title: A hybrid Centers for Medicaid and Medicare service mortality model in 3 diagnoses.
abstract: BACKGROUND
  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.
authors.affiliation: Veterans Health Administration Inpatient Evaluation Center, Office of Quality and Safety, Washington, DC, USA. marta.render@va.gov
authors.forename: Marta L
authors.initials: ML
authors.lastname: Render
authors.forename: Peter L
authors.initials: PL
authors.lastname: Almenoff
authors.forename: Annette
authors.initials: A
authors.lastname: Christianson
authors.forename: Anne E
authors.initials: AE
authors.lastname: Sales
authors.forename: Tammy
authors.initials: T
authors.lastname: Czarnecki
authors.forename: Jim A
authors.initials: JA
authors.lastname: Deddens
authors.forename: Ron W
authors.initials: RW
authors.lastname: Freyberg
authors.forename: Julie
authors.initials: J
authors.lastname: Eyman
authors.forename: Timothy P
authors.initials: TP
authors.lastname: Hofer
mesh_terms: D000367:Age Factors; D000368:Aged; D014487:Centers for Medicare and Medicaid Services, U.S. / Q000706:statistics & numerical data*; D019411:Clinical Laboratory Techniques; D015897:Comorbidity; D003625:Data Collection / Q000379:methods*; D006333:Heart Failure / Q000401:mortality*; D006787:Hospitals, Veterans; D006801:Humans; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000401:mortality*; D011014:Pneumonia / Q000401:mortality*; D020379:Risk Adjustment; D014481:United States / Q000453:epidemiology