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

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  • Dale W Bratzler
  • Sharon-Lise T Normand
  • Yun Wang
  • Walter J O'Donnell
  • Mark Metersky
  • Lein F Han
  • Michael T Rapp
  • Harlan M Krumholz

Abstract

Background: 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. Methodology/Principal Findings: 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 25th, 50th, and 75th 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). Conclusions/Significance: 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.

Suggested Citation

  • Dale W Bratzler & Sharon-Lise T Normand & Yun Wang & Walter J O'Donnell & Mark Metersky & Lein F Han & Michael T Rapp & Harlan M Krumholz, 2011. "An Administrative Claims Model for Profiling Hospital 30-Day Mortality Rates for Pneumonia Patients," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-7, April.
  • Handle: RePEc:plo:pone00:0017401
    DOI: 10.1371/journal.pone.0017401
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    1. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
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    Cited by:

    1. Harlan M Krumholz & Angela Hsieh & Rachel P Dreyer & John Welsh & Nihar R Desai & Kumar Dharmarajan, 2016. "Trajectories of Risk for Specific Readmission Diagnoses after Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-14, October.
    2. Seidu Dauda & Abe C. Dunn & Anne E. Hall, 2019. "Are Medical Care Prices Still Declining? A Systematic Examination of Quality-Adjusted Price Index Alternatives for Medical Care," BEA Working Papers 0166, Bureau of Economic Analysis.
    3. Dauda, Seidu & Dunn, Abe & Hall, Anne, 2022. "A systematic examination of quality-adjusted price index alternatives for medical care using claims data," Journal of Health Economics, Elsevier, vol. 85(C).

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