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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