Improving 30-day readmission continues to be problematic for most hospitals. This study reports the creation and validation of sex-specific inpatient (i) heart failure (HF) risk scores using electronic data from the beginning of inpatient care for effective and efficient prediction of 30-day readmission risk.

HF patients hospitalized at Intermountain Healthcare from 2005 to 2012 (derivation: n=6079; validation: n=2663) and Baylor Scott & White Health (North Region) from 2005 to 2013 (validation: n=5162) were studied. Sex-specific iHF scores were derived to predict post-hospitalization 30-day readmission using common HF laboratory measures and age. Risk scores adding social, morbidity, and treatment factors were also evaluated.

The iHF model for females utilized potassium, bicarbonate, blood urea nitrogen, red blood cell count, white blood cell count, and mean corpuscular hemoglobin concentration; for males, components were B-type natriuretic peptide, sodium, creatinine, hematocrit, red cell distribution width, and mean platelet volume. Among females, odds ratios (OR) were OR=1.99 for iHF tertile 3 vs. 1 (95% confidence interval [CI]=1.28, 3.08) for Intermountain validation (P-trend across tertiles=0.002) and OR=1.29 (CI=1.01, 1.66) for Baylor patients (P-trend=0.049). Among males, iHF had OR=1.95 (CI=1.33, 2.85) for tertile 3 vs. 1 in Intermountain (P-trend <0.001) and OR=2.03 (CI=1.52, 2.71) in Baylor (P-trend < 0.001). Expanded models using 182–183 variables had predictive abilities similar to iHF.

Sex-specific laboratory-based electronic health record-delivered iHF risk scores effectively predicted 30-day readmission among HF patients. Efficient to calculate and deliver to clinicians, recent clinical implementation of iHF scores suggest they are useful and useable for more precise clinical HF treatment.