An Administrative Claims Model for Profiling Hospital 30-Day Mortality Rates for Pneumonia Patients

Oklahoma Foundation for Medical Quality, Oklahoma City, Oklahoma, United States of America.
PLoS ONE (Impact Factor: 3.23). 04/2011; 6(4):e17401. DOI: 10.1371/journal.pone.0017401
Source: PubMed


Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia.
Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032).
An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model.

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    • "This has recently become evident in the academic literature. Bratzler et al recently reported that administrative claims-based data (an administrative model) for patients admitted with community acquired pneumonia closely estimates mortality risk as predicted using variables extracted from the medical record (a physiologic model) [11]. Similarly, the University Health Consortium recently hosted a webinar (December 5, 2011) on how an administrative based method for identifying central line infections compared to that National Health and Safety Network physiology based method for identifying central line infections. "
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    ABSTRACT: Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients. We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland-Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission. We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r(2) for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model. In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to patients admitted to intensive care units. As patients and providers increasingly use publicly reported information in making health care decisions and referrals, it is critical that the provided information be understood. Our results suggest that severity of illness may influence the mortality index in administrative models. We suggest that when interpreting "report cards" or metrics, health care providers determine how the risk adjustment was made and compares to other risk adjustment models.
    PLoS ONE 02/2012; 7(2):e32286. DOI:10.1371/journal.pone.0032286 · 3.23 Impact Factor
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    ABSTRACT: Health care quality in the US territories is poorly characterized. We used process measures to compare the performance of hospitals in the US territories and in the US states. Our sample included nonfederal hospitals located in the United States and its territories discharging Medicare fee-for-service (FFS) patients with a principal discharge diagnosis of acute myocardial infarction (AMI), heart failure (HF), or pneumonia (PNE) (July 2005-June 2008). We compared risk-standardized 30-day mortality and readmission rates between territorial and stateside hospitals, adjusting for performance on core process measures and hospital characteristics. In 57 territorial hospitals and 4799 stateside hospitals, hospital mean 30-day risk-standardized mortality rates were significantly higher in the US territories (P<.001) for AMI (18.8% vs 16.0%), HF (12.3% vs 10.8%), and PNE (14.9% vs 11.4%). Hospital mean 30-day risk-standardized readmission rates (RSRRs) were also significantly higher in the US territories for AMI (20.6% vs 19.8%; P=.04), and PNE (19.4% vs 18.4%; P=.01) but was not significant for HF (25.5% vs 24.5%; P=.07). The higher risk-standardized mortality rates in the US territories remained statistically significant after adjusting for hospital characteristics and core process measure performance. Hospitals in the US territories had lower performance on all core process measures (P<.05). Compared with hospitals in the US states, hospitals in the US territories have significantly higher 30-day mortality rates and lower performance on every core process measure for patients discharged after AMI, HF, and PNE. Eliminating the substantial quality gap in the US territories should be a national priority.
    Archives of internal medicine 06/2011; 171(17):1528-40. DOI:10.1001/archinternmed.2011.284 · 17.33 Impact Factor
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    ABSTRACT: Pneumonia is the most common infectious cause of death worldwide. Over the last decade, patient characteristics and health care factors have changed. However, little information is available regarding systematically and simultaneously exploring effects of these changes on pneumonia outcomes. We used nationwide longitudinal population-based data to examine which patient characteristics and health care factors were associated with changes in 30-day mortality rates for pneumonia patients. Trend analysis using multilevel techniques. General acute care hospitals throughout Taiwan. A total of 788,011 pneumonia admissions. Thirty-day mortality rates. Taiwan's National Health Insurance claims data from 1997 to 2008 were used to identify the effects of patient characteristics and health care factors on 30-day mortality rates. Male, older, or severely ill patients, patients with more comorbidities, weekend admissions, larger reimbursement cuts and lower physician volume were associated with increased 30-day mortality rates. Moreover, there were interactions between patient age and trend on mortality. Male, older or severely ill patients with pneumonia have higher 30-day mortality rates. However, mortality gaps between elderly and young patients narrowed over time; namely, the decline rate of mortality among elderly patients was faster than that among young patients. Pneumonia patients admitted on weekends also have higher mortality rates than those admitted on weekdays. The mortality of pneumonia patients rises under increased financial strain from cuts in reimbursement such as the Balanced Budget Act in the United States or global budgeting. Higher physician volume is associated with lower mortality rates.
    Journal of General Internal Medicine 11/2011; 27(5):527-33. DOI:10.1007/s11606-011-1932-1 · 3.42 Impact Factor
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