Jerry A. Krishnan, MD, PhD

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.

Chronic obstructive pulmonary disease (COPD) affects as many as 24 million individuals in the United States, is responsible for more than 700,000 annual hospital admissions, and is currently the nation's third leading cause of death, accounting for nearly $49.9 billion in medical spending in 2010.[1, 2] Reported in‐hospital mortality rates for patients hospitalized for exacerbations of COPD range from 2% to 5%.[3, 4, 5, 6, 7] Information about 30‐day mortality rates following hospitalization for COPD is more limited; however, international studies suggest that rates range from 3% to 9%,[8, 9] and 90‐day mortality rates exceed 15%.[10]

Despite this significant clinical and economic impact, there have been no large‐scale, sustained efforts to measure the quality or outcomes of hospital care for patients with COPD in the United States. What little is known about the treatment of patients with COPD suggests widespread opportunities to increase adherence to guideline‐recommended therapies, to reduce the use of ineffective treatments and tests, and to address variation in care across institutions.[5, 11, 12]

Public reporting of hospital performance is a key strategy for improving the quality and safety of hospital care, both in the United States and internationally.[13] Since 2007, the Centers for Medicare and Medicaid Services (CMS) has reported hospital mortality rates on the Hospital Compare Web site, and COPD is 1 of the conditions highlighted in the Affordable Care Act for future consideration.[14] Such initiatives rely on validated, risk‐adjusted performance measures for comparisons across institutions and to enable outcomes to be tracked over time. We present the development, validation, and results of a model intended for public reporting of risk‐standardized mortality rates for patients hospitalized with exacerbations of COPD that has been endorsed by the National Quality Forum.[15]

METHODS

RESULTS

Model Derivation

After exclusions were applied, the development sample included 150,035 admissions in 2008 at 4537 US hospitals (Figure 1). Factors that were most strongly associated with the risk of mortality included metastatic cancer (odds ratio [OR] 2.34), protein calorie malnutrition (OR 2.18), nonmetastatic cancers of the lung and upper digestive tract, (OR 1.80) cardiorespiratory failure and shock (OR 1.60), and congestive heart failure (OR 1.34) (Table 2).

Figure 1

Hospital Risk‐Standardized Mortality Rates

The mean unadjusted hospital 30‐day mortality rate was 8.6% and ranged from 0% to 100% (Figure 2a). Risk‐standardized mortality rates varied across hospitals (Figure 2b). The mean risk‐standardized mortality rate was 8.6% and ranged from 5.9% to 13.5%. The odds of mortality at a hospital 1 standard deviation above average was 1.20 times that of a hospital 1 standard deviation below average.

Figure 2

DISCUSSION

We present a hospital‐level risk‐standardized mortality measure for patients admitted with COPD based on administrative claims data that are intended for public reporting and that have achieved endorsement by the National Quality Forum, a voluntary consensus standards‐setting organization. Across more than 4500 US hospitals, the mean 30‐day risk‐standardized mortality rate in 2008 was 8.6%, and we observed considerable variation across institutions, despite adjustment for case mix, suggesting that improvement by lower‐performing institutions may be an achievable goal.

Although improving the delivery of evidence‐based care processes and outcomes of patients with acute myocardial infarction, heart failure, and pneumonia has been the focus of national quality improvement efforts for more than a decade, COPD has largely been overlooked.[23] Within this context, this analysis represents the first attempt to systematically measure, at the hospital level, 30‐day all‐cause mortality for patients admitted to US hospitals for exacerbation of COPD. The model we have developed and validated is intended to be used to compare the performance of hospitals while controlling for differences in the pretreatment risk of mortality of patients and accounting for the clustering of patients within hospitals, and will facilitate surveillance of hospital‐level risk‐adjusted outcomes over time.

In contrast to process‐based measures of quality, such as the percentage of patients with pneumonia who receive appropriate antibiotic therapy, performance measures based on patient outcomes provide a more comprehensive view of care and are more consistent with patients' goals.[24] Additionally, it is well established that hospital performance on individual and composite process measures explains only a small amount of the observed variation in patient outcomes between institutions.[25] In this regard, outcome measures incorporate important, but difficult to measure aspects of care, such as diagnostic accuracy and timing, communication and teamwork, the recognition and response to complications, care coordination at the time of transfers between levels of care, and care settings. Nevertheless, when used for making inferences about the quality of hospital care, individual measures such as the risk‐standardized hospital mortality rate should be interpreted in the context of other performance measures, including readmission, patient experience, and costs of care.

A number of prior investigators have described the outcomes of care for patients hospitalized with exacerbations of COPD, including identifying risk factors for mortality. Patil et al. carried out an analysis of the 1996 Nationwide Inpatient Sample and described an overall in‐hospital mortality rate of 2.5% among patients with COPD, and reported that a multivariable model containing sociodemographic characteristics about the patient and comorbidities had an area under the ROC curve of 0.70.[3] In contrast, this hospital‐level measure includes patients with a principal diagnosis of respiratory failure and focuses on 30‐day rather than inpatient mortality, accounting for the nearly 3‐fold higher mortality rate we observed. In a more recent study that used clinical from a large multistate database, Tabak et al. developed a prediction model for inpatient mortality for patients with COPD that contained only 4 factors: age, blood urea nitrogen, mental status, and pulse, and achieved an area under the ROC curve of 0.72.[4] The simplicity of such a model and its reliance on clinical measurements makes it particularly well suited for bedside application by clinicians, but less valuable for large‐scale public reporting programs that rely on administrative data. In the only other study identified that focused on the assessment of hospital mortality rates, Agabiti et al. analyzed the outcomes of 12,756 patients hospitalized for exacerbations of COPD, using similar ICD‐9‐CM diagnostic criteria as in this study, at 21 hospitals in Rome, Italy.[26] They reported an average crude 30‐day mortality rate of 3.8% among a group of 5 benchmark hospitals and an average mortality of 7.5% (range, 5.2%17.2%) among the remaining institutions.

To put the variation we observed in mortality rates into a broader context, the relative difference in the risk‐standardized hospital mortality rates across the 10th to 90th percentiles of hospital performance was 25% for acute myocardial infarction and 39% for heart failure, whereas rates varied 30% for COPD, from 7.6% to 9.9%.[27] Model discrimination in COPD (C statistic, 0.72) was also similar to that reported for models used for public reporting of hospital mortality in acute myocardial infarction (C statistic, 0.71) and pneumonia (C statistic, 0.72).

This study has a number of important strengths. First, the model was developed from a large sample of recent Medicare claims, achieved good discrimination, and was validated in samples not limited to Medicare beneficiaries. Second, by including patients with a principal diagnosis of COPD, as well as those with a principal diagnosis of acute respiratory failure when accompanied by a secondary diagnosis of COPD with acute exacerbation, this model can be used to assess hospital performance across the full spectrum of disease severity. This broad set of ICD‐9‐CM codes used to define the cohort also ensures that efforts to measure hospital performance will be less influenced by differences in documentation and coding practices across hospitals relating to the diagnosis or sequencing of acute respiratory failure diagnoses. Moreover, the inclusion of patients with respiratory failure is important because these patients have the greatest risk of mortality, and are those in whom efforts to improve the quality and safety of care may have the greatest impact. Third, rather than relying solely on information documented during the index admission, we used ambulatory and inpatient claims from the full year prior to the index admission to identify comorbidities and to distinguish them from potential complications of care. Finally, we did not include factors such as hospital characteristics (eg, number of beds, teaching status) in the model. Although they might have improved overall predictive ability, the goal of the hospital mortality measure is to enable comparisons of mortality rates among hospitals while controlling for differences in patient characteristics. To the extent that factors such as size or teaching status might be independently associated with hospital outcomes, it would be inappropriate to adjust away their effects, because mortality risk should not be influenced by hospital characteristics other than through their effects on quality.

These results should be viewed in light of several limitations. First, we used ICD‐9‐CM codes derived from claims files to define the patient populations included in the measure rather than collecting clinical or physiologic information prospectively or through manual review of medical records, such as the forced expiratory volume in 1 second or whether the patient required long‐term oxygen therapy. Nevertheless, we included a broad set of potential diagnosis codes to capture the full spectrum of COPD exacerbations and to minimize differences in coding across hospitals. Second, because the risk‐adjustment included diagnoses coded in the year prior to the index admission, it is potentially subject to bias due to regional differences in medical care utilization that are not driven by underlying differences in patient illness.[28] Third, using administrative claims data, we observed some paradoxical associations in the model that are difficult to explain on clinical grounds, such as a protective effect of substance and alcohol abuse or prior episodes of respiratory failure. Fourth, although we excluded patients from the analysis who were enrolled in hospice prior to, or on the day of, the index admission, we did not exclude those who choose to withdraw support, transition to comfort measures only, or enrolled in hospice care during a hospitalization. We do not seek to penalize hospitals for being sensitive to the preferences of patients at the end of life. At the same time, it is equally important that the measure is capable of detecting the outcomes of suboptimal care that may in some instances lead a patient or their family to withdraw support or choose hospice. Finally, we did not have the opportunity to validate the model against a clinical registry of patients with COPD, because such data do not currently exist. Nevertheless, the use of claims as a surrogate for chart data for risk adjustment has been validated for several conditions, including acute myocardial infarction, heart failure, and pneumonia.[29, 30]

CONCLUSIONS

Risk‐standardized 30‐day mortality rates for Medicare beneficiaries with COPD vary across hospitals in the US. Calculating and reporting hospital outcomes using validated performance measures may catalyze quality improvement activities and lead to better outcomes. Additional research would be helpful to confirm that hospitals with lower mortality rates achieve care that meets the goals of patients and their families better than at hospitals with higher mortality rates.

Disclosures

Peter K. Lindenauer, MD, MSc, is the guarantor of this article, taking responsibility for the integrity of the work as a whole, from inception to published article, and takes responsibility for the content of the manuscript, including the data and data analysis. All authors have made substantial contributions to the conception and design, or acquisition of data, or analysis and interpretation of data; have drafted the submitted article or revised it critically for important intellectual content; and have provided final approval of the version to be published. Preparation of this manuscript was completed under Contract Number: HHSM‐5002008‐0025I/HHSM‐500‐T0001, Modification No. 000007, Option Year 2 Measure Instrument Development and Support (MIDS). Sponsors did not contribute to the development of the research or manuscript. Dr. Au reports being an unpaid research consultant for Bosch Inc. He receives research funding from the NIH, Department of Veterans Affairs, AHRQ, and Gilead Sciences. The views of the this manuscript represent the authors and do not necessarily represent those of the Department of Veterans Affairs. Drs. Drye and Bernheim report receiving contract funding from CMS to develop and maintain quality measures.

Chronic obstructive pulmonary disease (COPD) affects as many as 24 million individuals in the United States, is responsible for more than 700,000 annual hospital admissions, and is currently the nation's third leading cause of death, accounting for nearly $49.9 billion in medical spending in 2010.[1, 2] Reported in‐hospital mortality rates for patients hospitalized for exacerbations of COPD range from 2% to 5%.[3, 4, 5, 6, 7] Information about 30‐day mortality rates following hospitalization for COPD is more limited; however, international studies suggest that rates range from 3% to 9%,[8, 9] and 90‐day mortality rates exceed 15%.[10]

Despite this significant clinical and economic impact, there have been no large‐scale, sustained efforts to measure the quality or outcomes of hospital care for patients with COPD in the United States. What little is known about the treatment of patients with COPD suggests widespread opportunities to increase adherence to guideline‐recommended therapies, to reduce the use of ineffective treatments and tests, and to address variation in care across institutions.[5, 11, 12]

Public reporting of hospital performance is a key strategy for improving the quality and safety of hospital care, both in the United States and internationally.[13] Since 2007, the Centers for Medicare and Medicaid Services (CMS) has reported hospital mortality rates on the Hospital Compare Web site, and COPD is 1 of the conditions highlighted in the Affordable Care Act for future consideration.[14] Such initiatives rely on validated, risk‐adjusted performance measures for comparisons across institutions and to enable outcomes to be tracked over time. We present the development, validation, and results of a model intended for public reporting of risk‐standardized mortality rates for patients hospitalized with exacerbations of COPD that has been endorsed by the National Quality Forum.[15]

METHODS

RESULTS

Model Derivation

After exclusions were applied, the development sample included 150,035 admissions in 2008 at 4537 US hospitals (Figure 1). Factors that were most strongly associated with the risk of mortality included metastatic cancer (odds ratio [OR] 2.34), protein calorie malnutrition (OR 2.18), nonmetastatic cancers of the lung and upper digestive tract, (OR 1.80) cardiorespiratory failure and shock (OR 1.60), and congestive heart failure (OR 1.34) (Table 2).

Figure 1

Hospital Risk‐Standardized Mortality Rates

The mean unadjusted hospital 30‐day mortality rate was 8.6% and ranged from 0% to 100% (Figure 2a). Risk‐standardized mortality rates varied across hospitals (Figure 2b). The mean risk‐standardized mortality rate was 8.6% and ranged from 5.9% to 13.5%. The odds of mortality at a hospital 1 standard deviation above average was 1.20 times that of a hospital 1 standard deviation below average.

Figure 2

DISCUSSION

We present a hospital‐level risk‐standardized mortality measure for patients admitted with COPD based on administrative claims data that are intended for public reporting and that have achieved endorsement by the National Quality Forum, a voluntary consensus standards‐setting organization. Across more than 4500 US hospitals, the mean 30‐day risk‐standardized mortality rate in 2008 was 8.6%, and we observed considerable variation across institutions, despite adjustment for case mix, suggesting that improvement by lower‐performing institutions may be an achievable goal.

Although improving the delivery of evidence‐based care processes and outcomes of patients with acute myocardial infarction, heart failure, and pneumonia has been the focus of national quality improvement efforts for more than a decade, COPD has largely been overlooked.[23] Within this context, this analysis represents the first attempt to systematically measure, at the hospital level, 30‐day all‐cause mortality for patients admitted to US hospitals for exacerbation of COPD. The model we have developed and validated is intended to be used to compare the performance of hospitals while controlling for differences in the pretreatment risk of mortality of patients and accounting for the clustering of patients within hospitals, and will facilitate surveillance of hospital‐level risk‐adjusted outcomes over time.

In contrast to process‐based measures of quality, such as the percentage of patients with pneumonia who receive appropriate antibiotic therapy, performance measures based on patient outcomes provide a more comprehensive view of care and are more consistent with patients' goals.[24] Additionally, it is well established that hospital performance on individual and composite process measures explains only a small amount of the observed variation in patient outcomes between institutions.[25] In this regard, outcome measures incorporate important, but difficult to measure aspects of care, such as diagnostic accuracy and timing, communication and teamwork, the recognition and response to complications, care coordination at the time of transfers between levels of care, and care settings. Nevertheless, when used for making inferences about the quality of hospital care, individual measures such as the risk‐standardized hospital mortality rate should be interpreted in the context of other performance measures, including readmission, patient experience, and costs of care.

A number of prior investigators have described the outcomes of care for patients hospitalized with exacerbations of COPD, including identifying risk factors for mortality. Patil et al. carried out an analysis of the 1996 Nationwide Inpatient Sample and described an overall in‐hospital mortality rate of 2.5% among patients with COPD, and reported that a multivariable model containing sociodemographic characteristics about the patient and comorbidities had an area under the ROC curve of 0.70.[3] In contrast, this hospital‐level measure includes patients with a principal diagnosis of respiratory failure and focuses on 30‐day rather than inpatient mortality, accounting for the nearly 3‐fold higher mortality rate we observed. In a more recent study that used clinical from a large multistate database, Tabak et al. developed a prediction model for inpatient mortality for patients with COPD that contained only 4 factors: age, blood urea nitrogen, mental status, and pulse, and achieved an area under the ROC curve of 0.72.[4] The simplicity of such a model and its reliance on clinical measurements makes it particularly well suited for bedside application by clinicians, but less valuable for large‐scale public reporting programs that rely on administrative data. In the only other study identified that focused on the assessment of hospital mortality rates, Agabiti et al. analyzed the outcomes of 12,756 patients hospitalized for exacerbations of COPD, using similar ICD‐9‐CM diagnostic criteria as in this study, at 21 hospitals in Rome, Italy.[26] They reported an average crude 30‐day mortality rate of 3.8% among a group of 5 benchmark hospitals and an average mortality of 7.5% (range, 5.2%17.2%) among the remaining institutions.

To put the variation we observed in mortality rates into a broader context, the relative difference in the risk‐standardized hospital mortality rates across the 10th to 90th percentiles of hospital performance was 25% for acute myocardial infarction and 39% for heart failure, whereas rates varied 30% for COPD, from 7.6% to 9.9%.[27] Model discrimination in COPD (C statistic, 0.72) was also similar to that reported for models used for public reporting of hospital mortality in acute myocardial infarction (C statistic, 0.71) and pneumonia (C statistic, 0.72).

This study has a number of important strengths. First, the model was developed from a large sample of recent Medicare claims, achieved good discrimination, and was validated in samples not limited to Medicare beneficiaries. Second, by including patients with a principal diagnosis of COPD, as well as those with a principal diagnosis of acute respiratory failure when accompanied by a secondary diagnosis of COPD with acute exacerbation, this model can be used to assess hospital performance across the full spectrum of disease severity. This broad set of ICD‐9‐CM codes used to define the cohort also ensures that efforts to measure hospital performance will be less influenced by differences in documentation and coding practices across hospitals relating to the diagnosis or sequencing of acute respiratory failure diagnoses. Moreover, the inclusion of patients with respiratory failure is important because these patients have the greatest risk of mortality, and are those in whom efforts to improve the quality and safety of care may have the greatest impact. Third, rather than relying solely on information documented during the index admission, we used ambulatory and inpatient claims from the full year prior to the index admission to identify comorbidities and to distinguish them from potential complications of care. Finally, we did not include factors such as hospital characteristics (eg, number of beds, teaching status) in the model. Although they might have improved overall predictive ability, the goal of the hospital mortality measure is to enable comparisons of mortality rates among hospitals while controlling for differences in patient characteristics. To the extent that factors such as size or teaching status might be independently associated with hospital outcomes, it would be inappropriate to adjust away their effects, because mortality risk should not be influenced by hospital characteristics other than through their effects on quality.

These results should be viewed in light of several limitations. First, we used ICD‐9‐CM codes derived from claims files to define the patient populations included in the measure rather than collecting clinical or physiologic information prospectively or through manual review of medical records, such as the forced expiratory volume in 1 second or whether the patient required long‐term oxygen therapy. Nevertheless, we included a broad set of potential diagnosis codes to capture the full spectrum of COPD exacerbations and to minimize differences in coding across hospitals. Second, because the risk‐adjustment included diagnoses coded in the year prior to the index admission, it is potentially subject to bias due to regional differences in medical care utilization that are not driven by underlying differences in patient illness.[28] Third, using administrative claims data, we observed some paradoxical associations in the model that are difficult to explain on clinical grounds, such as a protective effect of substance and alcohol abuse or prior episodes of respiratory failure. Fourth, although we excluded patients from the analysis who were enrolled in hospice prior to, or on the day of, the index admission, we did not exclude those who choose to withdraw support, transition to comfort measures only, or enrolled in hospice care during a hospitalization. We do not seek to penalize hospitals for being sensitive to the preferences of patients at the end of life. At the same time, it is equally important that the measure is capable of detecting the outcomes of suboptimal care that may in some instances lead a patient or their family to withdraw support or choose hospice. Finally, we did not have the opportunity to validate the model against a clinical registry of patients with COPD, because such data do not currently exist. Nevertheless, the use of claims as a surrogate for chart data for risk adjustment has been validated for several conditions, including acute myocardial infarction, heart failure, and pneumonia.[29, 30]

CONCLUSIONS

Risk‐standardized 30‐day mortality rates for Medicare beneficiaries with COPD vary across hospitals in the US. Calculating and reporting hospital outcomes using validated performance measures may catalyze quality improvement activities and lead to better outcomes. Additional research would be helpful to confirm that hospitals with lower mortality rates achieve care that meets the goals of patients and their families better than at hospitals with higher mortality rates.

Disclosures

Peter K. Lindenauer, MD, MSc, is the guarantor of this article, taking responsibility for the integrity of the work as a whole, from inception to published article, and takes responsibility for the content of the manuscript, including the data and data analysis. All authors have made substantial contributions to the conception and design, or acquisition of data, or analysis and interpretation of data; have drafted the submitted article or revised it critically for important intellectual content; and have provided final approval of the version to be published. Preparation of this manuscript was completed under Contract Number: HHSM‐5002008‐0025I/HHSM‐500‐T0001, Modification No. 000007, Option Year 2 Measure Instrument Development and Support (MIDS). Sponsors did not contribute to the development of the research or manuscript. Dr. Au reports being an unpaid research consultant for Bosch Inc. He receives research funding from the NIH, Department of Veterans Affairs, AHRQ, and Gilead Sciences. The views of the this manuscript represent the authors and do not necessarily represent those of the Department of Veterans Affairs. Drs. Drye and Bernheim report receiving contract funding from CMS to develop and maintain quality measures.

Chronic obstructive pulmonary disease (COPD) affects as many as 24 million individuals in the United States, is responsible for more than 700,000 annual hospital admissions, and is currently the nation's third leading cause of death, accounting for nearly $49.9 billion in medical spending in 2010.[1, 2] Reported in‐hospital mortality rates for patients hospitalized for exacerbations of COPD range from 2% to 5%.[3, 4, 5, 6, 7] Information about 30‐day mortality rates following hospitalization for COPD is more limited; however, international studies suggest that rates range from 3% to 9%,[8, 9] and 90‐day mortality rates exceed 15%.[10]

Despite this significant clinical and economic impact, there have been no large‐scale, sustained efforts to measure the quality or outcomes of hospital care for patients with COPD in the United States. What little is known about the treatment of patients with COPD suggests widespread opportunities to increase adherence to guideline‐recommended therapies, to reduce the use of ineffective treatments and tests, and to address variation in care across institutions.[5, 11, 12]

Public reporting of hospital performance is a key strategy for improving the quality and safety of hospital care, both in the United States and internationally.[13] Since 2007, the Centers for Medicare and Medicaid Services (CMS) has reported hospital mortality rates on the Hospital Compare Web site, and COPD is 1 of the conditions highlighted in the Affordable Care Act for future consideration.[14] Such initiatives rely on validated, risk‐adjusted performance measures for comparisons across institutions and to enable outcomes to be tracked over time. We present the development, validation, and results of a model intended for public reporting of risk‐standardized mortality rates for patients hospitalized with exacerbations of COPD that has been endorsed by the National Quality Forum.[15]

METHODS

RESULTS

Model Derivation

After exclusions were applied, the development sample included 150,035 admissions in 2008 at 4537 US hospitals (Figure 1). Factors that were most strongly associated with the risk of mortality included metastatic cancer (odds ratio [OR] 2.34), protein calorie malnutrition (OR 2.18), nonmetastatic cancers of the lung and upper digestive tract, (OR 1.80) cardiorespiratory failure and shock (OR 1.60), and congestive heart failure (OR 1.34) (Table 2).

Figure 1

Hospital Risk‐Standardized Mortality Rates

The mean unadjusted hospital 30‐day mortality rate was 8.6% and ranged from 0% to 100% (Figure 2a). Risk‐standardized mortality rates varied across hospitals (Figure 2b). The mean risk‐standardized mortality rate was 8.6% and ranged from 5.9% to 13.5%. The odds of mortality at a hospital 1 standard deviation above average was 1.20 times that of a hospital 1 standard deviation below average.

Figure 2

DISCUSSION

We present a hospital‐level risk‐standardized mortality measure for patients admitted with COPD based on administrative claims data that are intended for public reporting and that have achieved endorsement by the National Quality Forum, a voluntary consensus standards‐setting organization. Across more than 4500 US hospitals, the mean 30‐day risk‐standardized mortality rate in 2008 was 8.6%, and we observed considerable variation across institutions, despite adjustment for case mix, suggesting that improvement by lower‐performing institutions may be an achievable goal.

Although improving the delivery of evidence‐based care processes and outcomes of patients with acute myocardial infarction, heart failure, and pneumonia has been the focus of national quality improvement efforts for more than a decade, COPD has largely been overlooked.[23] Within this context, this analysis represents the first attempt to systematically measure, at the hospital level, 30‐day all‐cause mortality for patients admitted to US hospitals for exacerbation of COPD. The model we have developed and validated is intended to be used to compare the performance of hospitals while controlling for differences in the pretreatment risk of mortality of patients and accounting for the clustering of patients within hospitals, and will facilitate surveillance of hospital‐level risk‐adjusted outcomes over time.

In contrast to process‐based measures of quality, such as the percentage of patients with pneumonia who receive appropriate antibiotic therapy, performance measures based on patient outcomes provide a more comprehensive view of care and are more consistent with patients' goals.[24] Additionally, it is well established that hospital performance on individual and composite process measures explains only a small amount of the observed variation in patient outcomes between institutions.[25] In this regard, outcome measures incorporate important, but difficult to measure aspects of care, such as diagnostic accuracy and timing, communication and teamwork, the recognition and response to complications, care coordination at the time of transfers between levels of care, and care settings. Nevertheless, when used for making inferences about the quality of hospital care, individual measures such as the risk‐standardized hospital mortality rate should be interpreted in the context of other performance measures, including readmission, patient experience, and costs of care.

A number of prior investigators have described the outcomes of care for patients hospitalized with exacerbations of COPD, including identifying risk factors for mortality. Patil et al. carried out an analysis of the 1996 Nationwide Inpatient Sample and described an overall in‐hospital mortality rate of 2.5% among patients with COPD, and reported that a multivariable model containing sociodemographic characteristics about the patient and comorbidities had an area under the ROC curve of 0.70.[3] In contrast, this hospital‐level measure includes patients with a principal diagnosis of respiratory failure and focuses on 30‐day rather than inpatient mortality, accounting for the nearly 3‐fold higher mortality rate we observed. In a more recent study that used clinical from a large multistate database, Tabak et al. developed a prediction model for inpatient mortality for patients with COPD that contained only 4 factors: age, blood urea nitrogen, mental status, and pulse, and achieved an area under the ROC curve of 0.72.[4] The simplicity of such a model and its reliance on clinical measurements makes it particularly well suited for bedside application by clinicians, but less valuable for large‐scale public reporting programs that rely on administrative data. In the only other study identified that focused on the assessment of hospital mortality rates, Agabiti et al. analyzed the outcomes of 12,756 patients hospitalized for exacerbations of COPD, using similar ICD‐9‐CM diagnostic criteria as in this study, at 21 hospitals in Rome, Italy.[26] They reported an average crude 30‐day mortality rate of 3.8% among a group of 5 benchmark hospitals and an average mortality of 7.5% (range, 5.2%17.2%) among the remaining institutions.

To put the variation we observed in mortality rates into a broader context, the relative difference in the risk‐standardized hospital mortality rates across the 10th to 90th percentiles of hospital performance was 25% for acute myocardial infarction and 39% for heart failure, whereas rates varied 30% for COPD, from 7.6% to 9.9%.[27] Model discrimination in COPD (C statistic, 0.72) was also similar to that reported for models used for public reporting of hospital mortality in acute myocardial infarction (C statistic, 0.71) and pneumonia (C statistic, 0.72).

This study has a number of important strengths. First, the model was developed from a large sample of recent Medicare claims, achieved good discrimination, and was validated in samples not limited to Medicare beneficiaries. Second, by including patients with a principal diagnosis of COPD, as well as those with a principal diagnosis of acute respiratory failure when accompanied by a secondary diagnosis of COPD with acute exacerbation, this model can be used to assess hospital performance across the full spectrum of disease severity. This broad set of ICD‐9‐CM codes used to define the cohort also ensures that efforts to measure hospital performance will be less influenced by differences in documentation and coding practices across hospitals relating to the diagnosis or sequencing of acute respiratory failure diagnoses. Moreover, the inclusion of patients with respiratory failure is important because these patients have the greatest risk of mortality, and are those in whom efforts to improve the quality and safety of care may have the greatest impact. Third, rather than relying solely on information documented during the index admission, we used ambulatory and inpatient claims from the full year prior to the index admission to identify comorbidities and to distinguish them from potential complications of care. Finally, we did not include factors such as hospital characteristics (eg, number of beds, teaching status) in the model. Although they might have improved overall predictive ability, the goal of the hospital mortality measure is to enable comparisons of mortality rates among hospitals while controlling for differences in patient characteristics. To the extent that factors such as size or teaching status might be independently associated with hospital outcomes, it would be inappropriate to adjust away their effects, because mortality risk should not be influenced by hospital characteristics other than through their effects on quality.

These results should be viewed in light of several limitations. First, we used ICD‐9‐CM codes derived from claims files to define the patient populations included in the measure rather than collecting clinical or physiologic information prospectively or through manual review of medical records, such as the forced expiratory volume in 1 second or whether the patient required long‐term oxygen therapy. Nevertheless, we included a broad set of potential diagnosis codes to capture the full spectrum of COPD exacerbations and to minimize differences in coding across hospitals. Second, because the risk‐adjustment included diagnoses coded in the year prior to the index admission, it is potentially subject to bias due to regional differences in medical care utilization that are not driven by underlying differences in patient illness.[28] Third, using administrative claims data, we observed some paradoxical associations in the model that are difficult to explain on clinical grounds, such as a protective effect of substance and alcohol abuse or prior episodes of respiratory failure. Fourth, although we excluded patients from the analysis who were enrolled in hospice prior to, or on the day of, the index admission, we did not exclude those who choose to withdraw support, transition to comfort measures only, or enrolled in hospice care during a hospitalization. We do not seek to penalize hospitals for being sensitive to the preferences of patients at the end of life. At the same time, it is equally important that the measure is capable of detecting the outcomes of suboptimal care that may in some instances lead a patient or their family to withdraw support or choose hospice. Finally, we did not have the opportunity to validate the model against a clinical registry of patients with COPD, because such data do not currently exist. Nevertheless, the use of claims as a surrogate for chart data for risk adjustment has been validated for several conditions, including acute myocardial infarction, heart failure, and pneumonia.[29, 30]

CONCLUSIONS

Risk‐standardized 30‐day mortality rates for Medicare beneficiaries with COPD vary across hospitals in the US. Calculating and reporting hospital outcomes using validated performance measures may catalyze quality improvement activities and lead to better outcomes. Additional research would be helpful to confirm that hospitals with lower mortality rates achieve care that meets the goals of patients and their families better than at hospitals with higher mortality rates.

Disclosures

Peter K. Lindenauer, MD, MSc, is the guarantor of this article, taking responsibility for the integrity of the work as a whole, from inception to published article, and takes responsibility for the content of the manuscript, including the data and data analysis. All authors have made substantial contributions to the conception and design, or acquisition of data, or analysis and interpretation of data; have drafted the submitted article or revised it critically for important intellectual content; and have provided final approval of the version to be published. Preparation of this manuscript was completed under Contract Number: HHSM‐5002008‐0025I/HHSM‐500‐T0001, Modification No. 000007, Option Year 2 Measure Instrument Development and Support (MIDS). Sponsors did not contribute to the development of the research or manuscript. Dr. Au reports being an unpaid research consultant for Bosch Inc. He receives research funding from the NIH, Department of Veterans Affairs, AHRQ, and Gilead Sciences. The views of the this manuscript represent the authors and do not necessarily represent those of the Department of Veterans Affairs. Drs. Drye and Bernheim report receiving contract funding from CMS to develop and maintain quality measures.

Hospitalization may offer a natural opportunity to screen and advise patients on the advantages of quitting smoking due to a variety of reasons, such as the smoke‐free environment, availability of medical personnel, suitability of tailoring information, and the potential to catch a teachable moment.1, 2 Additionally, a recent meta‐analysis suggested that hospital‐based cessation programs and referrals to cardiac rehabilitation result in significantly higher rates of cessation among discharged smokers.3 In 2008, the U.S. Public Health Service Task Force on Clinical Practice Guidelines for Treating Tobacco Use and Dependence in hospitalized smokers recommended listing smoking status on problem lists, evaluating a smoker's preparedness to quit, providing counseling and medications to treat in‐hospital withdrawal symptoms, and arranging discharge follow‐up to help smokers remain abstinent.4 To promote these practices, the Center for Medicaid and Medicare Services (CMS) has made smoking cessation counseling a quality of care indicator for patients hospitalized with congestive heart failure (CHF), acute myocardial infarction (AMI), or pneumonia. This indicator is a critical step in recognizing the importance of smoking cessation counseling in improving mortality and morbidity for these patients.

Despite the importance of promoting smoking cessation among hospitalized patients, few studies have looked at whether or not hospitalized patients are prepared to quit smoking. Ascertaining patients' preparedness to quit smoking is an important first step in understanding a patient's readiness to change their health behaviors because smoking cessation is the culmination of a lengthy process of behavior change.5 Studies of healthy factory workers suggest that smokers who were more prepared to quit smoking had a higher number of previous quit attempts and perceived coworker encouragement.6

Understanding patient preparedness to quit smoking is especially important among African American smokers, who face a disproportionate health burden due to smoking‐related illness. Studies show that African Americans are less likely than other racial groups to engage in formal tobacco cessation interventions and have lower long‐term quit rates, despite a higher desire to quit smoking.5, 79 Understanding preparedness to quit among this particular group of hospitalized patients may be an important first step in identifying those most likely to quit and benefit from tailored, intensive interventions, such as using medications to assist in combination with postdischarge tobacco cessation counseling.

The aim of this study was to characterize the preparedness to quit smoking and to assess quit attempts made, methods used for quitting, and the success of such quit attempts at 1‐month follow‐up in a group comprised of a high proportion of underserved African American hospitalized smokers. In addition, the relationship of hospitalized patients' preparedness to quit and the effect of inpatient advice on the likelihood of subsequent tobacco cessation were examined.

Patients and Methods

The data used for this study were collected for the Cardiology Quality of Care Study, an ongoing prospective study of patients hospitalized on the inpatient cardiology service at the University of Chicago Medical Center. Newly admitted patients were approached by research assistants and consented to the study using a previously described protocol for enrolling hospitalized patients.10 Patients that lacked decisional capacity (score of <17 on the telephone version of the Mini‐Mental Status Exam)11 were excluded. Patients did not receive any scripted intervention during this admission to assist with cessation. The study left cessation counseling and advice to quit up to the discretion of the individual physician caring for the patient in the hospital. The Institutional Review Board at the University of Chicago approved this study.

Results

From February 2006 through July 2007, 86% (2906/3364) of all cardiology inpatients approached were interviewed. Fifteen percent (436/2906) of patients enrolled in the study indicated that they were current smokers. Contemplation Ladder scores were obtained on 95% (415/436) of the current smokers, and 1‐month postdischarge follow‐up telephone surveys were completed in 67% (276/415) of the current smokers. Three attempts were made to contact patients who were lost to follow‐up (Figure 1). The major reasons for inability to contact patients included wrong telephone numbers, disconnected phone lines, or no method to leave a message for the patient (ie, no answering machine). Given that we were only able to complete follow‐up interviews on 276 patients, we conducted our analyses on only this group of patients.

Figure 1

The average age of current smokers in the sample was 55 years (95% confidence interval [CI], 54‐58). Most current smokers were of the African American race (83%; 224/276). More than 65% of smokers had completed high school or higher, and nearly one‐half (46%) had an average household income of $25,000 or less before taxes. The most common admitting diagnoses per chart audit among current inpatient smokers were AMI (31%) and CHF (27%). The vast majority (95%) of hospitalized smokers in this sample were first‐time admissions to the University of Chicago. Table 1 shows the demographic data for current smokers compared to former smokers (those who have quit smoking prior to admission). Current smokers were more likely to be African American, had lower income levels, and were less likely to have completed high school. Additionally, current smokers were more likely to carry a potential diagnosis of AMI or CHF and to be a first‐time admission (Table 1).

Approximately three‐quarters (76%; 210/276) of current smokers were identified as prepared to quit, with a Ladder score 6. There was a wide distribution of Ladder scores, with one‐third (31%; 86/276) of smokers reporting a Ladder score of 8, indicating that they still smoke, but are ready to set a quit date and another 34% (95/276 patients) with Ladder scores of either 6 or 7 also indicating they were planning to quit smoking (Figure 2). A significant portion of smokers (71%; 195/276) reported making a quit attempt after discharge, and 38% of smokers (106/276) self‐reported that their quit attempt was successful (ie, no longer smoking at 1 month post discharge). Note that the quit rate is reduced to 26% (106/415) at 1 month if one conservatively assumes that those who did not take part in follow‐up were relapsers. Among those who did participate in follow‐up, as shown in Figure 3, the most frequently reported (53%; 145/276) method used to quit smoking was cold turkey. Thirteen percent (37/276) of patients reported making a quit attempt using pharmacological therapy (ie, NRT or bupropion) and only 4% (12/276) of patients reported making a quit attempt using the help of a smoking cessation program (Figure 3).

Figure 2

Figure 3

Preparedness was an important predictor of making a quit attempt. Prepared patients (ie, Ladder score 6) were significantly more likely than patients who were less prepared to report making a quit attempt after discharge (163/212 [77%] vs. 32/64 [50%], respectively; P < 0.001). This result remained significant after adjusting for sociodemographic characteristics with a similar effect size (adjusted estimates 76% [95% CI, 75.7‐76.7] prepared vs. 49% [95% CI, 48.5‐49.8]; P < 0.001). These results also remained significant with a similar effect size in analyses using multivariate logistic regression (Table 2). Of those patients who made quit attempts, prepared patients were slightly more likely to report a successful quit attempt (90/163; 55%) than were less‐prepared patients (16/32; 50%), though this was not significant (P = 0.205).

In the follow‐up sample, 17% could not remember if they received advice to quit smoking. Among those who were able to recall receiving advice, the majority (78%; 180/230) reported that they received advice from a nurse or physician during hospitalization, compared to 22% who did not recall ever being advised to quit by any healthcare provider during the admission. Patients who reported receiving advice to quit were more likely to report making a quit attempt postdischarge as compared to those that did not recall receiving advice (70% vs. 46%, respectively; P = 0.002). In a multivariate logistic regression, controlling for demographic factors and admitting diagnosis, both preparedness and receipt of in‐hospital advice were independent predictors of making a future quit attempt (odds ratio [OR] = 4.05; 95% CI, 1.91‐8.60; P < 0.001 for preparedness; OR = 3.96; 95% CI, 1.84‐8.54; P < 0.001 for advice). Additionally, there was no significant interaction or synergistic effect between being prepared to quit smoking and receiving in‐hospital advice to quit (OR = 1.24; 95% CI, 0.17‐9.21; P = 0.836) (Figure 4). When analyzing the effects of preparedness and advice on quit attempts, only preparedness to quit remained a significant predictor of a successful quit attempt (OR = 2.93; 95% CI, 1.13‐7.60; P = 0.027 for preparedness; OR = 2.16; 95% CI, 0.85‐5.49; P = 0.10 for advice to quit). As demonstrated in Table 2, a higher percentage of prepared patients made a quit attempt after discharge (76.9% vs. 50%) and had a successful quit attempt and short‐term abstinence (55% prepared patients vs. 50% less prepared patients).

Figure 4

Discussion

This study demonstrated that in a group of hospitalized underserved, and predominantly African American smokers, the majority of patients reported being prepared to quit smoking at the time of hospitalization. Prepared patients were more likely to report making a quit attempt after discharge and more likely to report being successful in their quit attempt than patients who reported being less prepared to quit during their hospitalization. Nevertheless, approximately one‐half of unprepared patients did make a quit attempt 1 month after discharge, demonstrating a desire to quit smoking after hospitalization among this population. However, short‐term success rates in this group were lower than in patients prepared to quit. In addition, preparedness to quit and receipt of in‐hospital advice to quit smoking were both found to be independent predictors of making a quit attempt, with nearly identical ORs; however, only preparedness remained significant after controlling for advice to quit. Last, although the majority of hospitalized cardiac patients were making quit attempts after discharge, most patients reported using the least effective quit methods (ie, cold turkey) rather than more effective and intensive interventions such as counseling in combination with pharmacotherapy.

These findings have important implications for current quality initiatives targeted at promoting smoking cessation among cardiac patients. First, these results highlight the need for evidence‐based methods to be made available to hospitalized smokers who are prepared to quit. Our results are consistent with other studies reporting rare use (5.2%) of NRT in the hospital setting, despite the proven benefit in treating nicotine withdrawal symptoms.17 This is also consistent with data reporting that among nonhospitalized smokers, quitting cold turkey was the most commonly used and least effective cessation method.18 Second, the rate of recall of in‐hospital advice among patients (78%) was generally consistent with those reported to CMS (most recent quarter 95% for AMI and 88% for CHF).19

In addition to receiving advice, preparedness to quit was associated with higher quit attempts, therefore highlighting the importance of assessing level of preparedness in addition to giving advice. The fact that most quit attempts were made using cold turkey and resulted in low short‐term success rates underscores the need to reevaluate the current CMS quality indicator of advice alone for hospitalized smokers. Furthermore, the recently updated 2008 U.S. Public Health guidelines recently recommend, in addition to advice, that all hospitalized smokers be assessed for readiness to change, be assisted in quitting with pharmacotherapy, and be arranged follow‐up for tobacco cessation postdischarge, highlighting the inadequacy of advice alone.4 While it is important to continue to advise all hospitalized smokers to quit, the study findings demonstrate that assessing preparedness may result in targeting more prepared patients with more intensive interventions. Further policy implications include that less prepared patients may need motivational techniques to increase their level of preparedness to quit during hospitalization.

Several limitations are worth mentioning. First, the study included a relatively small sample size drawn from a single urban medical center. The prevalence of current smokers in our sample was 15%, which is lower than many studies looking at cardiology inpatient smokers.3, 20 This limitation of our study may be attributed to the advanced age of the majority of our patients, as compared with other studies, as well as the possibility of socially desirable response bias that many low‐income African American smokers may experience, leaving them less likely to admit to smoking at the time of hospitalization. Second, there was a low follow‐up rate, with 66% of patients undergoing follow‐up postdischarge. While this may raise the concerns of differences between ladder scores in those patients that participated in follow‐up and those that did not, analyses show no significant difference between level of preparedness in these 2 groups (68% prepared in patients who received follow‐up vs. 63% prepared patients in those who did not participate in follow‐up; P = 0.36). Third, follow‐up of quit attempts and receipt of advice were all assessed using self‐report, and, therefore, were limited by lack of verification and lack of assessment for potential recall bias. Fourth, in this pilot study, the follow‐up period was relatively short at 1 month postdischarge. It is likely that rates of successful quit attempts would be lower with longer‐term follow‐up periods, given previous literature demonstrating the difficulty with long‐term abstinence.21 Last, the study was not able to account for potential effects that hospitalization itself may have on preparedness, as patients may be more likely to report being prepared to quit when in the face of a health shock,22 as well as the fact that some patients may demonstrate a socially desirable response bias influenced by hospitalization.

In conclusion, the majority of underserved smokers with cardiac disease reported being prepared to quit smoking and were more likely to self‐report making a quit attempt after discharge. However, the majority of these quit attempts were made via cold turkey, without the support of available evidence‐based methods to quit. It is possible that by directly providing education, access to pharmacotherapy, and counseling options, the utilization rates for more efficacious treatments would increase in cardiac patients who are prepared to quit. While recall of in‐hospital advice was associated with future quit attempts, prepared patients who recalled receiving advice were more likely to make a quit attempt than prepared patients who did not recall receiving advice, as well as unprepared patients. Together, these findings highlight the need to consider a patient's level of preparedness to quit in understanding the success of in‐hospital advice and the importance of making evidence‐based cessation methods available to hospitalized smokers who are prepared to quit. Additionally, identifying patients not prepared to quit may help in providing them with appropriate motivational therapy, to move them along the stages of change, as well as educational information on how to quit once they have decided to do so.

Hospitalization may offer a natural opportunity to screen and advise patients on the advantages of quitting smoking due to a variety of reasons, such as the smoke‐free environment, availability of medical personnel, suitability of tailoring information, and the potential to catch a teachable moment.1, 2 Additionally, a recent meta‐analysis suggested that hospital‐based cessation programs and referrals to cardiac rehabilitation result in significantly higher rates of cessation among discharged smokers.3 In 2008, the U.S. Public Health Service Task Force on Clinical Practice Guidelines for Treating Tobacco Use and Dependence in hospitalized smokers recommended listing smoking status on problem lists, evaluating a smoker's preparedness to quit, providing counseling and medications to treat in‐hospital withdrawal symptoms, and arranging discharge follow‐up to help smokers remain abstinent.4 To promote these practices, the Center for Medicaid and Medicare Services (CMS) has made smoking cessation counseling a quality of care indicator for patients hospitalized with congestive heart failure (CHF), acute myocardial infarction (AMI), or pneumonia. This indicator is a critical step in recognizing the importance of smoking cessation counseling in improving mortality and morbidity for these patients.

Despite the importance of promoting smoking cessation among hospitalized patients, few studies have looked at whether or not hospitalized patients are prepared to quit smoking. Ascertaining patients' preparedness to quit smoking is an important first step in understanding a patient's readiness to change their health behaviors because smoking cessation is the culmination of a lengthy process of behavior change.5 Studies of healthy factory workers suggest that smokers who were more prepared to quit smoking had a higher number of previous quit attempts and perceived coworker encouragement.6

Understanding patient preparedness to quit smoking is especially important among African American smokers, who face a disproportionate health burden due to smoking‐related illness. Studies show that African Americans are less likely than other racial groups to engage in formal tobacco cessation interventions and have lower long‐term quit rates, despite a higher desire to quit smoking.5, 79 Understanding preparedness to quit among this particular group of hospitalized patients may be an important first step in identifying those most likely to quit and benefit from tailored, intensive interventions, such as using medications to assist in combination with postdischarge tobacco cessation counseling.

The aim of this study was to characterize the preparedness to quit smoking and to assess quit attempts made, methods used for quitting, and the success of such quit attempts at 1‐month follow‐up in a group comprised of a high proportion of underserved African American hospitalized smokers. In addition, the relationship of hospitalized patients' preparedness to quit and the effect of inpatient advice on the likelihood of subsequent tobacco cessation were examined.

Patients and Methods

The data used for this study were collected for the Cardiology Quality of Care Study, an ongoing prospective study of patients hospitalized on the inpatient cardiology service at the University of Chicago Medical Center. Newly admitted patients were approached by research assistants and consented to the study using a previously described protocol for enrolling hospitalized patients.10 Patients that lacked decisional capacity (score of <17 on the telephone version of the Mini‐Mental Status Exam)11 were excluded. Patients did not receive any scripted intervention during this admission to assist with cessation. The study left cessation counseling and advice to quit up to the discretion of the individual physician caring for the patient in the hospital. The Institutional Review Board at the University of Chicago approved this study.

Results

From February 2006 through July 2007, 86% (2906/3364) of all cardiology inpatients approached were interviewed. Fifteen percent (436/2906) of patients enrolled in the study indicated that they were current smokers. Contemplation Ladder scores were obtained on 95% (415/436) of the current smokers, and 1‐month postdischarge follow‐up telephone surveys were completed in 67% (276/415) of the current smokers. Three attempts were made to contact patients who were lost to follow‐up (Figure 1). The major reasons for inability to contact patients included wrong telephone numbers, disconnected phone lines, or no method to leave a message for the patient (ie, no answering machine). Given that we were only able to complete follow‐up interviews on 276 patients, we conducted our analyses on only this group of patients.

Figure 1

The average age of current smokers in the sample was 55 years (95% confidence interval [CI], 54‐58). Most current smokers were of the African American race (83%; 224/276). More than 65% of smokers had completed high school or higher, and nearly one‐half (46%) had an average household income of $25,000 or less before taxes. The most common admitting diagnoses per chart audit among current inpatient smokers were AMI (31%) and CHF (27%). The vast majority (95%) of hospitalized smokers in this sample were first‐time admissions to the University of Chicago. Table 1 shows the demographic data for current smokers compared to former smokers (those who have quit smoking prior to admission). Current smokers were more likely to be African American, had lower income levels, and were less likely to have completed high school. Additionally, current smokers were more likely to carry a potential diagnosis of AMI or CHF and to be a first‐time admission (Table 1).

Approximately three‐quarters (76%; 210/276) of current smokers were identified as prepared to quit, with a Ladder score 6. There was a wide distribution of Ladder scores, with one‐third (31%; 86/276) of smokers reporting a Ladder score of 8, indicating that they still smoke, but are ready to set a quit date and another 34% (95/276 patients) with Ladder scores of either 6 or 7 also indicating they were planning to quit smoking (Figure 2). A significant portion of smokers (71%; 195/276) reported making a quit attempt after discharge, and 38% of smokers (106/276) self‐reported that their quit attempt was successful (ie, no longer smoking at 1 month post discharge). Note that the quit rate is reduced to 26% (106/415) at 1 month if one conservatively assumes that those who did not take part in follow‐up were relapsers. Among those who did participate in follow‐up, as shown in Figure 3, the most frequently reported (53%; 145/276) method used to quit smoking was cold turkey. Thirteen percent (37/276) of patients reported making a quit attempt using pharmacological therapy (ie, NRT or bupropion) and only 4% (12/276) of patients reported making a quit attempt using the help of a smoking cessation program (Figure 3).

Figure 2

Figure 3

Preparedness was an important predictor of making a quit attempt. Prepared patients (ie, Ladder score 6) were significantly more likely than patients who were less prepared to report making a quit attempt after discharge (163/212 [77%] vs. 32/64 [50%], respectively; P < 0.001). This result remained significant after adjusting for sociodemographic characteristics with a similar effect size (adjusted estimates 76% [95% CI, 75.7‐76.7] prepared vs. 49% [95% CI, 48.5‐49.8]; P < 0.001). These results also remained significant with a similar effect size in analyses using multivariate logistic regression (Table 2). Of those patients who made quit attempts, prepared patients were slightly more likely to report a successful quit attempt (90/163; 55%) than were less‐prepared patients (16/32; 50%), though this was not significant (P = 0.205).

In the follow‐up sample, 17% could not remember if they received advice to quit smoking. Among those who were able to recall receiving advice, the majority (78%; 180/230) reported that they received advice from a nurse or physician during hospitalization, compared to 22% who did not recall ever being advised to quit by any healthcare provider during the admission. Patients who reported receiving advice to quit were more likely to report making a quit attempt postdischarge as compared to those that did not recall receiving advice (70% vs. 46%, respectively; P = 0.002). In a multivariate logistic regression, controlling for demographic factors and admitting diagnosis, both preparedness and receipt of in‐hospital advice were independent predictors of making a future quit attempt (odds ratio [OR] = 4.05; 95% CI, 1.91‐8.60; P < 0.001 for preparedness; OR = 3.96; 95% CI, 1.84‐8.54; P < 0.001 for advice). Additionally, there was no significant interaction or synergistic effect between being prepared to quit smoking and receiving in‐hospital advice to quit (OR = 1.24; 95% CI, 0.17‐9.21; P = 0.836) (Figure 4). When analyzing the effects of preparedness and advice on quit attempts, only preparedness to quit remained a significant predictor of a successful quit attempt (OR = 2.93; 95% CI, 1.13‐7.60; P = 0.027 for preparedness; OR = 2.16; 95% CI, 0.85‐5.49; P = 0.10 for advice to quit). As demonstrated in Table 2, a higher percentage of prepared patients made a quit attempt after discharge (76.9% vs. 50%) and had a successful quit attempt and short‐term abstinence (55% prepared patients vs. 50% less prepared patients).

Figure 4

Discussion

This study demonstrated that in a group of hospitalized underserved, and predominantly African American smokers, the majority of patients reported being prepared to quit smoking at the time of hospitalization. Prepared patients were more likely to report making a quit attempt after discharge and more likely to report being successful in their quit attempt than patients who reported being less prepared to quit during their hospitalization. Nevertheless, approximately one‐half of unprepared patients did make a quit attempt 1 month after discharge, demonstrating a desire to quit smoking after hospitalization among this population. However, short‐term success rates in this group were lower than in patients prepared to quit. In addition, preparedness to quit and receipt of in‐hospital advice to quit smoking were both found to be independent predictors of making a quit attempt, with nearly identical ORs; however, only preparedness remained significant after controlling for advice to quit. Last, although the majority of hospitalized cardiac patients were making quit attempts after discharge, most patients reported using the least effective quit methods (ie, cold turkey) rather than more effective and intensive interventions such as counseling in combination with pharmacotherapy.

These findings have important implications for current quality initiatives targeted at promoting smoking cessation among cardiac patients. First, these results highlight the need for evidence‐based methods to be made available to hospitalized smokers who are prepared to quit. Our results are consistent with other studies reporting rare use (5.2%) of NRT in the hospital setting, despite the proven benefit in treating nicotine withdrawal symptoms.17 This is also consistent with data reporting that among nonhospitalized smokers, quitting cold turkey was the most commonly used and least effective cessation method.18 Second, the rate of recall of in‐hospital advice among patients (78%) was generally consistent with those reported to CMS (most recent quarter 95% for AMI and 88% for CHF).19

In addition to receiving advice, preparedness to quit was associated with higher quit attempts, therefore highlighting the importance of assessing level of preparedness in addition to giving advice. The fact that most quit attempts were made using cold turkey and resulted in low short‐term success rates underscores the need to reevaluate the current CMS quality indicator of advice alone for hospitalized smokers. Furthermore, the recently updated 2008 U.S. Public Health guidelines recently recommend, in addition to advice, that all hospitalized smokers be assessed for readiness to change, be assisted in quitting with pharmacotherapy, and be arranged follow‐up for tobacco cessation postdischarge, highlighting the inadequacy of advice alone.4 While it is important to continue to advise all hospitalized smokers to quit, the study findings demonstrate that assessing preparedness may result in targeting more prepared patients with more intensive interventions. Further policy implications include that less prepared patients may need motivational techniques to increase their level of preparedness to quit during hospitalization.

Several limitations are worth mentioning. First, the study included a relatively small sample size drawn from a single urban medical center. The prevalence of current smokers in our sample was 15%, which is lower than many studies looking at cardiology inpatient smokers.3, 20 This limitation of our study may be attributed to the advanced age of the majority of our patients, as compared with other studies, as well as the possibility of socially desirable response bias that many low‐income African American smokers may experience, leaving them less likely to admit to smoking at the time of hospitalization. Second, there was a low follow‐up rate, with 66% of patients undergoing follow‐up postdischarge. While this may raise the concerns of differences between ladder scores in those patients that participated in follow‐up and those that did not, analyses show no significant difference between level of preparedness in these 2 groups (68% prepared in patients who received follow‐up vs. 63% prepared patients in those who did not participate in follow‐up; P = 0.36). Third, follow‐up of quit attempts and receipt of advice were all assessed using self‐report, and, therefore, were limited by lack of verification and lack of assessment for potential recall bias. Fourth, in this pilot study, the follow‐up period was relatively short at 1 month postdischarge. It is likely that rates of successful quit attempts would be lower with longer‐term follow‐up periods, given previous literature demonstrating the difficulty with long‐term abstinence.21 Last, the study was not able to account for potential effects that hospitalization itself may have on preparedness, as patients may be more likely to report being prepared to quit when in the face of a health shock,22 as well as the fact that some patients may demonstrate a socially desirable response bias influenced by hospitalization.

In conclusion, the majority of underserved smokers with cardiac disease reported being prepared to quit smoking and were more likely to self‐report making a quit attempt after discharge. However, the majority of these quit attempts were made via cold turkey, without the support of available evidence‐based methods to quit. It is possible that by directly providing education, access to pharmacotherapy, and counseling options, the utilization rates for more efficacious treatments would increase in cardiac patients who are prepared to quit. While recall of in‐hospital advice was associated with future quit attempts, prepared patients who recalled receiving advice were more likely to make a quit attempt than prepared patients who did not recall receiving advice, as well as unprepared patients. Together, these findings highlight the need to consider a patient's level of preparedness to quit in understanding the success of in‐hospital advice and the importance of making evidence‐based cessation methods available to hospitalized smokers who are prepared to quit. Additionally, identifying patients not prepared to quit may help in providing them with appropriate motivational therapy, to move them along the stages of change, as well as educational information on how to quit once they have decided to do so.

Hospitalization may offer a natural opportunity to screen and advise patients on the advantages of quitting smoking due to a variety of reasons, such as the smoke‐free environment, availability of medical personnel, suitability of tailoring information, and the potential to catch a teachable moment.1, 2 Additionally, a recent meta‐analysis suggested that hospital‐based cessation programs and referrals to cardiac rehabilitation result in significantly higher rates of cessation among discharged smokers.3 In 2008, the U.S. Public Health Service Task Force on Clinical Practice Guidelines for Treating Tobacco Use and Dependence in hospitalized smokers recommended listing smoking status on problem lists, evaluating a smoker's preparedness to quit, providing counseling and medications to treat in‐hospital withdrawal symptoms, and arranging discharge follow‐up to help smokers remain abstinent.4 To promote these practices, the Center for Medicaid and Medicare Services (CMS) has made smoking cessation counseling a quality of care indicator for patients hospitalized with congestive heart failure (CHF), acute myocardial infarction (AMI), or pneumonia. This indicator is a critical step in recognizing the importance of smoking cessation counseling in improving mortality and morbidity for these patients.

Despite the importance of promoting smoking cessation among hospitalized patients, few studies have looked at whether or not hospitalized patients are prepared to quit smoking. Ascertaining patients' preparedness to quit smoking is an important first step in understanding a patient's readiness to change their health behaviors because smoking cessation is the culmination of a lengthy process of behavior change.5 Studies of healthy factory workers suggest that smokers who were more prepared to quit smoking had a higher number of previous quit attempts and perceived coworker encouragement.6

Understanding patient preparedness to quit smoking is especially important among African American smokers, who face a disproportionate health burden due to smoking‐related illness. Studies show that African Americans are less likely than other racial groups to engage in formal tobacco cessation interventions and have lower long‐term quit rates, despite a higher desire to quit smoking.5, 79 Understanding preparedness to quit among this particular group of hospitalized patients may be an important first step in identifying those most likely to quit and benefit from tailored, intensive interventions, such as using medications to assist in combination with postdischarge tobacco cessation counseling.

The aim of this study was to characterize the preparedness to quit smoking and to assess quit attempts made, methods used for quitting, and the success of such quit attempts at 1‐month follow‐up in a group comprised of a high proportion of underserved African American hospitalized smokers. In addition, the relationship of hospitalized patients' preparedness to quit and the effect of inpatient advice on the likelihood of subsequent tobacco cessation were examined.

Patients and Methods

The data used for this study were collected for the Cardiology Quality of Care Study, an ongoing prospective study of patients hospitalized on the inpatient cardiology service at the University of Chicago Medical Center. Newly admitted patients were approached by research assistants and consented to the study using a previously described protocol for enrolling hospitalized patients.10 Patients that lacked decisional capacity (score of <17 on the telephone version of the Mini‐Mental Status Exam)11 were excluded. Patients did not receive any scripted intervention during this admission to assist with cessation. The study left cessation counseling and advice to quit up to the discretion of the individual physician caring for the patient in the hospital. The Institutional Review Board at the University of Chicago approved this study.

Results

From February 2006 through July 2007, 86% (2906/3364) of all cardiology inpatients approached were interviewed. Fifteen percent (436/2906) of patients enrolled in the study indicated that they were current smokers. Contemplation Ladder scores were obtained on 95% (415/436) of the current smokers, and 1‐month postdischarge follow‐up telephone surveys were completed in 67% (276/415) of the current smokers. Three attempts were made to contact patients who were lost to follow‐up (Figure 1). The major reasons for inability to contact patients included wrong telephone numbers, disconnected phone lines, or no method to leave a message for the patient (ie, no answering machine). Given that we were only able to complete follow‐up interviews on 276 patients, we conducted our analyses on only this group of patients.

Figure 1

The average age of current smokers in the sample was 55 years (95% confidence interval [CI], 54‐58). Most current smokers were of the African American race (83%; 224/276). More than 65% of smokers had completed high school or higher, and nearly one‐half (46%) had an average household income of $25,000 or less before taxes. The most common admitting diagnoses per chart audit among current inpatient smokers were AMI (31%) and CHF (27%). The vast majority (95%) of hospitalized smokers in this sample were first‐time admissions to the University of Chicago. Table 1 shows the demographic data for current smokers compared to former smokers (those who have quit smoking prior to admission). Current smokers were more likely to be African American, had lower income levels, and were less likely to have completed high school. Additionally, current smokers were more likely to carry a potential diagnosis of AMI or CHF and to be a first‐time admission (Table 1).

Approximately three‐quarters (76%; 210/276) of current smokers were identified as prepared to quit, with a Ladder score 6. There was a wide distribution of Ladder scores, with one‐third (31%; 86/276) of smokers reporting a Ladder score of 8, indicating that they still smoke, but are ready to set a quit date and another 34% (95/276 patients) with Ladder scores of either 6 or 7 also indicating they were planning to quit smoking (Figure 2). A significant portion of smokers (71%; 195/276) reported making a quit attempt after discharge, and 38% of smokers (106/276) self‐reported that their quit attempt was successful (ie, no longer smoking at 1 month post discharge). Note that the quit rate is reduced to 26% (106/415) at 1 month if one conservatively assumes that those who did not take part in follow‐up were relapsers. Among those who did participate in follow‐up, as shown in Figure 3, the most frequently reported (53%; 145/276) method used to quit smoking was cold turkey. Thirteen percent (37/276) of patients reported making a quit attempt using pharmacological therapy (ie, NRT or bupropion) and only 4% (12/276) of patients reported making a quit attempt using the help of a smoking cessation program (Figure 3).

Figure 2

Figure 3

Preparedness was an important predictor of making a quit attempt. Prepared patients (ie, Ladder score 6) were significantly more likely than patients who were less prepared to report making a quit attempt after discharge (163/212 [77%] vs. 32/64 [50%], respectively; P < 0.001). This result remained significant after adjusting for sociodemographic characteristics with a similar effect size (adjusted estimates 76% [95% CI, 75.7‐76.7] prepared vs. 49% [95% CI, 48.5‐49.8]; P < 0.001). These results also remained significant with a similar effect size in analyses using multivariate logistic regression (Table 2). Of those patients who made quit attempts, prepared patients were slightly more likely to report a successful quit attempt (90/163; 55%) than were less‐prepared patients (16/32; 50%), though this was not significant (P = 0.205).

In the follow‐up sample, 17% could not remember if they received advice to quit smoking. Among those who were able to recall receiving advice, the majority (78%; 180/230) reported that they received advice from a nurse or physician during hospitalization, compared to 22% who did not recall ever being advised to quit by any healthcare provider during the admission. Patients who reported receiving advice to quit were more likely to report making a quit attempt postdischarge as compared to those that did not recall receiving advice (70% vs. 46%, respectively; P = 0.002). In a multivariate logistic regression, controlling for demographic factors and admitting diagnosis, both preparedness and receipt of in‐hospital advice were independent predictors of making a future quit attempt (odds ratio [OR] = 4.05; 95% CI, 1.91‐8.60; P < 0.001 for preparedness; OR = 3.96; 95% CI, 1.84‐8.54; P < 0.001 for advice). Additionally, there was no significant interaction or synergistic effect between being prepared to quit smoking and receiving in‐hospital advice to quit (OR = 1.24; 95% CI, 0.17‐9.21; P = 0.836) (Figure 4). When analyzing the effects of preparedness and advice on quit attempts, only preparedness to quit remained a significant predictor of a successful quit attempt (OR = 2.93; 95% CI, 1.13‐7.60; P = 0.027 for preparedness; OR = 2.16; 95% CI, 0.85‐5.49; P = 0.10 for advice to quit). As demonstrated in Table 2, a higher percentage of prepared patients made a quit attempt after discharge (76.9% vs. 50%) and had a successful quit attempt and short‐term abstinence (55% prepared patients vs. 50% less prepared patients).

Figure 4

Discussion

This study demonstrated that in a group of hospitalized underserved, and predominantly African American smokers, the majority of patients reported being prepared to quit smoking at the time of hospitalization. Prepared patients were more likely to report making a quit attempt after discharge and more likely to report being successful in their quit attempt than patients who reported being less prepared to quit during their hospitalization. Nevertheless, approximately one‐half of unprepared patients did make a quit attempt 1 month after discharge, demonstrating a desire to quit smoking after hospitalization among this population. However, short‐term success rates in this group were lower than in patients prepared to quit. In addition, preparedness to quit and receipt of in‐hospital advice to quit smoking were both found to be independent predictors of making a quit attempt, with nearly identical ORs; however, only preparedness remained significant after controlling for advice to quit. Last, although the majority of hospitalized cardiac patients were making quit attempts after discharge, most patients reported using the least effective quit methods (ie, cold turkey) rather than more effective and intensive interventions such as counseling in combination with pharmacotherapy.

These findings have important implications for current quality initiatives targeted at promoting smoking cessation among cardiac patients. First, these results highlight the need for evidence‐based methods to be made available to hospitalized smokers who are prepared to quit. Our results are consistent with other studies reporting rare use (5.2%) of NRT in the hospital setting, despite the proven benefit in treating nicotine withdrawal symptoms.17 This is also consistent with data reporting that among nonhospitalized smokers, quitting cold turkey was the most commonly used and least effective cessation method.18 Second, the rate of recall of in‐hospital advice among patients (78%) was generally consistent with those reported to CMS (most recent quarter 95% for AMI and 88% for CHF).19

In addition to receiving advice, preparedness to quit was associated with higher quit attempts, therefore highlighting the importance of assessing level of preparedness in addition to giving advice. The fact that most quit attempts were made using cold turkey and resulted in low short‐term success rates underscores the need to reevaluate the current CMS quality indicator of advice alone for hospitalized smokers. Furthermore, the recently updated 2008 U.S. Public Health guidelines recently recommend, in addition to advice, that all hospitalized smokers be assessed for readiness to change, be assisted in quitting with pharmacotherapy, and be arranged follow‐up for tobacco cessation postdischarge, highlighting the inadequacy of advice alone.4 While it is important to continue to advise all hospitalized smokers to quit, the study findings demonstrate that assessing preparedness may result in targeting more prepared patients with more intensive interventions. Further policy implications include that less prepared patients may need motivational techniques to increase their level of preparedness to quit during hospitalization.

Several limitations are worth mentioning. First, the study included a relatively small sample size drawn from a single urban medical center. The prevalence of current smokers in our sample was 15%, which is lower than many studies looking at cardiology inpatient smokers.3, 20 This limitation of our study may be attributed to the advanced age of the majority of our patients, as compared with other studies, as well as the possibility of socially desirable response bias that many low‐income African American smokers may experience, leaving them less likely to admit to smoking at the time of hospitalization. Second, there was a low follow‐up rate, with 66% of patients undergoing follow‐up postdischarge. While this may raise the concerns of differences between ladder scores in those patients that participated in follow‐up and those that did not, analyses show no significant difference between level of preparedness in these 2 groups (68% prepared in patients who received follow‐up vs. 63% prepared patients in those who did not participate in follow‐up; P = 0.36). Third, follow‐up of quit attempts and receipt of advice were all assessed using self‐report, and, therefore, were limited by lack of verification and lack of assessment for potential recall bias. Fourth, in this pilot study, the follow‐up period was relatively short at 1 month postdischarge. It is likely that rates of successful quit attempts would be lower with longer‐term follow‐up periods, given previous literature demonstrating the difficulty with long‐term abstinence.21 Last, the study was not able to account for potential effects that hospitalization itself may have on preparedness, as patients may be more likely to report being prepared to quit when in the face of a health shock,22 as well as the fact that some patients may demonstrate a socially desirable response bias influenced by hospitalization.

In conclusion, the majority of underserved smokers with cardiac disease reported being prepared to quit smoking and were more likely to self‐report making a quit attempt after discharge. However, the majority of these quit attempts were made via cold turkey, without the support of available evidence‐based methods to quit. It is possible that by directly providing education, access to pharmacotherapy, and counseling options, the utilization rates for more efficacious treatments would increase in cardiac patients who are prepared to quit. While recall of in‐hospital advice was associated with future quit attempts, prepared patients who recalled receiving advice were more likely to make a quit attempt than prepared patients who did not recall receiving advice, as well as unprepared patients. Together, these findings highlight the need to consider a patient's level of preparedness to quit in understanding the success of in‐hospital advice and the importance of making evidence‐based cessation methods available to hospitalized smokers who are prepared to quit. Additionally, identifying patients not prepared to quit may help in providing them with appropriate motivational therapy, to move them along the stages of change, as well as educational information on how to quit once they have decided to do so.