Mihaela S. Stefan, MD

Dyspnea, defined as a subjective experience of breathing discomfort,[1] is the seventh most frequent reason adult patients present to the emergency room and the most frequent cause for emergency room visits in patients 65 years or older.[2] Moreover, dyspnea is experienced by 49% of patients hospitalized with a medical condition[3, 4, 5] and by 70% of patients who are seriously ill.[6]

Based on evidence that patients are not treated consistently and effectively for relief of their shortness of breath, the American College of Chest Physicians (ACCP) statement on dyspnea management in patients with advanced lung or heart disease recommended that patients should be asked to rate their dyspnea, and the rating should be routinely documented in the medical record to guide management.[7] Although clinicians may question the utility of routine assessment of dyspnea using a standardized scale, studies have found that the prevalence of dyspnea reported from chart review is much lower than when patients are directly interviewed.[8] This may be the result of underrecognition of dyspnea or poor documentation by physicians, or that patients may not communicate their symptoms unless the physician specifically asks. As is the case with pain, routine assessment of dyspnea severity could lead to improved clinical management and greater patient‐centered care. However, unlike in the case of pain, regulatory bodies, such as the Joint Commission for Accreditation of Healthcare Organization, do not require routine dyspnea assessment.[9]

Currently, there are more than 40,000 hospitalists in the United States, and the vast majority of hospitals with >200 beds have a hospitalist group.[10] Hospitalists care for over 60% of inpatients[11] and play a major role in the management of patients with acute cardiopulmonary diseases. If standardized approaches for the assessment and documentation of dyspnea are to be implemented, hospitalists would be a key stakeholder group for utilizing enhanced clinical information about dyspnea. Therefore, we evaluated attitudes and practices of hospitalists in regard to the assessment and management of dyspnea, including the potential benefits and challenges related to the implementation of standardized assessment. We hypothesized that hospitalists would believe that a dyspnea scale for assessment of severity could improve their management of patients with cardiovascular diseases. Further, we hypothesized that physicians who agreed with the general statement that dyspnea is an important clinical problem would be more likely to believe that routine dyspnea assessment would be valuable.

METHODS

RESULTS

Overall, 178 (69.8%) of 255 identified hospitalists completed the survey, and all 9 participating hospitals had a response rate greater than 50%. The median number of years in practice was 6 (range, 038 years). A majority (77.5%) of respondents agreed with the statement that dyspnea is 1 of the major symptoms of patients with cardiopulmonary disease, and that its treatment is central to the management of these patients (77.0%) (Figure 1).

Figure 1

DISCUSSION

In this survey of 178 most hospitalists from a diverse group of 9 US hospitals, we found that most indicate that severity of dyspnea has a profound influence on their clinical practice (including their decision whether to intensify treatments such as diuretics or bronchodilators, to pursue additional diagnostic testing, add opioids or other nonpharmacological treatments) and ultimately their decision regarding the timing of hospital discharge. More importantly, whereas less than half reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.

Despite being a highly prevalent symptom in diverse patient populations, several studies have shown that documentation of dyspnea is sporadic and evaluation of dyspnea quality of care is not routinely performed.[13, 14, 15] Statements from a number of professional societies, including the ACCP, the American Thoracic Society and the Canadian Respiratory Society, recommend that dyspnea management should rely on patient reporting, and that dyspnea severity should be recorded.[1, 4, 7] Assessment is an essential step to guide interventions; however, simply asking about the presence or absence of dyspnea is insufficient.

Several rating scales have been validated and might be implementable in the acute care setting, including the Numerical Rating Scale and the Visual Assessment Scale.[16, 17, 18, 19, 20] Our survey shows that standardized documentation of dyspnea severity in clinical practice is uncommon. However, most hospitalists in our study believed that assessment of dyspnea, using a standardized scale, would positively impact their management of patients with cardiopulmonary disease.

There are a number of potential benefits of routine assessment of dyspnea in hospitalized patients. Implementation of a standardized approach to dyspnea measurement would result in more uniform assessment and documentation practices, and in turn greater awareness among members of the patient‐care team. Though not sufficient to improve care, measurement is necessary because physicians do not always recognize the severity of patients' dyspnea or may not recognize its presence. A retrospective study that assessed the prevalence of symptoms in 410 ambulatory patients showed that one‐quarter of patients had dyspnea, but only half of them told their doctor about it.[21] Two other studies of patients with cancer diagnoses found that 30%70% of patients had dyspnea, but the symptom was recognized in only half of them; even when recognized, dyspnea severity was frequently underrated by physicians.[21, 22] Importantly, underestimation appears to correlate with underutilization of symptomatic management of dyspnea.[8]

Although the results of our survey are encouraging, they highlight a number of potential barriers and misconceptions among hospitalists. For example, although dyspnea can be characterized only by the person experiencing it, only 42% of our survey respondents believed that patients are able to rate their dyspnea intensity on a scale. Some of these responses may be influenced by the fact that dyspnea scales are not currently available to patients under their care. Another explanation is that similar to the case for pain, some hospitalists may believe that patients will exaggerate dyspnea severity. Almost one‐third of the respondents stated that objective measures, such as respiratory rate or oxygen saturation, are more important than a patient's experience of dyspnea in guiding the treatment, and that dyspnea is a subjective symptom and not a vital sign itself. Hospitalists who appreciated the importance of dyspnea in clinical practice were more likely to support the implementation of a standardized dyspnea scale for dyspnea assessment.

Although the potential benefits of including routine measurement of dyspnea in standard hospital practice may seem obvious, evidence that implementing routine assessment improves patient care or outcomes is lacking. Even if hospitalists see the value of dyspnea assessment, asking nurses to collect and document additional information would represent a substantial change in hospital workflow. Finally, without specific protocols to guide care, it is unclear whether physicians will be able to use new information about dyspnea severity effectively. Future studies need to evaluate the impact of implementing routine dyspnea assessment on the management of patients with cardiopulmonary diseases including the use of evidence‐based interventions and reducing the use of less valuable care.

Most hospitalists agreed with the basic principles of dyspnea treatment in patients with advanced cardiopulmonary disease after the primary disease had been stabilized. Effective measures are available, and several guidelines endorse opioids in dyspnea management.[1, 4, 7] However, many clinicians are uncomfortable with this approach for dyspnea, and opioids remain underused. In our study, almost 90% of physicians recognized that concerns about respiratory depression limits opioids use as a treatment. A qualitative study that explored the physicians' perspective toward opioids showed that most physicians were reluctant to prescribe opioids for refractory dyspnea, describing a lack of related knowledge and experience, and fears related to the potential adverse effects. The findings of our study also outline the need to better educate residents and hospitalists on the assessment and management of dyspnea, including prescribing opioids for refractory dyspnea.[23]

CONCLUSIONS

The results of this survey suggest that most hospitalists believe that routine assessment of dyspnea severity would enhance their clinical decision making and improve patient care. Standardized assessment of dyspnea might result in better awareness of this symptom among providers, reduce undertreatment and mistreatment, and ultimately result in better outcomes for patients. However, implementation of the routine assessment of dyspnea would change current clinical practices and may have a significant effect on existing nursing and physician workflows. Additional research is needed to determine the feasibility and impact on outcomes of routine dyspnea assessment.

Dyspnea, defined as a subjective experience of breathing discomfort,[1] is the seventh most frequent reason adult patients present to the emergency room and the most frequent cause for emergency room visits in patients 65 years or older.[2] Moreover, dyspnea is experienced by 49% of patients hospitalized with a medical condition[3, 4, 5] and by 70% of patients who are seriously ill.[6]

Based on evidence that patients are not treated consistently and effectively for relief of their shortness of breath, the American College of Chest Physicians (ACCP) statement on dyspnea management in patients with advanced lung or heart disease recommended that patients should be asked to rate their dyspnea, and the rating should be routinely documented in the medical record to guide management.[7] Although clinicians may question the utility of routine assessment of dyspnea using a standardized scale, studies have found that the prevalence of dyspnea reported from chart review is much lower than when patients are directly interviewed.[8] This may be the result of underrecognition of dyspnea or poor documentation by physicians, or that patients may not communicate their symptoms unless the physician specifically asks. As is the case with pain, routine assessment of dyspnea severity could lead to improved clinical management and greater patient‐centered care. However, unlike in the case of pain, regulatory bodies, such as the Joint Commission for Accreditation of Healthcare Organization, do not require routine dyspnea assessment.[9]

Currently, there are more than 40,000 hospitalists in the United States, and the vast majority of hospitals with >200 beds have a hospitalist group.[10] Hospitalists care for over 60% of inpatients[11] and play a major role in the management of patients with acute cardiopulmonary diseases. If standardized approaches for the assessment and documentation of dyspnea are to be implemented, hospitalists would be a key stakeholder group for utilizing enhanced clinical information about dyspnea. Therefore, we evaluated attitudes and practices of hospitalists in regard to the assessment and management of dyspnea, including the potential benefits and challenges related to the implementation of standardized assessment. We hypothesized that hospitalists would believe that a dyspnea scale for assessment of severity could improve their management of patients with cardiovascular diseases. Further, we hypothesized that physicians who agreed with the general statement that dyspnea is an important clinical problem would be more likely to believe that routine dyspnea assessment would be valuable.

METHODS

RESULTS

Overall, 178 (69.8%) of 255 identified hospitalists completed the survey, and all 9 participating hospitals had a response rate greater than 50%. The median number of years in practice was 6 (range, 038 years). A majority (77.5%) of respondents agreed with the statement that dyspnea is 1 of the major symptoms of patients with cardiopulmonary disease, and that its treatment is central to the management of these patients (77.0%) (Figure 1).

Figure 1

DISCUSSION

In this survey of 178 most hospitalists from a diverse group of 9 US hospitals, we found that most indicate that severity of dyspnea has a profound influence on their clinical practice (including their decision whether to intensify treatments such as diuretics or bronchodilators, to pursue additional diagnostic testing, add opioids or other nonpharmacological treatments) and ultimately their decision regarding the timing of hospital discharge. More importantly, whereas less than half reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.

Despite being a highly prevalent symptom in diverse patient populations, several studies have shown that documentation of dyspnea is sporadic and evaluation of dyspnea quality of care is not routinely performed.[13, 14, 15] Statements from a number of professional societies, including the ACCP, the American Thoracic Society and the Canadian Respiratory Society, recommend that dyspnea management should rely on patient reporting, and that dyspnea severity should be recorded.[1, 4, 7] Assessment is an essential step to guide interventions; however, simply asking about the presence or absence of dyspnea is insufficient.

Several rating scales have been validated and might be implementable in the acute care setting, including the Numerical Rating Scale and the Visual Assessment Scale.[16, 17, 18, 19, 20] Our survey shows that standardized documentation of dyspnea severity in clinical practice is uncommon. However, most hospitalists in our study believed that assessment of dyspnea, using a standardized scale, would positively impact their management of patients with cardiopulmonary disease.

There are a number of potential benefits of routine assessment of dyspnea in hospitalized patients. Implementation of a standardized approach to dyspnea measurement would result in more uniform assessment and documentation practices, and in turn greater awareness among members of the patient‐care team. Though not sufficient to improve care, measurement is necessary because physicians do not always recognize the severity of patients' dyspnea or may not recognize its presence. A retrospective study that assessed the prevalence of symptoms in 410 ambulatory patients showed that one‐quarter of patients had dyspnea, but only half of them told their doctor about it.[21] Two other studies of patients with cancer diagnoses found that 30%70% of patients had dyspnea, but the symptom was recognized in only half of them; even when recognized, dyspnea severity was frequently underrated by physicians.[21, 22] Importantly, underestimation appears to correlate with underutilization of symptomatic management of dyspnea.[8]

Although the results of our survey are encouraging, they highlight a number of potential barriers and misconceptions among hospitalists. For example, although dyspnea can be characterized only by the person experiencing it, only 42% of our survey respondents believed that patients are able to rate their dyspnea intensity on a scale. Some of these responses may be influenced by the fact that dyspnea scales are not currently available to patients under their care. Another explanation is that similar to the case for pain, some hospitalists may believe that patients will exaggerate dyspnea severity. Almost one‐third of the respondents stated that objective measures, such as respiratory rate or oxygen saturation, are more important than a patient's experience of dyspnea in guiding the treatment, and that dyspnea is a subjective symptom and not a vital sign itself. Hospitalists who appreciated the importance of dyspnea in clinical practice were more likely to support the implementation of a standardized dyspnea scale for dyspnea assessment.

Although the potential benefits of including routine measurement of dyspnea in standard hospital practice may seem obvious, evidence that implementing routine assessment improves patient care or outcomes is lacking. Even if hospitalists see the value of dyspnea assessment, asking nurses to collect and document additional information would represent a substantial change in hospital workflow. Finally, without specific protocols to guide care, it is unclear whether physicians will be able to use new information about dyspnea severity effectively. Future studies need to evaluate the impact of implementing routine dyspnea assessment on the management of patients with cardiopulmonary diseases including the use of evidence‐based interventions and reducing the use of less valuable care.

Most hospitalists agreed with the basic principles of dyspnea treatment in patients with advanced cardiopulmonary disease after the primary disease had been stabilized. Effective measures are available, and several guidelines endorse opioids in dyspnea management.[1, 4, 7] However, many clinicians are uncomfortable with this approach for dyspnea, and opioids remain underused. In our study, almost 90% of physicians recognized that concerns about respiratory depression limits opioids use as a treatment. A qualitative study that explored the physicians' perspective toward opioids showed that most physicians were reluctant to prescribe opioids for refractory dyspnea, describing a lack of related knowledge and experience, and fears related to the potential adverse effects. The findings of our study also outline the need to better educate residents and hospitalists on the assessment and management of dyspnea, including prescribing opioids for refractory dyspnea.[23]

CONCLUSIONS

The results of this survey suggest that most hospitalists believe that routine assessment of dyspnea severity would enhance their clinical decision making and improve patient care. Standardized assessment of dyspnea might result in better awareness of this symptom among providers, reduce undertreatment and mistreatment, and ultimately result in better outcomes for patients. However, implementation of the routine assessment of dyspnea would change current clinical practices and may have a significant effect on existing nursing and physician workflows. Additional research is needed to determine the feasibility and impact on outcomes of routine dyspnea assessment.

Dyspnea, defined as a subjective experience of breathing discomfort,[1] is the seventh most frequent reason adult patients present to the emergency room and the most frequent cause for emergency room visits in patients 65 years or older.[2] Moreover, dyspnea is experienced by 49% of patients hospitalized with a medical condition[3, 4, 5] and by 70% of patients who are seriously ill.[6]

Based on evidence that patients are not treated consistently and effectively for relief of their shortness of breath, the American College of Chest Physicians (ACCP) statement on dyspnea management in patients with advanced lung or heart disease recommended that patients should be asked to rate their dyspnea, and the rating should be routinely documented in the medical record to guide management.[7] Although clinicians may question the utility of routine assessment of dyspnea using a standardized scale, studies have found that the prevalence of dyspnea reported from chart review is much lower than when patients are directly interviewed.[8] This may be the result of underrecognition of dyspnea or poor documentation by physicians, or that patients may not communicate their symptoms unless the physician specifically asks. As is the case with pain, routine assessment of dyspnea severity could lead to improved clinical management and greater patient‐centered care. However, unlike in the case of pain, regulatory bodies, such as the Joint Commission for Accreditation of Healthcare Organization, do not require routine dyspnea assessment.[9]

Currently, there are more than 40,000 hospitalists in the United States, and the vast majority of hospitals with >200 beds have a hospitalist group.[10] Hospitalists care for over 60% of inpatients[11] and play a major role in the management of patients with acute cardiopulmonary diseases. If standardized approaches for the assessment and documentation of dyspnea are to be implemented, hospitalists would be a key stakeholder group for utilizing enhanced clinical information about dyspnea. Therefore, we evaluated attitudes and practices of hospitalists in regard to the assessment and management of dyspnea, including the potential benefits and challenges related to the implementation of standardized assessment. We hypothesized that hospitalists would believe that a dyspnea scale for assessment of severity could improve their management of patients with cardiovascular diseases. Further, we hypothesized that physicians who agreed with the general statement that dyspnea is an important clinical problem would be more likely to believe that routine dyspnea assessment would be valuable.

METHODS

RESULTS

Overall, 178 (69.8%) of 255 identified hospitalists completed the survey, and all 9 participating hospitals had a response rate greater than 50%. The median number of years in practice was 6 (range, 038 years). A majority (77.5%) of respondents agreed with the statement that dyspnea is 1 of the major symptoms of patients with cardiopulmonary disease, and that its treatment is central to the management of these patients (77.0%) (Figure 1).

Figure 1

DISCUSSION

In this survey of 178 most hospitalists from a diverse group of 9 US hospitals, we found that most indicate that severity of dyspnea has a profound influence on their clinical practice (including their decision whether to intensify treatments such as diuretics or bronchodilators, to pursue additional diagnostic testing, add opioids or other nonpharmacological treatments) and ultimately their decision regarding the timing of hospital discharge. More importantly, whereas less than half reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.

Despite being a highly prevalent symptom in diverse patient populations, several studies have shown that documentation of dyspnea is sporadic and evaluation of dyspnea quality of care is not routinely performed.[13, 14, 15] Statements from a number of professional societies, including the ACCP, the American Thoracic Society and the Canadian Respiratory Society, recommend that dyspnea management should rely on patient reporting, and that dyspnea severity should be recorded.[1, 4, 7] Assessment is an essential step to guide interventions; however, simply asking about the presence or absence of dyspnea is insufficient.

Several rating scales have been validated and might be implementable in the acute care setting, including the Numerical Rating Scale and the Visual Assessment Scale.[16, 17, 18, 19, 20] Our survey shows that standardized documentation of dyspnea severity in clinical practice is uncommon. However, most hospitalists in our study believed that assessment of dyspnea, using a standardized scale, would positively impact their management of patients with cardiopulmonary disease.

There are a number of potential benefits of routine assessment of dyspnea in hospitalized patients. Implementation of a standardized approach to dyspnea measurement would result in more uniform assessment and documentation practices, and in turn greater awareness among members of the patient‐care team. Though not sufficient to improve care, measurement is necessary because physicians do not always recognize the severity of patients' dyspnea or may not recognize its presence. A retrospective study that assessed the prevalence of symptoms in 410 ambulatory patients showed that one‐quarter of patients had dyspnea, but only half of them told their doctor about it.[21] Two other studies of patients with cancer diagnoses found that 30%70% of patients had dyspnea, but the symptom was recognized in only half of them; even when recognized, dyspnea severity was frequently underrated by physicians.[21, 22] Importantly, underestimation appears to correlate with underutilization of symptomatic management of dyspnea.[8]

Although the results of our survey are encouraging, they highlight a number of potential barriers and misconceptions among hospitalists. For example, although dyspnea can be characterized only by the person experiencing it, only 42% of our survey respondents believed that patients are able to rate their dyspnea intensity on a scale. Some of these responses may be influenced by the fact that dyspnea scales are not currently available to patients under their care. Another explanation is that similar to the case for pain, some hospitalists may believe that patients will exaggerate dyspnea severity. Almost one‐third of the respondents stated that objective measures, such as respiratory rate or oxygen saturation, are more important than a patient's experience of dyspnea in guiding the treatment, and that dyspnea is a subjective symptom and not a vital sign itself. Hospitalists who appreciated the importance of dyspnea in clinical practice were more likely to support the implementation of a standardized dyspnea scale for dyspnea assessment.

Although the potential benefits of including routine measurement of dyspnea in standard hospital practice may seem obvious, evidence that implementing routine assessment improves patient care or outcomes is lacking. Even if hospitalists see the value of dyspnea assessment, asking nurses to collect and document additional information would represent a substantial change in hospital workflow. Finally, without specific protocols to guide care, it is unclear whether physicians will be able to use new information about dyspnea severity effectively. Future studies need to evaluate the impact of implementing routine dyspnea assessment on the management of patients with cardiopulmonary diseases including the use of evidence‐based interventions and reducing the use of less valuable care.

Most hospitalists agreed with the basic principles of dyspnea treatment in patients with advanced cardiopulmonary disease after the primary disease had been stabilized. Effective measures are available, and several guidelines endorse opioids in dyspnea management.[1, 4, 7] However, many clinicians are uncomfortable with this approach for dyspnea, and opioids remain underused. In our study, almost 90% of physicians recognized that concerns about respiratory depression limits opioids use as a treatment. A qualitative study that explored the physicians' perspective toward opioids showed that most physicians were reluctant to prescribe opioids for refractory dyspnea, describing a lack of related knowledge and experience, and fears related to the potential adverse effects. The findings of our study also outline the need to better educate residents and hospitalists on the assessment and management of dyspnea, including prescribing opioids for refractory dyspnea.[23]

CONCLUSIONS

The results of this survey suggest that most hospitalists believe that routine assessment of dyspnea severity would enhance their clinical decision making and improve patient care. Standardized assessment of dyspnea might result in better awareness of this symptom among providers, reduce undertreatment and mistreatment, and ultimately result in better outcomes for patients. However, implementation of the routine assessment of dyspnea would change current clinical practices and may have a significant effect on existing nursing and physician workflows. Additional research is needed to determine the feasibility and impact on outcomes of routine dyspnea assessment.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.

There are approximately 3 million cases of Clostridium difficile infection (CDI) per year in the United States.[1, 2, 3, 4] Of these, 10% result in a hospitalization or occur as a consequence of the exposures and treatments associated with hospitalization.[1, 2, 3, 4] Some patients with CDI experience mild diarrhea that is responsive to therapy, but other patients experience severe, life‐threatening disease that is refractory to treatment, leading to pseudomembranous colitis, toxic megacolon, and sepsis with a 60‐day mortality rate that exceeds 12%.[5, 6, 7, 8, 9, 10, 11, 12, 13, 14]

Hospital‐onset CDI (HOCDI), defined as C difficile‐associated diarrhea and related symptoms with onset more than 48 hours after admission to a healthcare facility,[15] represents a unique marriage of CDI risk factors.[5] A vulnerable patient is introduced into an environment that contains both exposure to C difficile (through other patients or healthcare workers) and treatment with antibacterial agents that may diminish normal flora. Consequently, CDI is common among hospitalized patients.[16, 17, 18] A particularly important group for understanding the burden of disease is patients who initially present to the hospital with sepsis and subsequently develop HOCDI. Sepsis patients are often critically ill and are universally treated with antibiotics.

Determining the incremental cost and mortality risk attributable to HOCDI is methodologically challenging. Because HOCDI is associated with presenting severity, the sickest patients are also the most likely to contract the disease. HOCDI is also associated with time of exposure or length of stay (LOS). Because LOS is a risk factor, comparing LOS between those with and without HOCDI will overestimate the impact if the time to diagnosis is not taken into account.[16, 17, 19, 20] We aimed to examine the impact of HOCDI in hospitalized patients with sepsis using a large, multihospital database with statistical methods that took presenting severity and time to diagnosis into account.

METHODS

RESULTS

We identified 486,943 adult sepsis admissions to a Premier hospital between July 1, 2004 and December 31, 2010. After applying all exclusion criteria, we had a final sample of 218,915 admissions with sepsis (from 400 hospitals) at risk for HOCDI (Figure 1). Of these, 2368 (1.08%) met criteria for diagnosis of CDI after hospital day 2 and were matched to controls using index date and propensity score.

Figure 1

Distribution by LOS, Index Day, and Risk for Mortality

The unadjusted and unmatched LOS was longer for cases than controls (19 days vs 8 days, Table 2) (see Supporting Figure 1 in the online version of this article). Approximately 90% of the patients had an index day of 14 or less (Figure 2). Among patients both with and without CDI, the unadjusted mortality risk increased as the index day (and thus the total LOS) increased.

Table 2.Comparison of Length of Stay, Mortality, and Costs for Propensity‐Matched Patients With and Without HOCDI

Outcome	HOCDI	No HOCDI	Difference (95% CI)	P
NOTE: Abbreviations: CI, confidence interval; HOCDI, hospital‐onset Clostridium difficile infection; RR, relative risk.
Length of stay, d
Raw results	19.2	8.3	8.4 (8.48.5)	<0.01
Raw results for survivors only	18.6	8.0	10.6 (10.311.0)	<0.01
Matched results	19.2	14.2	5.1(4.45.7)	<0.01
Matched results for survivors only	18.6	13.6	5.1 (4.45.8)	<0.01
Mortality, %
Raw results	24.0	10.1	13.9 (12.615.1), RR=2.4 (2.22.5)	<0.01
Matched results	24.0	15.4	8.6 (6.410.9), RR=1.6 (1.41.8)	<0.01
Costs, US$
Raw results median costs [interquartile range]	$26,187 [$15,117$46,273]	$9,988 [$6,296$17,351]	$16,190 ($15,826$16,555)	<0.01
Raw results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$9,429 [$6,070$15,875]	$14,620 ($14,246$14,996)	<0.01
Matched results [interquartile range]	$26,187 [$15,117$46,273]	$19,160 [$12,392$33,777]	$5,308 ($4,521$6,108)
Matched results for survivors only [interquartile range]	$24,038 [$14,169$41,654]	$17,811 [$11,614$29,298]	$4,916 ($4,088$5,768)	<0.01

Figure 2

Adjusted Results

Compared to patients without disease, HOCDI patients had an increased unadjusted mortality (24% vs 10%, P<0.001). This translates into a relative risk of 2.4 (95% confidence interval [CI]: 2.2, 2.5). In the matched cohort, the difference in the mortality rates was attenuated, but still significantly higher in the HOCDI patients (24% versus 15%, P<0.001, an absolute difference of 9%; 95% CI: 6.410.8). The adjusted relative risk of mortality for HOCDI was 1.6 (95% CI: 1.41.8; Table 2). After matching, patients with CDI had a LOS of 19.2 days versus 14.2 days in matched controls (difference of 5.1 days; 95% CI: 4.45.7; P<0.001). When the LOS analysis was limited to survivors only, this difference of 5 days remained (P<0.001). In an analysis limited to survivors only, the difference in median costs between cases and controls was $4916 (95% CI: $4088$5768; P<0.001). In a secondary analysis examining heterogeneity between HOCDI and outcomes across clinical subgroups, the absolute difference in mortality and costs between cases and controls varied across demographics, comorbidity, and ICU admission, but the relative risks were similar (Figure 3) (see Supporting Figure 3 in the online version of this article).

Figure 3

DISCUSSION

In this large cohort of patients with sepsis, we found that approximately 1 in 100 patients with sepsis developed HOCDI. Even after matching with controls based on the date of symptom onset and propensity score, patients who developed HOCDI were more than 1.6 times more likely to die in the hospital. HOCDI also added 5 days to the average hospitalization for patients with sepsis and increased median costs by approximately $5000. These findings suggest that a hospital that prevents 1 case of HOCDI per month in sepsis patients could avoid 1 death and 60 inpatient days annually, achieving an approximate yearly savings of $60,000.

Until now, the incremental cost and mortality attributable to HOCDI in sepsis patients have been poorly understood. Attributing outcomes can be methodologically challenging because patients who are at greatest risk for poor outcomes are the most likely to contract the disease and are at risk for longer periods of time. Therefore, it is necessary to take into account differences in severity of illness and time at risk between diseased and nondiseased populations and to ensure that outcomes attributed to the disease occur after disease onset.[28, 32] The majority of prior studies examining the impact of CDI on hospitalized patients have been limited by a lack of adequate matching to controls, small sample size, or failure to take into account time to infection.[16, 17, 19, 20]

A few studies have taken into account severity, time to infection, or both in estimating the impact of HOCDI. Using a time‐dependent Cox model that accounted for time to infection, Micek et al. found no difference in mortality but a longer LOS in mechanically ventilated patients (not limited to sepsis) with CDI.[33] However, their study was conducted at only 3 centers, did not take into account severity at the time of diagnosis, and did not clearly distinguish between community‐onset CDI and HOCDI. Oake et al. and Forster et al. examined the impact of CDI on patients hospitalized in a 2‐hospital health system in Canada.[12, 13] Using the baseline mortality estimate in a Cox multivariate proportional hazards regression model that accounted for the time‐varying nature of CDI, they found that HOCDI increased absolute risk of death by approximately 10%. Also, notably similar to our study were their findings that HOCDI occurred in approximately 1 in 100 patients and that the attributable median increase in LOS due to hospital‐onset CDI was 6 days. Although methodologically rigorous, these 2 small studies did not assess the impact of CDI on costs of care, were not focused on sepsis patients or even patients who received antibiotics, and also did not clearly distinguish between community‐onset CDI and HOCDI.

Our study therefore has important strengths. It is the first to examine the impact of HOCDI, including costs, on the outcomes of patients hospitalized with sepsis. The fact that we took into account both time to diagnosis and severity at the time of diagnosis (by using an index date for both cases and controls and determining severity on that date) prevented us from overestimating the impact of HOCDI on outcomes. The large differences in outcomes we observed in unadjusted and unmatched data were tempered after multivariate adjustment (eg, difference in LOS from 10.6 days to 5.1 additional days, costs from $14,620 to $4916 additional costs after adjustment). Our patient sample was derived from a large, multihospital database that contains actual hospital costs as derived from internal accounting systems. The fact that our study used data from hundreds of hospitals means that our estimates of cost, LOS, and mortality may be more generalizable than the work of Micek et al., Oake et al., and Forster et al.

This work also has important implications. First, hospital administrators, clinicians, and researchers can use our results to evaluate the cost‐effectiveness of HOCDI prevention measures (eg, hand hygiene programs, antibiotic stewardship). By quantifying the cost per case in sepsis patients, we allow administrators and researchers to compare the incremental costs of HOCDI prevention programs to the dollars and lives saved due to prevention efforts. Second, we found that our propensity model identified patients whose risk varied greatly. This suggests that an opportunity exists to identify subgroups of patients that are at highest risk. Identifying high‐risk subgroups will allow for targeted risk reduction interventions and the opportunity to reduce transmission (eg, by placing high‐risk patients in a private room). Finally, we have reaffirmed that time to diagnosis and presenting severity need to be rigorously addressed prior to making estimates of the impact of CDI burden and other hospital‐acquired conditions and injuries.

There are limitations to this study as well. We did not have access to microbiological data. However, we required a diagnosis code of CDI, evidence of testing, and treatment after the date of testing to confirm a diagnosis. We also adopted detailed exclusion criteria to ensure that CDI that was not present on admission and that controls did not have CDI. These stringent inclusion and exclusion criteria strengthened the internal validity of our estimates of disease impact. We used administrative claims data, which limited our ability to adjust for severity. However, the detailed nature of the database allowed us to use treatments, such as vasopressors and antibiotics, to identify cases; treatments were also used as a validated indicator of severity,[26] which may have helped to reduce some of this potential bias. Although our propensity model included many predictors of CDI, such as use of proton pump inhibitors and factors associated with mortality, not every confounder was completely balanced after propensity matching, although the statistical differences may have been related to our large sample size and therefore might not be clinically significant. We also may have failed to include all possible predictors of CDI in the propensity model.

In a large, diverse cohort of hospitalized patients with sepsis, we found that HOCDI lengthened hospital stay by approximately 5 days, increased risk of in‐hospital mortality by 9%, and increased hospital cost by approximately $5000 per patient. These findings highlight the importance of identifying effective prevention measures and of determining the patient populations at greatest risk for HOCDI.

Disclosures: The study was conducted with funding from the Division of Critical Care and the Center for Quality of Care Research at Baystate Medical Center. Dr. Lagu is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114745. Dr. Stefan is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number K01HL114631. Drs. Lagu and Lindenauer had full access to all of the data in the study; they take responsibility for the integrity of the data and the accuracy of the data analysis. Drs. Lagu, Lindenauer, Steingrub, Higgins, Stefan, Haessler, and Rothberg conceived of the study. Dr. Lindenauer acquired the data. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon analyzed and interpreted the data. Dr. Lagu drafted the manuscript. Drs. Lagu, Lindenauer, Rothberg, Steingrub, Nathanson, Stefan, Haessler, Higgins, and Mr. Hannon critically reviewed the manuscript for important intellectual content. Dr. Nathanson carried out the statistical analyses. Dr. Nathanson, through his company OptiStatim LLC, was paid by the investigators with funding from the Department of Medicine at Baystate Medical Center to assist in conducting the statistical analyses in this study. The authors report no further conflicts of interest.

Acute respiratory failure (ARF), a common and serious complication in hospitalized patients, may be caused by several conditions including pneumonia, chronic obstructive pulmonary disease (COPD), adult respiratory distress syndrome (ARDS), and congestive heart failure (CHF). Although ARF is conventionally defined by an arterial oxygen tension of <60 mm Hg, an arterial carbon dioxide tension of >45 mm Hg, or both, these thresholds serve as a guide to be used in combination with history and clinical assessment of the patient.[1, 2] Supplemental oxygen and treatment of the underlying cause is the mainstay of therapy for ARF, but in severe cases patients are treated with invasive mechanical ventilation (IMV) or noninvasive ventilation (NIV). ARF is the most frequent reason for admission to the intensive care unit (ICU)[3, 4] and has an in‐hospital mortality rate of 33% to 37% among those who require IMV.[5, 6] The majority of epidemiologic studies of ARF have been limited to patients requiring mechanical ventilation or those admitted to the ICU, and information about the characteristics and outcomes of patients across the full spectrum of severity is much more limited.[5, 7, 8, 9, 10, 11] General improvements in the management of underlying conditions, implementation of more effective ventilation strategies,[12, 13] and increasing use of NIV[14, 15] may have led to better outcomes for patients with ARF, yet empirical evidence of a change in the adjusted mortality rate over time is lacking.

The objective of this study was to provide a broad characterization of the epidemiology of ARF among adults hospitalized in the United States using a large nationally representative database. We sought to evaluate whether incidence, mortality, cost, or ventilation practice associated with ARF in the United States changed over the period of 2001 to 2009.

METHODS

RESULTS

Hospitalization Trends

The number of hospitalizations with an ARF diagnosis code increased at an average annual rate of 11.3% from 1,007,549 (standard deviation [SD] = 19,268) in 2001 to 1,917,910 (SD = 47,558) in 2009. More than two‐thirds of ARF admissions were associated with medical, rather than surgical, conditions (69.5% in 2001 and 71.2% in 2009). The median age, racial make‐up, and gender did not change significantly. Over the study period we observed an increase in ARF‐related hospitalizations in large, urban, teaching hospitals and in hospitals located in the Midwest (Table 1).

Table 1.Hospitalizations With Acute Respiratory Failure in the United States, 2001 to 2009, by Patient and Hospital Characteristics

	2001	2003	2005	2007	2009
NOTE: Abbreviations: ARF, acute respiratory failure; IMV, invasive mechanical ventilation; LOS, length of stay; NIV, noninvasive ventilation; SD, standard deviation; SE standard error. P value for trend <0.01, including all years 20012009, *P value for trend <0.0001, including all years 20012009. Adjusted for sex, age, race, hospital characteristics, and comorbidities. Geometric mean reported, standard errors from Taylor series expansion.
Patient characteristics
All, N (SD)	1,007,549 (19,268)	1,184,928 (25,542)	1,288,594 (30,493)	1,480,270 (32,002)	1,917,910 (47,558)
Age, mean (SE), y	66.6 (0.2)	66.0 (0.2)	66.1 (0.2)	65.8 (0.2)	65.8 (0.2)
Age group, %
1844	11.5	12.0	11.5	11.6	10.9
4564*	26.7	28.9	29.6	30.7	31.7
6584*	50.2	47.8	47.0	45.7	45.3
85+	11.5	11.4	11.9	12.0	12.1
Male*	48.1	48.2	48.6	49.3	49.2
Race
White	75.8	71.9	76.5	71.8	73.4
Black	12.7	13.6	11.2	14.2	12.5
Hispanic	7.2	9.8	7.7	8.5	7.8
Other	4.2	4.7	4.7	5.5	6.3
Primary ARF	20.7	20.9	25.9	26.1	19.9
Secondary ARF	79.3	79.1	74.1	73.9	80.1
Medical*	69.5	69.1	69.9	70.2	71.2
Surgical*	30.5	30.8	30.1	29.8	28.8
Hospital characteristics, %
Number of beds
Small	10.0	10.1	10.5	10.8	11.3
Medium	25.2	25.3	24.6	24.0	22.7
Large	64.7	64.6	64.9	65.2	66.0
Region
South*	18.5	18.5	17.6	17.0	16.3
Midwest	21.4	22.0	23.6	23.2	23.5
Northeast	42.6	41.7	41.4	42.2	42.1
West*	17.5	17.8	17.3	17.6	18.1
Hospital type
Rural	13.6	13.0	11.8	11.0	10.8
Urban nonteaching	45.5	44.5	50.1	45.3	45.7
Urban teaching	40.9	42.5	38.1	43.7	43.6
Patient outcomes
Ventilation strategy
IMV*	48.5	48.4	47.5	46.5	42.1
NIV*	3.8	5.3	6.9	9.4	10.1
IMV or NIV	50.9	51.7	52.1	52.9	49.7
Disposition
Home/home healthcare*	42.1	43.8	42.8	43.4	45.7
Transfer to acute care	5.2	4.7	4.6	4.6	4.4
Nursing facility*	24.4	24.9	27.4	28.6	29.0
Other	0.7	0.8	0.9	0.9	1.0
Adjusted mortality, % (SE)*	27.6 (0.3)	26.4 (0.4)	24.9 (0.4)	22.7 (0.4)	20.6 (0.3)
Adjusted mean, LOS/case, d (SE)*	7.8 (0.1)	7.9 (0.1)	7.7 (0.1)	7.5 (0.1)	7.1 (0.1)
Adjusted mean cost/case, 2009 US$, (SE)	15,818 (251)	16,981 (419)	17,236 (411)	16,941 (436)	15,987 (402)

After adjusting for age and sex, the population incidence of ARF increased from 502 (standard error [SE] = 10) cases per 100,000 in 2001 to 784 (SE = 19) cases per 100,000 in 2009 (a 56% increase, P < 0.0001). Hispanics had the lowest rates of ARF, with both black and white groups having similar rates (Table 2).

Table 2.Cases of Acute Respiratory Failure per 100,000 Population

	2001	2003	2005	2007	2009
NOTE: Data are presented as number per 100,000 population (standard error), standardized to 2000 US Census population. *P value for trend < 0.0001, including all years 2001 to 2009.
All*	502 (10)	569 (12)	595 (14)	627 (14)	784 (19)
Age group
1844*	107 (3)	130 (4)	137 (4)	153 (5)	189 (6)
4564*	422 (9)	500 (12)	521 (13)	580 (14)	739 (19)
6584*	1697 (35)	1863 (42)	1950 (50)	2066 (46)	2578 (69)
85+	3449 (86)	3792 (106)	3981 (120)	3429 (97)	4163 (123)
Sex
Male*	491 (10)	553 (13)	582 (14)	629 (14)	782 (20)
Female*	512 (10)	583 (12)	607 (15)	625 (13)	786 (19)
Race/ethnicity
White*	398 (11)	427 (12)	466 (16)	450 (13)	699 (21)
Black*	423 (27)	513 (33)	432 (26)	574 (38)	738 (37)
Hispanic*	247 (24)	381 (42)	307 (27)	353 (34)	478 (42)
Other*	268 (20)	342 (29)	347 (26)	424 (29)	713 (77)
In‐hospital mortality	140 (3)	148 (3)	146 (3)	140 (3)	154 (4)

The most common etiologies of ARF among medical patients were pneumonia, CHF, ARDS, COPD exacerbation, and sepsis. Over the 9‐year study, the proportion of cases secondary to pneumonia and sepsis rose significantly: from 39% to 46% and 13% to 21%, respectively (Figure 1).

Figure 1

2009 Data Analysis

In 2009 the 1,917,910 hospitalizations with ARF resulted in 381,155 (SD = 8965) deaths and a total inpatient cost of $54 billion. The most common etiologies in patients over 65 years old were pneumonia, CHF, COPD, ARDS, and sepsis. In patients younger than 45 years the most frequent diagnoses were pneumonia, ARDS, sepsis, asthma, drug ingestion, and trauma. Stratified analysis by gender and by age groups showed that mortality rates among men were higher than for women and were highest in patients older than 85 years (Table 3).

Table 3.Characteristics of Hospitalizations by Etiology (Medical, Surgical, Comorbidities, Procedures) in 2009

Disease	Total	Age <45 Years	4565 Years	6584 Years	85+ Years	Male	Female
NOTE: One patient can have more than 1 diagnosis. Abbreviations: AMI, acute myocardial infarction; ARDS, adult respiratory distress syndrome; CHF, congestive heart failure; CI, confidence interval; COPD, chronic obstructive pulmonary disease; IMV, invasive mechanical ventilation; NIV, noninvasive ventilation. *P < 0.0001 for age group. P < 0.0001 for gender. The P values are not from Rao‐Scott 2 test.
Medical
Total, N (%)	1,364,624 (71.2)	144,715 (10.6)	416,922 (30.6)	615,009 (45.1)	187,977 (13.8)	647,894 (47.5)	716,635 (52.5)
Pneumonia, %*	46.1	41.7	42.8	46.9	54.3	48.8	43.7
CHF, %*	36.6	10.4	27.3	43.6	54.8	35.0	38.1
ARDS, %*	16.1	22.9	16.2	14.5	15.9	15.5	16.7
Sepsis, %*	21.2	18.1	21.3	21.3	23.1	22.8	19.8
COPD, %*	25.4	4.2	25.6	32.3	18.3	25.0	25.7
AMI, %*	9.0	2.6	7.1	10.5	13.3	9.3	8.8
Asthma, %*	9.2	18.1	11.6	6.7	5.4	6.2	12.0
Stroke, %*	4.8	2.3	4.1	5.5	6.0	5.0	4.7
Trauma or burns, %*	3.4	5.4	2.9	3.0	4.1	4.3	2.5
Cardiorespiratory arrest, %*	4.1	3.9	4.4	4.1	3.8	4.6	3.7
Drug, %*	3.7	16.6	5.1	0.8	0.3	3.8	3.6
IMV, %*	37.7	54.6	43.7	33.5	24.8	41.1	34.5
NIV, %*	11.9	7.1	11.5	13.0	12.7	11.4	12.3
In‐hospital mortality (CI)	22 (21.322.7)	12.9 (11.913.9)	18.5 (17.619.4)	23.9 (23.024.9)	31.8 (30.633.1)	24.2 (23.325.1)	20.9 (20.121.7)
Surgical
Total, N (%)	552971 (28.8)	64983 (11.8)	190225 (34.4)	254336 (46)	43426 (7.9)	295660 (53.5)	257287 (46.5)
Pneumonia, %*	34.9	33.0	34.0	35.0	40.5	37.1	32.2
CHF, %*	27.2	8.9	21.7	33.3	42.6	26.7	27.7
ARDS, %*	45.5	51.5	45.2	44.7	42.7	45.0	46.1
Sepsis, %*	25.1	22.8	25.4	25.2	26.1	25.4	24.7
COPD, %*	8.2	1.1	7.4	10.8	7.5	8.3	8.1
AMI, %*	16.9	4.9	17.0	19.8	17.9	19.1	14.4
Asthma, %*	6.1	7.6	7.2	5.4	3.6	4.1	8.5
Stroke, %*	8.9	6.6	9.2	9.4	7.2	8.9	8.8
Trauma or burns, %*	12.2	26.5	9.6	9.2	20.3	13.8	10.4
Cardiorespiratory arrest, %*	5.5	4.4	6.0	5.4	5.2	6.1	4.7
Drug, %*	0.5	1.3	0.7	0.2	0.2	0.4	0.6
IMV, %*	52.9	57.1	54.3	51.3	50.0	54.5	51.0
NIV, %*	5.8	3.5	5.5	6.4	6.4	5.6	6.0
In‐hospital mortality, % (CI)	18.6 (17.819.5)	10.7 (9.312.0)	15.5 (14.216.8)	20.8 (19.821.9)	29.4 (27.831.1)	19.0 (18.219.8)	18.3 (17.319.2)

When we examined ventilation practices among medical patients we found that patients older than 85 years, when compared to patients younger than 45 years, were less likely to be treated with IMV (25% vs 55%) and more likely to be treated with NIV (12.7% vs 7%). At the same time, the average cost per case was lowest among patients 85 years and older, and hospital costs per case fell sharply after age 70 years. Costs were considerably higher for those who did not survive during hospitalization, particularly for patients younger than 45 years (Figure 2).

Figure 2

DISCUSSION

In this large population‐based study, we found that the number of hospitalizations associated with a diagnosis of ARF almost doubled over a 9‐year period. In 2009 there were nearly 2 million hospitalizations with ARF in the United States, resulting in approximately 380,000 deaths and inpatient costs of over $54 billion. The population‐adjusted ARF hospitalization rates increased in all age groups, and patients 85 years and older had the highest age‐specific hospitalization rate. Although overall rates of mechanical ventilation (NIV or IMV) remained stable over the 9‐year period, there was an important shift away from IMV (which decreased from 48% in 2001 to 42% in 2009) toward NIV (which increased from 4% in 2001 to 10% in 2009). Overall, there was a significant increase in the number of total deaths despite a decline in adjusted in‐hospital mortality rates. In‐hospital mortality rates decreased for all cases of ARF regardless of ventilation choice.

The findings of this study mirror results of others that have shown that although the incidence of critical care illnesses like sepsis[17, 20, 21, 26] and acute renal failure[27] has increased over the last decade, in‐hospital mortality rates have decreased.[20, 21, 28] Our results also compliment the results of a recent study that looked at hospitalizations for noncardiogenic ARF, which observed a 3.7‐fold increase in the number of cases and a steady decline in case fatality.[11]

Most prior studies addressing the incidence of ARF have included only patients receiving mechanical ventilation. In 1994, the estimated number of cases of ARF requiring IMV was 329,766,[9] which increased to 790,257 in 2005.[10] In our study we found that in 2009, the number of patients with ARF hospitalizations with IMV increased to 806,538. The increase in the overall number of cases with ARF was mainly driven by a surge in cases of sepsis and pneumonia. Our findings are consistent with national trends over time in noncardiogenic ARF[11] and in conditions that predispose patients to ARF such as sepsis[17, 20, 28] and acute renal failure.[27] As the number of claims for ARF doubled and the number of deaths increased, we found that adjusted hospital mortality improved from 27.6% in 2001 to 20.6% in 2009. This decline in hospital mortality was observed among all patients groups, regardless of ventilation choice. The decline in overall case fatality is consistent with prior findings in noncardiogenic ARF,[11] sepsis,[17, 28] and CHF.[29]

There are a number of potential explanations for the reduction in mortality observed over the study period, including improvements in hospital management of the underlying conditions leading to ARF, an increase in the proportion of patients being treated with NIV,[30] and advances in the care of critically ill patients such as the use of low‐tidal volume ventilation.[31, 32] Another contributor may be an increase in the proportion of discharges to nursing facilities, although this change in discharge disposition cannot fully explain our findings. For example, from 2007 to 2009, mortality decreased by 2 percentage points, and nursing home discharges increased by only 0.4 percentage points. Growth and aging of the US population only partially explain the increase we observed in the incidence of ARF, as age‐ and sex‐adjusted population rates increased by 56% from 2001 to 2009. In addition, the NIS captures data on hospital discharges and not individual patients; thus, a patient may have had multiple admissions. Over the last decade adoption of a more intensive practice style has been associated with improved in‐hospital mortality,[33, 34] and although these patients may be living longer they may have multiple readmissions.[35, 36]

We also observed that older patients were less likely to be treated with IMV, had a higher mortality rate, and less expensive care. These results are consistent with other studies and suggest that the intensity of treatment decreases with increasing age, and decisions to withhold or withdraw life‐supporting treatments are more frequent in the elderly.[26, 37] Prior research has shown that severity of illness is more important than age on patients' prognosis,[38, 39] and aggressive treatment strategies are not less cost‐effective when provided to older patients.[40]

Another important finding of this study is the marked increase in the use of NIV paired with a modest reduction in the use of IMV in the treatment of patients with ARF. This finding adds to evidence from other studies, which have similarly reported a dramatic increase in the use of NIV and a decrease in the use of IMV in patients with COPD as well as in ARF of other etiologies.[30, 41]

Our work has several limitations. First, we identified ARF based on ICD‐9‐CM codes and therefore cannot exclude disease misclassification. We did not find any studies in the literature addressing the accuracy and the completeness of ARF coding. However, we employed the same codes used to define ARF as has been used to define organ dysfunction in studies of severe sepsis,[17, 20] and the ICD‐9‐CM codes that we used to identify cases of ARDS have been used in prior studies.[11, 22, 23] Another limitation is that it is not clear to what extent the trends we observed may be due to changes over time in documentation and coding practices. Although this should be considered given the additional reimbursement associated with the diagnosis of ARF, our observation that rates of assisted ventilation have remained almost flat over the 9‐year period of the study suggest that would not wholly account for the rise in ARF. Second, because we did not have access to physiological data such as results of blood gas testing, we could not determine whether the threshold for applying the diagnosis of ARF or for delivering ventilatory support has changed over time. Third, for the purpose of this study we employed a broad definition of ARF, not limiting cases to those requiring mechanical ventilation, and this led to a more heterogeneous cohort including less severe cases of ARF. However, this is not dissimilar to the heterogeneity in disease severity observed among patients who receive a diagnosis of heart failure or acute renal failure. Fourth, survivors of ARF remain at high risk of death in the months after hospitalization,[42] but we assessed only in‐hospital mortality. It is possible that although in‐hospital mortality has improved, 30‐day mortality remained stable. Finally, as the NIS contains only discharge‐level data, we could not distinguish between patients admitted for ARF from those who developed ARF (potentially iatrogenic) after admission.

In summary, over the period of 2001 to 2009, there was a large increase in the number of patients given a diagnosis of ARF and a concomitant reduction in inpatient mortality. Although rates of mechanical ventilation remained relatively constant, there was a significant shift toward greater use of NIV at the expense of IMV.

Acute respiratory failure (ARF), a common and serious complication in hospitalized patients, may be caused by several conditions including pneumonia, chronic obstructive pulmonary disease (COPD), adult respiratory distress syndrome (ARDS), and congestive heart failure (CHF). Although ARF is conventionally defined by an arterial oxygen tension of <60 mm Hg, an arterial carbon dioxide tension of >45 mm Hg, or both, these thresholds serve as a guide to be used in combination with history and clinical assessment of the patient.[1, 2] Supplemental oxygen and treatment of the underlying cause is the mainstay of therapy for ARF, but in severe cases patients are treated with invasive mechanical ventilation (IMV) or noninvasive ventilation (NIV). ARF is the most frequent reason for admission to the intensive care unit (ICU)[3, 4] and has an in‐hospital mortality rate of 33% to 37% among those who require IMV.[5, 6] The majority of epidemiologic studies of ARF have been limited to patients requiring mechanical ventilation or those admitted to the ICU, and information about the characteristics and outcomes of patients across the full spectrum of severity is much more limited.[5, 7, 8, 9, 10, 11] General improvements in the management of underlying conditions, implementation of more effective ventilation strategies,[12, 13] and increasing use of NIV[14, 15] may have led to better outcomes for patients with ARF, yet empirical evidence of a change in the adjusted mortality rate over time is lacking.

The objective of this study was to provide a broad characterization of the epidemiology of ARF among adults hospitalized in the United States using a large nationally representative database. We sought to evaluate whether incidence, mortality, cost, or ventilation practice associated with ARF in the United States changed over the period of 2001 to 2009.

METHODS

RESULTS