital day 4. Median duration of of VTEP was 5 days.

Only 1 patient (4.5%) rebled after VTEP initiation. The patient received UFH every 8 hours starting on hospital day 6, and rebleeding occurred on day 9. Repeat EGD showed ulcers at banding sites. The patient was restarted on VTEP on hospital day 13 without recurrence of rebleeding. This patient had a MELD score of 24, initial INR >2, hematocrit <25%, had grade 3 varices and stigmata of recent bleeding on EGD, and received 4 units of packed red cells. These values are similar to those of the cohort as a whole (Table 1). This patient also was diagnosed with DVT while receiving VTEP on hospital day 15. This patient's coagulopathy was in the setting of terminal illness; the patient expired on hospital day 25.

One additional patient rebled prior to VTEP initiation on day 3 with repeat EGD showing a bleeding varix. This patient was nevertheless started on VTEP 4 days after rebleeding. Despite use of VTEP, this patient was diagnosed with DVT on hospital day 9 (and may well have had the DVT at the time of VTEP initiation). The patient was transitioned to therapeutic dose heparin which was tolerated without recurrence of rebleeding.

There were no other confirmed cases of DVT in this series. One additional patient underwent angiogram that showed no pulmonary embolism; 2 other patients underwent lower extremity ultrasounds that were negative for DVT.

Discussion

At our medical center, only a few inpatients with ESLD admitted with variceal bleed received VTEP. These patients were seemingly at high risk for bleeding and rebleeding given high MELD scores, variceal bleeding, and presence of at least one clinical factor suggesting bleeding risk, and in several cases 3 or more such factors.13, 18 Despite this, only 1 patient rebled while receiving VTEP. We captured rebleeding rates only during the index hospitalization. We therefore may underestimate early rebleeding rates.1013 Nevertheless, our inpatient data included complete coverage of the earliest period after the index bleeds and the period during which patients were exposed to VTEP, which should be the time of highest rebleeding risk related to VTEP exposure. Interestingly the patient who rebled while on VTEP was also diagnosed with VTE while on VTEP. Two patients (9%) in our sample were diagnosed with VTE.

This case series is limited by its small sample size, retrospective nature, single center observation, and perhaps especially by possible selection bias. We were unable to specifically quantify rebleeding risk. Several authors have identified individual factors associated with rebleeding,1013 these were tabulated for patients in this case series (Table 1) and all patients had at least 1 of these factors. Concurrent infection and hepatic vein pressure gradient have been shown to predict rebleeding;9, 19 we were unable to identify these factors in our data.

There was considerable variability in this case series in timing of VTEP initiation relative to initial bleed. We were unable to characterize provider or patient characteristics that may have influenced the decision to initiate VTEP and timing. The sample size was also too small to comment upon factors associated with choice of UFH versus LMWH and any potential differences in rebleeding risk between the 2. We also did not look at outcomes postindex hospitalization so we can not comment on the extended risk of rebleeding with VTEP after discharge. However, the risk of rebleeding is highest within the first 96 hours13 and all patients in this series were hospitalized at least 4 days. Nonetheless, we captured all patients with ESLD and variceal bleeding exposed to VTEP at a large center over a three‐year period and found rebleeding rates less than what might be expected.

Conclusions

Our observations suggest that some inpatients with ESLD and variceal bleeding may tolerate pharmacologic VTEP. In this small group of patients, VTEP was associated with an unexpectedly low incidence of rebleeding. While this case series does not support broad use of VTEP in this population, the lower‐than‐expected rates of rebleeding suggest that further study of the safety and effectiveness of pharmacologic VTEP in inpatient populations with ESLD may be warranted, particularly given the recommendations of recent national VTE prophylaxis guidelines.4

References
  1. Aujesky D,Roy PM,Le Manach CP, et al.Validation of a model to predict adverse outcomes in patients with pulmonary embolism.Eur Heart J.2006;27(4):476481.
  2. White RH.The epidemiology of venous thromboembolism.Circulation.2003;107(23 Suppl 1):I4I8.
  3. Anderson FA,Wheeler HB,Goldberg RJ,Hosmer DW,Forcier A.The prevalence of risk factors for venous thromboembolism among hospital patients.Arch Intern Med.1992;152(8):16601664.
  4. Geerts WH,Bergqvist D,Pineo GF, et al.Prevention of venous thromboembolism: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines. 8th Edition.Chest.2008;133(6 Suppl):381S453S.
  5. Northup PG,McMahon MM,Ruhl AP, et al.Coagulopathy does not fully protect hospitalized cirrhosis patients from peripheral venous thromboembolism.Am J Gastroenterol.2006;101(7):15241528; quiz 680.
  6. Amitrano L,Guardascione MA,Brancaccio V,Balzano A.Coagulation disorders in liver disease.Semin Liver Dis.2002;22(1):8396.
  7. Gulley D,Teal E,Suvannasankha A,Chalasani N,Liangpunsakul S.Deep vein thrombosis and pulmonary embolism in cirrhosis patients.Dig Dis Sci.2008;53(11):30123017.
  8. Sogaard KK,Horvath‐Puho E,Gronbaek H,Jepsen P,Vilstrup H,Sorensen HT.Risk of venous thromboembolism in patients with liver disease: a nationwide population‐based case‐control study.Am J Gastroenterol.2009;104(1):96101.
  9. de Franchis R,Dell'Era A.Non‐invasive diagnosis of cirrhosis and the natural history of its complications.Best Pract Res Clin Gastroenterol.2007;21(1):318.
  10. Chalasani N,Kahi C,Francois F,et al.Improved patient survival after acute variceal bleeding: a multicenter, cohort study.Am J Gastroenterol.2003;98(3):653659.
  11. Carbonell N,Pauwels A,Serfaty L,Fourdan O,Levy VG,Poupon R.Improved survival after variceal bleeding in patients with cirrhosis over the past two decades.Hepatology.2004;40(3):652659.
  12. D'Amico G,De Franchis R.Upper digestive bleeding in cirrhosis. Post‐therapeutic outcome and prognostic indicators.Hepatology.2003;38(3):599612.
  13. Bambha K,Kim WR,Pedersen R,Bida JP,Kremers WK,Kamath PS.Predictors of early re‐bleeding and mortality after acute variceal haemorrhage in patients with cirrhosis.Gut.2008;57(6):814820.
  14. Smith MW,Jarma KM,Schleyer AM,Schreuder AB,Goss R,Onstad S.Use of hospital administrative data to assess quality improvement initiatives.J Gen Intern Med.2007;22(Supplement).
  15. Jalan R,Hayes PC.UK guidelines on the management of variceal haemorrhage in cirrhotic patients.Gut.2000,year="2000"2000;46(90003):iii115.
  16. Siringo S,McCormick PA,Mistry P,Kaye G,McIntyre N,Burroughs AK.Prognostic significance of the white nipple sign in variceal bleeding.Gastrointest Endosc.1991;37(1):5155.
  17. Kamath PS,Wiesner RH,Malinchoc M, et al.A model to predict survival in patients with end‐stage liver disease.Hepatology.2001;33(2):464470.
  18. de Franchis R.Evolving consensus in portal hypertension. Report of the Baveno IV consensus workshop on methodology of diagnosis and therapy in portal hypertension.J Hepatol.2005;43(1):167176.
  19. Hou MC,Lin HC,Liu TT, et al.Antibiotic prophylaxis after endoscopic therapy prevents rebleeding in acute variceal hemorrhage: a randomized trial.Hepatology.2004;39(3):746753.
References
  1. Aujesky D,Roy PM,Le Manach CP, et al.Validation of a model to predict adverse outcomes in patients with pulmonary embolism.Eur Heart J.2006;27(4):476481.
  2. White RH.The epidemiology of venous thromboembolism.Circulation.2003;107(23 Suppl 1):I4I8.
  3. Anderson FA,Wheeler HB,Goldberg RJ,Hosmer DW,Forcier A.The prevalence of risk factors for venous thromboembolism among hospital patients.Arch Intern Med.1992;152(8):16601664.
  4. Geerts WH,Bergqvist D,Pineo GF, et al.Prevention of venous thromboembolism: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines. 8th Edition.Chest.2008;133(6 Suppl):381S453S.
  5. Northup PG,McMahon MM,Ruhl AP, et al.Coagulopathy does not fully protect hospitalized cirrhosis patients from peripheral venous thromboembolism.Am J Gastroenterol.2006;101(7):15241528; quiz 680.
  6. Amitrano L,Guardascione MA,Brancaccio V,Balzano A.Coagulation disorders in liver disease.Semin Liver Dis.2002;22(1):8396.
  7. Gulley D,Teal E,Suvannasankha A,Chalasani N,Liangpunsakul S.Deep vein thrombosis and pulmonary embolism in cirrhosis patients.Dig Dis Sci.2008;53(11):30123017.
  8. Sogaard KK,Horvath‐Puho E,Gronbaek H,Jepsen P,Vilstrup H,Sorensen HT.Risk of venous thromboembolism in patients with liver disease: a nationwide population‐based case‐control study.Am J Gastroenterol.2009;104(1):96101.
  9. de Franchis R,Dell'Era A.Non‐invasive diagnosis of cirrhosis and the natural history of its complications.Best Pract Res Clin Gastroenterol.2007;21(1):318.
  10. Chalasani N,Kahi C,Francois F,et al.Improved patient survival after acute variceal bleeding: a multicenter, cohort study.Am J Gastroenterol.2003;98(3):653659.
  11. Carbonell N,Pauwels A,Serfaty L,Fourdan O,Levy VG,Poupon R.Improved survival after variceal bleeding in patients with cirrhosis over the past two decades.Hepatology.2004;40(3):652659.
  12. D'Amico G,De Franchis R.Upper digestive bleeding in cirrhosis. Post‐therapeutic outcome and prognostic indicators.Hepatology.2003;38(3):599612.
  13. Bambha K,Kim WR,Pedersen R,Bida JP,Kremers WK,Kamath PS.Predictors of early re‐bleeding and mortality after acute variceal haemorrhage in patients with cirrhosis.Gut.2008;57(6):814820.
  14. Smith MW,Jarma KM,Schleyer AM,Schreuder AB,Goss R,Onstad S.Use of hospital administrative data to assess quality improvement initiatives.J Gen Intern Med.2007;22(Supplement).
  15. Jalan R,Hayes PC.UK guidelines on the management of variceal haemorrhage in cirrhotic patients.Gut.2000,year="2000"2000;46(90003):iii115.
  16. Siringo S,McCormick PA,Mistry P,Kaye G,McIntyre N,Burroughs AK.Prognostic significance of the white nipple sign in variceal bleeding.Gastrointest Endosc.1991;37(1):5155.
  17. Kamath PS,Wiesner RH,Malinchoc M, et al.A model to predict survival in patients with end‐stage liver disease.Hepatology.2001;33(2):464470.
  18. de Franchis R.Evolving consensus in portal hypertension. Report of the Baveno IV consensus workshop on methodology of diagnosis and therapy in portal hypertension.J Hepatol.2005;43(1):167176.
  19. Hou MC,Lin HC,Liu TT, et al.Antibiotic prophylaxis after endoscopic therapy prevents rebleeding in acute variceal hemorrhage: a randomized trial.Hepatology.2004;39(3):746753.
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A descriptive case series of patients with end‐stage liver disease hospitalized with variceal bleeding who received pharmacologic venous thromboembolism prophylaxis
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Improving Insulin Ordering Safely

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Improving insulin ordering safely: The development of an inpatient glycemic control program

The benefits of glycemic control include decreased patient morbidity, mortality, length of stay, and reduced hospital costs. In 2004, the American College of Endocrinology (ACE) issued glycemic guidelines for non‐critical‐care units (fasting glucose <110 mg/dL, nonfasting glucose <180 mg/dL).1 A comprehensive review of inpatient glycemic management called for development and evaluation of inpatient programs and tools.2 The 2006 ACE/American Diabetes Association (ADA) Statement on Inpatient Diabetes and Glycemic Control identified key components of an inpatient glycemic control program as: (1) solid administrative support; (2) a multidisciplinary committee; (3) assessment of current processes, care, and barriers; (4) development and implementation of order sets, protocols, policies, and educational efforts; and (5) metrics for evaluation.3

In 2003, Harborview Medical Center (HMC) formed a multidisciplinary committee to institute a Glycemic Control Program. The early goals were to decrease the use of sliding‐scale insulin, increase the appropriate use of basal and prandial insulin, and to avoid hypoglycemia. Here we report our program design and trends in physician insulin ordering from 2003 through 2006.

Patients and Methods

Setting

Seattle's HMC is a 400‐bed level‐1 regional trauma center managed by the University of Washington. The hospital's mission includes serving at‐risk populations. Based on illness, the University HealthSystem Consortium (UHC) assigns HMC the highest predicted mortality among its 131 affiliated hospitals nationwide.4

Patients

We included all patients hospitalized in non‐critical‐care wardsmedical, surgical, and psychiatric. Patients were categorized as dysglycemic if they: (1) received subcutaneous insulin or oral diabetic medications; or (2) had any single glucose level outside the normal range of 125 mg/dL or <60 mg/dL. Patients not meeting these criteria were classified as euglycemic. Approval was obtained from the University of Washington Human Subjects Review Committee.

Program Description

Since 2003, the multidisciplinary committeephysicians, nurses, pharmacy representatives, and dietary and administrative representativeshas directed the development of the Glycemic Control Program with support from hospital administration and the Department of Quality Improvement. Funding for this program has been provided by the hospital based on the prominence of glycemic control among quality and safety measures, a projected decrease in costs, and the high incidence of diabetes in our patient population. Figure 1 outlines the program's key interventions.

Figure 1
Timeline of interventions.

First, a Subcutaneous Insulin Order Form was released for elective use in May 2004 (Figure 2). This form incorporated the 3 components of quality insulin ordering (basal, scheduled prandial, and prandial correction dosing) and provides prompts and education. A Diabetes Nurse Specialist trained nursing staff on the use of the form.

Figure 2
Subcutaneous insulin orders.

Second, we developed an automated daily data report identifying patients with out‐of‐range glucose levels defined as having any single glucose readings <60 mg/dL or any 2 readings 180 mg/dL within the prior 24 hours. In February 2006, this daily report became available to the clinicians on the committee.

Third, the Glycemic Control Program recruited a full‐time clinical Advanced Registered Nurse Practitioner (ARNP) and part‐time supervising physician to provide directed intervention and education for patients and medical personnel. Since August 2006, the ARNP has reviewed the out‐of‐range report daily, performs assessments, refines insulin orders, and educates clinicians. The assessments include chart review (of history and glycemic control), discussion with primary physician and nurse (and often the dietician), and interview of the patient and/or family. This leads to development and implementation of a glycemic control plan. Clinician education is performed both as direct education of the primary physician at the time of intervention and as didactic sessions.

Outcomes

Physician Insulin Ordering

The numbers of patients receiving basal and short‐acting insulin were identified from the electronic medication record. Basal insulin included glargine and neutral protamine Hagerdorn (NPH). Short‐acting insulin (lispro or regular) could be ordered as scheduled prandial, prandial correction, or sliding scale. The distinction between prandial correction and sliding scale is that correction precedes meals exclusively and is not intended for use without food; in contrast, sliding scale is given regardless of food being consumed and is considered substandard. Quality insulin ordering is defined as having basal, prandial scheduled, and prandial correction doses.

In the electronic record, however, we were unable to distinguish the intent of short‐acting insulin orders in the larger data set. Thus, we reviewed a subset of 100 randomly selected charts (25 from each year from 2003 through 2006) to differentiate scheduled prandial, prandial correction, and sliding scale.

Hyperglycemia

Hyperglycemia was defined as glucose 180 mg/dL. The proportion of dysglycemic patients with hyperglycemia was calculated daily as the percent of dysglycemic patients with any 2 glucose levels 180 mg/dL. Daily values were averaged for quarterly measures.

Hypoglycemia

Hypoglycemia was defined as glucose <60 mg/dL. The proportion of all dysglycemic patients with hypoglycemia was calculated daily as the percent of dysglycemic patients with a single glucose level of <60 mg/dL. Daily values were averaged for quarterly measures.

Data Collection

Data were retrieved from electronic medical records, hospital administrative decision support, and risk‐adjusted5 UHC clinical database information. Glucose data were obtained from laboratory records (venous) and nursing data from bedside chemsticks (capillary).

Statistical Analyses

Data were analyzed using SAS 9.1 (SAS Institute, Cary, NC) and SPSS 13.0 (SPSS, Chicago, IL). The mean and standard deviation (SD) for continuous variables and proportions for categorical variables were calculated. Data were examined, plotted, and trended over time. Where applicable, linear regression trend lines were fitted and tested for statistical significance (P value <0.05).

Results

Patients

In total, 44,225 patients were identified from January 1, 2003 through December 31, 2006; 18,087 patients (41%) were classified as dysglycemic as defined by either: (1) receiving insulin or oral diabetic medicine; or (2) having a glucose level 125 mg/dL or <60 mg/dL. Characteristics of the population are outlined in Table 1. Both groups shared similar ethnic distributions. Across all 4 years, dysglycemic patients tended to be older and have a higher severity of illness. As an additional descriptor of severity of illness, UHC mean expected length of stay (LOS) and mean expected mortality (risk‐adjusted5) were higher for dysglycemic patients.

Characteristics of the Patient Population
Dysglycemic Euglycemic
  • Abbreviations: LOS, length of stay; SD, standard deviation; UHC, University HealthSystem Consortium.

  • UHC LOS and mortality are reported as additional descriptors of severity of illness.

Number of patients 18,088 26,144
Age (years, mean SD) 48.4 20.3 41.3 18.3
Gender, male (%) 64.7 62.7
Ethnicity (%)
Caucasian 68.2 70.1
African‐American/Black 11.0 12.0
Hispanic 6.8 6.2
Native American 1.8 18
Asian 7.9 5.5
Unknown 4.3 4.4
UHC severity of illness index (%)
Minor 18.3 38.8
Moderate 35.4 40.8
Major 29.5 16.7
Extreme 16.9 3.6
UHC expected LOS (days, mean SD)* 7.8 6.9 5.2 4.1
UHC expected mortality (mean SD)* 0.06 0.13 0.01 0.06

Physician Insulin Ordering

Ordering of both short‐acting and basal insulin increased (Figure 3). The ratio of short‐acting to basal orders decreased from 3.36 (1668/496) in 2003 to 1.97 (2226/1128) in 2006.

Figure 3
Percentage of dysglycemic patients receiving short‐acting and basal insulin.

Chart review of the 100 randomly selected dysglycemic patients revealed increased ordering of prandial correction dosing from 8% of patients in 2003 to 32% in 2006. Yet, only 1 patient in 2003 and only 2 in 2006 had scheduled prandial. Ordering of sliding scale insulin fell from 16% in 2003 to 4% in 2006.

Glycemic Control Outcomes

The percentage of dysglycemic patients with hyperglycemia ranged from 19 to 24 without significant decline over the 4 years (Figure 4A). The percentage of hypoglycemic dysglycemic patients was increasing from 2003 to 2004, but in the years following the interventions (2005 through 2006) this declined significantly (P = 0.003; Figure 4B). On average, the observed LOS was higher for dysglycemic vs. euglycemic patients (mean SD days: 9.4 12.2 and 5.8 8.5, respectively). The mean observed to expected mortality ratio was 0.45 0.08 and 0.44 0.17 for the dysglycemic and euglycemic patients, respectively. Over the 4 years no statistically significant change in observed LOS or adjusted mortality was found (data not shown).

Figure 4
(A) Hyperglycemia. Percent of dysglycemic patients with any 2 glucose levels greater than 180 mg/dL in a 24‐hour period. (B) Hypoglycemia. Percent of dysglycemic patients with a single glucose level less than 60 mg/dL in a 24‐hour period.

Conclusions

HMC, a safety net hospital with the highest UHC expected mortality of 131 hospitals nationwide, has demonstrated early successes in building its Glycemic Control Program, including: (1) decreased prescription of sliding scale; (2) a marked increase in prescription of basal insulin; and (3) significantly decreasing hypoglycemic events subsequent to the interventions. The decreased sliding scale and increased overall ordering of insulin could reflect increased awareness brought internationally through the literature and locally through our program. Two distinctive aspects of HMC's Glycemic Control Program, when compared to others,68 include: (1) the daily use of real‐time data to identify and target patients with out‐of‐range glucose levels; and (2) the coverage of all non‐critical‐care floors with a single clinician.

In 2003 and 2004, the increasing hypoglycemia we observed paralleled the international focus on aggressively treating hyperglycemia in the acute care setting. We observed a significant decrease in hypoglycemia in 2005 and 2006 that could be attributed to the education provided by the Glycemic Control Program and 2 features on the subcutaneous insulin order set: the prominent hypoglycemia protocol and the order hold prandial insulin if the patient cannot eat. These are similar features identified in a report on preventing hospital hypoglycemia.9 Additionally, hypoglycemia may have decreased secondary to the emphasis on not using short‐acting insulin at bedtime.

Despite increased and improved insulin ordering, we did not observe a significant change in the percent of dysglycemic patients with 2 glucose levels 180 mg/dL. In our program patients are identified for intervention after their glucose levels are out‐of‐range. To better evaluate the impact of our interventions on the glycemic control of each patient, we plan to analyze the glucose levels in the days following identification of patients. Alternatively, we could provide intervention to all patients with dysglycemia rather than waiting for glucoses to be out‐of‐range. Though this approach would require greater resources than the single clinician we currently employ.

Our early experience highlights areas for future evaluation and intervention. First, the lack of scheduled prandial insulin and that less than one‐third of dysglycemic patients have basal insulin ordered underscore a continued need to target quality insulin ordering to include all componentsbasal, scheduled prandial, and prandial correction. Second, while the daily report is a good rudimentary identification tool for at‐risk patients, it offers limited information as to the impact of our clinical intervention. Thus, refined evaluative metrics need be developed to prospectively assess the course of glycemic control for patients.

We acknowledge the limitations of this study. First, our most involved interventionthe addition of the clinical intervention teamcame only 6 months before the end of the study period. Second, this is an observational retrospective analysis and cannot distinguish confounders, such as physician preferences and decisions, that not easily quantified or controlled for. Third, our definition of dysglycemic incorporated 41% of non‐critical‐care patients, possibly reflecting too broad a definition.

In summary, we have described an inpatient Glycemic Control Program that relies on real‐time data to identify patients in need of intervention. Early in our program we observed improved insulin ordering quality and decreased rates of hypoglycemia. Future steps include evaluating the impact of our clinical intervention team and further refining glycemic control metrics to prospectively identify patients at risk for hyper‐ and hypoglycemia.

Acknowledgements

The authors thank Sofia Medvedev (UHC) and Derk B. Adams (HMC QI). The information contained in this article was based in part on the Clinical Data Products Data Base maintained by the UHC.

References
  1. Garber AJ,Moghissi ES,Bransome ED, et al.American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10(suppl 2):49.
  2. Clement S,Braithwaite SS,Magee MF, et al.Management of diabetes and hyperglycemia in hospitals.Diabetes Care.2004;27:553591.
  3. American College of Endocrinology and American Diabetes Association Consensus statement on inpatient diabetes and glycemic control.Diabetes Care.2006;29:19551962.
  4. University HealthSystem Consortium Mortality. Confidential Clinical Outcomes Report. Available at: http://www.uhc.edu. Accessed August2009 (Access with UHC permission only).
  5. Mortality risk adjustment for University HealthSystem Consortium's Clinical database. Available at: http://www.ahrq.gov/qual/mortality/Meurer.pdf. Accessed August2009.
  6. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12:491505.
  7. Korytkowski M,Dinardo M,Donihi AC,Bigi L,Devita M.Evolution of a diabetes inpatient safety committee.Endocr Pract.2006;12(suppl 3):9199.
  8. Newton CA,Young S.Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(suppl 3):4348.
  9. Braithwaite SS,Buie MM,Thompson CL, et al.Hospital hypoglycemia: not only treatment but also prevention.Endocr Pract.2004;10(suppl 2):8999.
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The benefits of glycemic control include decreased patient morbidity, mortality, length of stay, and reduced hospital costs. In 2004, the American College of Endocrinology (ACE) issued glycemic guidelines for non‐critical‐care units (fasting glucose <110 mg/dL, nonfasting glucose <180 mg/dL).1 A comprehensive review of inpatient glycemic management called for development and evaluation of inpatient programs and tools.2 The 2006 ACE/American Diabetes Association (ADA) Statement on Inpatient Diabetes and Glycemic Control identified key components of an inpatient glycemic control program as: (1) solid administrative support; (2) a multidisciplinary committee; (3) assessment of current processes, care, and barriers; (4) development and implementation of order sets, protocols, policies, and educational efforts; and (5) metrics for evaluation.3

In 2003, Harborview Medical Center (HMC) formed a multidisciplinary committee to institute a Glycemic Control Program. The early goals were to decrease the use of sliding‐scale insulin, increase the appropriate use of basal and prandial insulin, and to avoid hypoglycemia. Here we report our program design and trends in physician insulin ordering from 2003 through 2006.

Patients and Methods

Setting

Seattle's HMC is a 400‐bed level‐1 regional trauma center managed by the University of Washington. The hospital's mission includes serving at‐risk populations. Based on illness, the University HealthSystem Consortium (UHC) assigns HMC the highest predicted mortality among its 131 affiliated hospitals nationwide.4

Patients

We included all patients hospitalized in non‐critical‐care wardsmedical, surgical, and psychiatric. Patients were categorized as dysglycemic if they: (1) received subcutaneous insulin or oral diabetic medications; or (2) had any single glucose level outside the normal range of 125 mg/dL or <60 mg/dL. Patients not meeting these criteria were classified as euglycemic. Approval was obtained from the University of Washington Human Subjects Review Committee.

Program Description

Since 2003, the multidisciplinary committeephysicians, nurses, pharmacy representatives, and dietary and administrative representativeshas directed the development of the Glycemic Control Program with support from hospital administration and the Department of Quality Improvement. Funding for this program has been provided by the hospital based on the prominence of glycemic control among quality and safety measures, a projected decrease in costs, and the high incidence of diabetes in our patient population. Figure 1 outlines the program's key interventions.

Figure 1
Timeline of interventions.

First, a Subcutaneous Insulin Order Form was released for elective use in May 2004 (Figure 2). This form incorporated the 3 components of quality insulin ordering (basal, scheduled prandial, and prandial correction dosing) and provides prompts and education. A Diabetes Nurse Specialist trained nursing staff on the use of the form.

Figure 2
Subcutaneous insulin orders.

Second, we developed an automated daily data report identifying patients with out‐of‐range glucose levels defined as having any single glucose readings <60 mg/dL or any 2 readings 180 mg/dL within the prior 24 hours. In February 2006, this daily report became available to the clinicians on the committee.

Third, the Glycemic Control Program recruited a full‐time clinical Advanced Registered Nurse Practitioner (ARNP) and part‐time supervising physician to provide directed intervention and education for patients and medical personnel. Since August 2006, the ARNP has reviewed the out‐of‐range report daily, performs assessments, refines insulin orders, and educates clinicians. The assessments include chart review (of history and glycemic control), discussion with primary physician and nurse (and often the dietician), and interview of the patient and/or family. This leads to development and implementation of a glycemic control plan. Clinician education is performed both as direct education of the primary physician at the time of intervention and as didactic sessions.

Outcomes

Physician Insulin Ordering

The numbers of patients receiving basal and short‐acting insulin were identified from the electronic medication record. Basal insulin included glargine and neutral protamine Hagerdorn (NPH). Short‐acting insulin (lispro or regular) could be ordered as scheduled prandial, prandial correction, or sliding scale. The distinction between prandial correction and sliding scale is that correction precedes meals exclusively and is not intended for use without food; in contrast, sliding scale is given regardless of food being consumed and is considered substandard. Quality insulin ordering is defined as having basal, prandial scheduled, and prandial correction doses.

In the electronic record, however, we were unable to distinguish the intent of short‐acting insulin orders in the larger data set. Thus, we reviewed a subset of 100 randomly selected charts (25 from each year from 2003 through 2006) to differentiate scheduled prandial, prandial correction, and sliding scale.

Hyperglycemia

Hyperglycemia was defined as glucose 180 mg/dL. The proportion of dysglycemic patients with hyperglycemia was calculated daily as the percent of dysglycemic patients with any 2 glucose levels 180 mg/dL. Daily values were averaged for quarterly measures.

Hypoglycemia

Hypoglycemia was defined as glucose <60 mg/dL. The proportion of all dysglycemic patients with hypoglycemia was calculated daily as the percent of dysglycemic patients with a single glucose level of <60 mg/dL. Daily values were averaged for quarterly measures.

Data Collection

Data were retrieved from electronic medical records, hospital administrative decision support, and risk‐adjusted5 UHC clinical database information. Glucose data were obtained from laboratory records (venous) and nursing data from bedside chemsticks (capillary).

Statistical Analyses

Data were analyzed using SAS 9.1 (SAS Institute, Cary, NC) and SPSS 13.0 (SPSS, Chicago, IL). The mean and standard deviation (SD) for continuous variables and proportions for categorical variables were calculated. Data were examined, plotted, and trended over time. Where applicable, linear regression trend lines were fitted and tested for statistical significance (P value <0.05).

Results

Patients

In total, 44,225 patients were identified from January 1, 2003 through December 31, 2006; 18,087 patients (41%) were classified as dysglycemic as defined by either: (1) receiving insulin or oral diabetic medicine; or (2) having a glucose level 125 mg/dL or <60 mg/dL. Characteristics of the population are outlined in Table 1. Both groups shared similar ethnic distributions. Across all 4 years, dysglycemic patients tended to be older and have a higher severity of illness. As an additional descriptor of severity of illness, UHC mean expected length of stay (LOS) and mean expected mortality (risk‐adjusted5) were higher for dysglycemic patients.

Characteristics of the Patient Population
Dysglycemic Euglycemic
  • Abbreviations: LOS, length of stay; SD, standard deviation; UHC, University HealthSystem Consortium.

  • UHC LOS and mortality are reported as additional descriptors of severity of illness.

Number of patients 18,088 26,144
Age (years, mean SD) 48.4 20.3 41.3 18.3
Gender, male (%) 64.7 62.7
Ethnicity (%)
Caucasian 68.2 70.1
African‐American/Black 11.0 12.0
Hispanic 6.8 6.2
Native American 1.8 18
Asian 7.9 5.5
Unknown 4.3 4.4
UHC severity of illness index (%)
Minor 18.3 38.8
Moderate 35.4 40.8
Major 29.5 16.7
Extreme 16.9 3.6
UHC expected LOS (days, mean SD)* 7.8 6.9 5.2 4.1
UHC expected mortality (mean SD)* 0.06 0.13 0.01 0.06

Physician Insulin Ordering

Ordering of both short‐acting and basal insulin increased (Figure 3). The ratio of short‐acting to basal orders decreased from 3.36 (1668/496) in 2003 to 1.97 (2226/1128) in 2006.

Figure 3
Percentage of dysglycemic patients receiving short‐acting and basal insulin.

Chart review of the 100 randomly selected dysglycemic patients revealed increased ordering of prandial correction dosing from 8% of patients in 2003 to 32% in 2006. Yet, only 1 patient in 2003 and only 2 in 2006 had scheduled prandial. Ordering of sliding scale insulin fell from 16% in 2003 to 4% in 2006.

Glycemic Control Outcomes

The percentage of dysglycemic patients with hyperglycemia ranged from 19 to 24 without significant decline over the 4 years (Figure 4A). The percentage of hypoglycemic dysglycemic patients was increasing from 2003 to 2004, but in the years following the interventions (2005 through 2006) this declined significantly (P = 0.003; Figure 4B). On average, the observed LOS was higher for dysglycemic vs. euglycemic patients (mean SD days: 9.4 12.2 and 5.8 8.5, respectively). The mean observed to expected mortality ratio was 0.45 0.08 and 0.44 0.17 for the dysglycemic and euglycemic patients, respectively. Over the 4 years no statistically significant change in observed LOS or adjusted mortality was found (data not shown).

Figure 4
(A) Hyperglycemia. Percent of dysglycemic patients with any 2 glucose levels greater than 180 mg/dL in a 24‐hour period. (B) Hypoglycemia. Percent of dysglycemic patients with a single glucose level less than 60 mg/dL in a 24‐hour period.

Conclusions

HMC, a safety net hospital with the highest UHC expected mortality of 131 hospitals nationwide, has demonstrated early successes in building its Glycemic Control Program, including: (1) decreased prescription of sliding scale; (2) a marked increase in prescription of basal insulin; and (3) significantly decreasing hypoglycemic events subsequent to the interventions. The decreased sliding scale and increased overall ordering of insulin could reflect increased awareness brought internationally through the literature and locally through our program. Two distinctive aspects of HMC's Glycemic Control Program, when compared to others,68 include: (1) the daily use of real‐time data to identify and target patients with out‐of‐range glucose levels; and (2) the coverage of all non‐critical‐care floors with a single clinician.

In 2003 and 2004, the increasing hypoglycemia we observed paralleled the international focus on aggressively treating hyperglycemia in the acute care setting. We observed a significant decrease in hypoglycemia in 2005 and 2006 that could be attributed to the education provided by the Glycemic Control Program and 2 features on the subcutaneous insulin order set: the prominent hypoglycemia protocol and the order hold prandial insulin if the patient cannot eat. These are similar features identified in a report on preventing hospital hypoglycemia.9 Additionally, hypoglycemia may have decreased secondary to the emphasis on not using short‐acting insulin at bedtime.

Despite increased and improved insulin ordering, we did not observe a significant change in the percent of dysglycemic patients with 2 glucose levels 180 mg/dL. In our program patients are identified for intervention after their glucose levels are out‐of‐range. To better evaluate the impact of our interventions on the glycemic control of each patient, we plan to analyze the glucose levels in the days following identification of patients. Alternatively, we could provide intervention to all patients with dysglycemia rather than waiting for glucoses to be out‐of‐range. Though this approach would require greater resources than the single clinician we currently employ.

Our early experience highlights areas for future evaluation and intervention. First, the lack of scheduled prandial insulin and that less than one‐third of dysglycemic patients have basal insulin ordered underscore a continued need to target quality insulin ordering to include all componentsbasal, scheduled prandial, and prandial correction. Second, while the daily report is a good rudimentary identification tool for at‐risk patients, it offers limited information as to the impact of our clinical intervention. Thus, refined evaluative metrics need be developed to prospectively assess the course of glycemic control for patients.

We acknowledge the limitations of this study. First, our most involved interventionthe addition of the clinical intervention teamcame only 6 months before the end of the study period. Second, this is an observational retrospective analysis and cannot distinguish confounders, such as physician preferences and decisions, that not easily quantified or controlled for. Third, our definition of dysglycemic incorporated 41% of non‐critical‐care patients, possibly reflecting too broad a definition.

In summary, we have described an inpatient Glycemic Control Program that relies on real‐time data to identify patients in need of intervention. Early in our program we observed improved insulin ordering quality and decreased rates of hypoglycemia. Future steps include evaluating the impact of our clinical intervention team and further refining glycemic control metrics to prospectively identify patients at risk for hyper‐ and hypoglycemia.

Acknowledgements

The authors thank Sofia Medvedev (UHC) and Derk B. Adams (HMC QI). The information contained in this article was based in part on the Clinical Data Products Data Base maintained by the UHC.

The benefits of glycemic control include decreased patient morbidity, mortality, length of stay, and reduced hospital costs. In 2004, the American College of Endocrinology (ACE) issued glycemic guidelines for non‐critical‐care units (fasting glucose <110 mg/dL, nonfasting glucose <180 mg/dL).1 A comprehensive review of inpatient glycemic management called for development and evaluation of inpatient programs and tools.2 The 2006 ACE/American Diabetes Association (ADA) Statement on Inpatient Diabetes and Glycemic Control identified key components of an inpatient glycemic control program as: (1) solid administrative support; (2) a multidisciplinary committee; (3) assessment of current processes, care, and barriers; (4) development and implementation of order sets, protocols, policies, and educational efforts; and (5) metrics for evaluation.3

In 2003, Harborview Medical Center (HMC) formed a multidisciplinary committee to institute a Glycemic Control Program. The early goals were to decrease the use of sliding‐scale insulin, increase the appropriate use of basal and prandial insulin, and to avoid hypoglycemia. Here we report our program design and trends in physician insulin ordering from 2003 through 2006.

Patients and Methods

Setting

Seattle's HMC is a 400‐bed level‐1 regional trauma center managed by the University of Washington. The hospital's mission includes serving at‐risk populations. Based on illness, the University HealthSystem Consortium (UHC) assigns HMC the highest predicted mortality among its 131 affiliated hospitals nationwide.4

Patients

We included all patients hospitalized in non‐critical‐care wardsmedical, surgical, and psychiatric. Patients were categorized as dysglycemic if they: (1) received subcutaneous insulin or oral diabetic medications; or (2) had any single glucose level outside the normal range of 125 mg/dL or <60 mg/dL. Patients not meeting these criteria were classified as euglycemic. Approval was obtained from the University of Washington Human Subjects Review Committee.

Program Description

Since 2003, the multidisciplinary committeephysicians, nurses, pharmacy representatives, and dietary and administrative representativeshas directed the development of the Glycemic Control Program with support from hospital administration and the Department of Quality Improvement. Funding for this program has been provided by the hospital based on the prominence of glycemic control among quality and safety measures, a projected decrease in costs, and the high incidence of diabetes in our patient population. Figure 1 outlines the program's key interventions.

Figure 1
Timeline of interventions.

First, a Subcutaneous Insulin Order Form was released for elective use in May 2004 (Figure 2). This form incorporated the 3 components of quality insulin ordering (basal, scheduled prandial, and prandial correction dosing) and provides prompts and education. A Diabetes Nurse Specialist trained nursing staff on the use of the form.

Figure 2
Subcutaneous insulin orders.

Second, we developed an automated daily data report identifying patients with out‐of‐range glucose levels defined as having any single glucose readings <60 mg/dL or any 2 readings 180 mg/dL within the prior 24 hours. In February 2006, this daily report became available to the clinicians on the committee.

Third, the Glycemic Control Program recruited a full‐time clinical Advanced Registered Nurse Practitioner (ARNP) and part‐time supervising physician to provide directed intervention and education for patients and medical personnel. Since August 2006, the ARNP has reviewed the out‐of‐range report daily, performs assessments, refines insulin orders, and educates clinicians. The assessments include chart review (of history and glycemic control), discussion with primary physician and nurse (and often the dietician), and interview of the patient and/or family. This leads to development and implementation of a glycemic control plan. Clinician education is performed both as direct education of the primary physician at the time of intervention and as didactic sessions.

Outcomes

Physician Insulin Ordering

The numbers of patients receiving basal and short‐acting insulin were identified from the electronic medication record. Basal insulin included glargine and neutral protamine Hagerdorn (NPH). Short‐acting insulin (lispro or regular) could be ordered as scheduled prandial, prandial correction, or sliding scale. The distinction between prandial correction and sliding scale is that correction precedes meals exclusively and is not intended for use without food; in contrast, sliding scale is given regardless of food being consumed and is considered substandard. Quality insulin ordering is defined as having basal, prandial scheduled, and prandial correction doses.

In the electronic record, however, we were unable to distinguish the intent of short‐acting insulin orders in the larger data set. Thus, we reviewed a subset of 100 randomly selected charts (25 from each year from 2003 through 2006) to differentiate scheduled prandial, prandial correction, and sliding scale.

Hyperglycemia

Hyperglycemia was defined as glucose 180 mg/dL. The proportion of dysglycemic patients with hyperglycemia was calculated daily as the percent of dysglycemic patients with any 2 glucose levels 180 mg/dL. Daily values were averaged for quarterly measures.

Hypoglycemia

Hypoglycemia was defined as glucose <60 mg/dL. The proportion of all dysglycemic patients with hypoglycemia was calculated daily as the percent of dysglycemic patients with a single glucose level of <60 mg/dL. Daily values were averaged for quarterly measures.

Data Collection

Data were retrieved from electronic medical records, hospital administrative decision support, and risk‐adjusted5 UHC clinical database information. Glucose data were obtained from laboratory records (venous) and nursing data from bedside chemsticks (capillary).

Statistical Analyses

Data were analyzed using SAS 9.1 (SAS Institute, Cary, NC) and SPSS 13.0 (SPSS, Chicago, IL). The mean and standard deviation (SD) for continuous variables and proportions for categorical variables were calculated. Data were examined, plotted, and trended over time. Where applicable, linear regression trend lines were fitted and tested for statistical significance (P value <0.05).

Results

Patients

In total, 44,225 patients were identified from January 1, 2003 through December 31, 2006; 18,087 patients (41%) were classified as dysglycemic as defined by either: (1) receiving insulin or oral diabetic medicine; or (2) having a glucose level 125 mg/dL or <60 mg/dL. Characteristics of the population are outlined in Table 1. Both groups shared similar ethnic distributions. Across all 4 years, dysglycemic patients tended to be older and have a higher severity of illness. As an additional descriptor of severity of illness, UHC mean expected length of stay (LOS) and mean expected mortality (risk‐adjusted5) were higher for dysglycemic patients.

Characteristics of the Patient Population
Dysglycemic Euglycemic
  • Abbreviations: LOS, length of stay; SD, standard deviation; UHC, University HealthSystem Consortium.

  • UHC LOS and mortality are reported as additional descriptors of severity of illness.

Number of patients 18,088 26,144
Age (years, mean SD) 48.4 20.3 41.3 18.3
Gender, male (%) 64.7 62.7
Ethnicity (%)
Caucasian 68.2 70.1
African‐American/Black 11.0 12.0
Hispanic 6.8 6.2
Native American 1.8 18
Asian 7.9 5.5
Unknown 4.3 4.4
UHC severity of illness index (%)
Minor 18.3 38.8
Moderate 35.4 40.8
Major 29.5 16.7
Extreme 16.9 3.6
UHC expected LOS (days, mean SD)* 7.8 6.9 5.2 4.1
UHC expected mortality (mean SD)* 0.06 0.13 0.01 0.06

Physician Insulin Ordering

Ordering of both short‐acting and basal insulin increased (Figure 3). The ratio of short‐acting to basal orders decreased from 3.36 (1668/496) in 2003 to 1.97 (2226/1128) in 2006.

Figure 3
Percentage of dysglycemic patients receiving short‐acting and basal insulin.

Chart review of the 100 randomly selected dysglycemic patients revealed increased ordering of prandial correction dosing from 8% of patients in 2003 to 32% in 2006. Yet, only 1 patient in 2003 and only 2 in 2006 had scheduled prandial. Ordering of sliding scale insulin fell from 16% in 2003 to 4% in 2006.

Glycemic Control Outcomes

The percentage of dysglycemic patients with hyperglycemia ranged from 19 to 24 without significant decline over the 4 years (Figure 4A). The percentage of hypoglycemic dysglycemic patients was increasing from 2003 to 2004, but in the years following the interventions (2005 through 2006) this declined significantly (P = 0.003; Figure 4B). On average, the observed LOS was higher for dysglycemic vs. euglycemic patients (mean SD days: 9.4 12.2 and 5.8 8.5, respectively). The mean observed to expected mortality ratio was 0.45 0.08 and 0.44 0.17 for the dysglycemic and euglycemic patients, respectively. Over the 4 years no statistically significant change in observed LOS or adjusted mortality was found (data not shown).

Figure 4
(A) Hyperglycemia. Percent of dysglycemic patients with any 2 glucose levels greater than 180 mg/dL in a 24‐hour period. (B) Hypoglycemia. Percent of dysglycemic patients with a single glucose level less than 60 mg/dL in a 24‐hour period.

Conclusions

HMC, a safety net hospital with the highest UHC expected mortality of 131 hospitals nationwide, has demonstrated early successes in building its Glycemic Control Program, including: (1) decreased prescription of sliding scale; (2) a marked increase in prescription of basal insulin; and (3) significantly decreasing hypoglycemic events subsequent to the interventions. The decreased sliding scale and increased overall ordering of insulin could reflect increased awareness brought internationally through the literature and locally through our program. Two distinctive aspects of HMC's Glycemic Control Program, when compared to others,68 include: (1) the daily use of real‐time data to identify and target patients with out‐of‐range glucose levels; and (2) the coverage of all non‐critical‐care floors with a single clinician.

In 2003 and 2004, the increasing hypoglycemia we observed paralleled the international focus on aggressively treating hyperglycemia in the acute care setting. We observed a significant decrease in hypoglycemia in 2005 and 2006 that could be attributed to the education provided by the Glycemic Control Program and 2 features on the subcutaneous insulin order set: the prominent hypoglycemia protocol and the order hold prandial insulin if the patient cannot eat. These are similar features identified in a report on preventing hospital hypoglycemia.9 Additionally, hypoglycemia may have decreased secondary to the emphasis on not using short‐acting insulin at bedtime.

Despite increased and improved insulin ordering, we did not observe a significant change in the percent of dysglycemic patients with 2 glucose levels 180 mg/dL. In our program patients are identified for intervention after their glucose levels are out‐of‐range. To better evaluate the impact of our interventions on the glycemic control of each patient, we plan to analyze the glucose levels in the days following identification of patients. Alternatively, we could provide intervention to all patients with dysglycemia rather than waiting for glucoses to be out‐of‐range. Though this approach would require greater resources than the single clinician we currently employ.

Our early experience highlights areas for future evaluation and intervention. First, the lack of scheduled prandial insulin and that less than one‐third of dysglycemic patients have basal insulin ordered underscore a continued need to target quality insulin ordering to include all componentsbasal, scheduled prandial, and prandial correction. Second, while the daily report is a good rudimentary identification tool for at‐risk patients, it offers limited information as to the impact of our clinical intervention. Thus, refined evaluative metrics need be developed to prospectively assess the course of glycemic control for patients.

We acknowledge the limitations of this study. First, our most involved interventionthe addition of the clinical intervention teamcame only 6 months before the end of the study period. Second, this is an observational retrospective analysis and cannot distinguish confounders, such as physician preferences and decisions, that not easily quantified or controlled for. Third, our definition of dysglycemic incorporated 41% of non‐critical‐care patients, possibly reflecting too broad a definition.

In summary, we have described an inpatient Glycemic Control Program that relies on real‐time data to identify patients in need of intervention. Early in our program we observed improved insulin ordering quality and decreased rates of hypoglycemia. Future steps include evaluating the impact of our clinical intervention team and further refining glycemic control metrics to prospectively identify patients at risk for hyper‐ and hypoglycemia.

Acknowledgements

The authors thank Sofia Medvedev (UHC) and Derk B. Adams (HMC QI). The information contained in this article was based in part on the Clinical Data Products Data Base maintained by the UHC.

References
  1. Garber AJ,Moghissi ES,Bransome ED, et al.American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10(suppl 2):49.
  2. Clement S,Braithwaite SS,Magee MF, et al.Management of diabetes and hyperglycemia in hospitals.Diabetes Care.2004;27:553591.
  3. American College of Endocrinology and American Diabetes Association Consensus statement on inpatient diabetes and glycemic control.Diabetes Care.2006;29:19551962.
  4. University HealthSystem Consortium Mortality. Confidential Clinical Outcomes Report. Available at: http://www.uhc.edu. Accessed August2009 (Access with UHC permission only).
  5. Mortality risk adjustment for University HealthSystem Consortium's Clinical database. Available at: http://www.ahrq.gov/qual/mortality/Meurer.pdf. Accessed August2009.
  6. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12:491505.
  7. Korytkowski M,Dinardo M,Donihi AC,Bigi L,Devita M.Evolution of a diabetes inpatient safety committee.Endocr Pract.2006;12(suppl 3):9199.
  8. Newton CA,Young S.Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(suppl 3):4348.
  9. Braithwaite SS,Buie MM,Thompson CL, et al.Hospital hypoglycemia: not only treatment but also prevention.Endocr Pract.2004;10(suppl 2):8999.
References
  1. Garber AJ,Moghissi ES,Bransome ED, et al.American College of Endocrinology position statement on inpatient diabetes and metabolic control.Endocr Pract.2004;10(suppl 2):49.
  2. Clement S,Braithwaite SS,Magee MF, et al.Management of diabetes and hyperglycemia in hospitals.Diabetes Care.2004;27:553591.
  3. American College of Endocrinology and American Diabetes Association Consensus statement on inpatient diabetes and glycemic control.Diabetes Care.2006;29:19551962.
  4. University HealthSystem Consortium Mortality. Confidential Clinical Outcomes Report. Available at: http://www.uhc.edu. Accessed August2009 (Access with UHC permission only).
  5. Mortality risk adjustment for University HealthSystem Consortium's Clinical database. Available at: http://www.ahrq.gov/qual/mortality/Meurer.pdf. Accessed August2009.
  6. DeSantis AJ,Schmeltz LR,Schmidt K, et al.Inpatient management of hyperglycemia: the Northwestern experience.Endocr Pract.2006;12:491505.
  7. Korytkowski M,Dinardo M,Donihi AC,Bigi L,Devita M.Evolution of a diabetes inpatient safety committee.Endocr Pract.2006;12(suppl 3):9199.
  8. Newton CA,Young S.Financial implications of glycemic control: results of an inpatient diabetes management program.Endocr Pract.2006;12(suppl 3):4348.
  9. Braithwaite SS,Buie MM,Thompson CL, et al.Hospital hypoglycemia: not only treatment but also prevention.Endocr Pract.2004;10(suppl 2):8999.
Issue
Journal of Hospital Medicine - 4(7)
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Journal of Hospital Medicine - 4(7)
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Improving insulin ordering safely: The development of an inpatient glycemic control program
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Improving insulin ordering safely: The development of an inpatient glycemic control program
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