Derivation and Validation of an In-Hospital Mortality Prediction Model Suitable for Profiling Hospital Performance in Heart Failure

J Am Heart Assoc. 2018 Feb 8;7(4):e005256. doi: 10.1161/JAHA.116.005256.


Background: Comparing heart failure (HF) outcomes across hospitals requires adequate risk adjustment. We aimed to develop and validate a model that can be used to compare quality of HF care across hospitals.

Methods and results: We included patients with HF aged ≥18 years admitted to one of 433 hospitals that participated in the Premier Inc Data Warehouse. This model (Premier) contained patient demographics, comorbidities, and acute conditions present on admission, derived from administrative and billing records. In a separate data set derived from electronic health records, we validated the Premier model by comparing hospital risk-standardized mortality rates calculated with the Premier model to those calculated with a validated clinical model containing laboratory data (LAPS [Laboratory-Based Acute Physiology Score]). Among the 200 832 admissions in the Premier Inc Data Warehouse, inpatient mortality was 4.0%. The model showed acceptable discrimination in the warehouse data (C statistic 0.75; 95% confidence interval, 0.74-0.76). In the validation data set, both the Premier model and the LAPS models showed acceptable discrimination (C statistic: Premier: 0.76 [95% confidence interval, 0.74-0.77]; LAPS: 0.78 [95% confidence interval, 0.76-0.80]). Risk-standardized mortality rates for both models ranged from 2% to 7%. A linear regression equation describing the association between Premier- and LAPS-specific mortality rates revealed a regression line with a slope of 0.71 (SE: 0.07). The correlation coefficient of the standardized mortality rates from the 2 models was 0.82.

Conclusions: Compared with a validated model derived from clinical data, an HF mortality model derived from administrative data showed highly correlated risk-standardized mortality rate estimates, suggesting it could be used to identify high- and low-performing hospitals for HF care.

Keywords: heart failure; mortality; quality of care.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Data Warehousing
  • Female
  • Healthcare Disparities*
  • Heart Failure / diagnosis
  • Heart Failure / mortality*
  • Heart Failure / physiopathology
  • Heart Failure / therapy*
  • Hospital Mortality*
  • Humans
  • Male
  • Middle Aged
  • Outcome and Process Assessment, Health Care*
  • Quality Indicators, Health Care*
  • Reproducibility of Results
  • Risk Assessment
  • Risk Factors
  • Time Factors