Introduction: Reliance on administrative data sources and a cohort with restricted age range (Medicare 65 y and above) may limit conclusions drawn from public reporting of 30-day mortality rates in 3 diagnoses [acute myocardial infarction (AMI), congestive heart failure (CHF), pneumonia (PNA)] from Center for Medicaid and Medicare Services.
Methods: We categorized patients with diagnostic codes for AMI, CHF, and PNA admitted to 138 Veterans Administration hospitals (2006–2009) into 2 groups (less than 65 y or ALL), then applied 3 different models that predicted 30-day mortality [Center for Medicaid and Medicare Services administrative (ADM), ADM+laboratory data (PLUS), and clinical (CLIN)] to each age/diagnosis group. C statistic (CSTAT) and Hosmer Lemeshow Goodness of Fit measured discrimination and calibration. Pearson correlation coefficient (r) compared relationship between the hospitals’ risk-standardized mortality rates (RSMRs) calculated with different models. Hospitals were rated as significantly different (SD) when confidence intervals (bootstrapping) omitted National RSMR.
Results: The ≥65-year models included 57%–67% of all patients (78%–82% deaths). The PLUS models improved discrimination and calibration across diagnoses and age groups (CSTAT—CHF/65 y and above: 0.67 vs. 0. 773 vs. 0.761; ADM/PLUS/CLIN; Hosmer Lemeshow Goodness of Fit significant 4/6 ADM vs. 2/6 PLUS). Correlation of RSMR was good between ADM and PLUS (r—AMI 0.859; CHF 0.821; PNA 0.750), and 65 years and above and ALL (r>0.90). SD ratings changed in 1%–12% of hospitals (greatest change in PNA).
Conclusions: Performance measurement systems should include laboratory data, which improve model performance. Changes in SD ratings suggest caution in using a single metric to label hospital performance.
*Veterans Health Administration Inpatient Evaluation Center, Office of Quality and Safety, Washington, DC
†Division of Pulmonary Critical Care and Sleep, University of Cincinnati College of Medicine, Cincinnati, OH
‡Division of Pulmonary Critical Care Sleep, University of Kansas School of Medicine, Kansas City, KS
§VA HSR&D Center of Excellence, Ann Arbor, MI
∥University of Michigan College of Nursing, Ann Arbor, MI
¶Veterans Health Administration Office of Quality and Performance, Washington D.C
#University of Cincinnati College of Mathematical Sciences, Cincinnati, OH
**Division of Internal Medicine, University of Michigan, Ann Arbor, MI
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The study was funded by Veterans Health Administration.
The authors declare no conflict of interest.
Reprints: Marta L. Render, MD, 3200 Vine St (111f) Cincinnati, OH 45220. E-mail: email@example.com.