Impact of the method of calculating 30-day readmission rate after hospitalization for heart failure. Data from the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry.

Abstract

Thirty-day readmission rate after heart failure (HF) hospitalization is widely used to evaluate healthcare quality. Methodology may substantially influence estimated rates. We assessed the impact of different definitions on HF and all-cause readmission rates. Readmission rates were examined in 1,835 patients discharged following HF hospitalization using 64 unique definitions derived from five methodological factors: (1) ICD-10 codes (broad vs narrow), (2) index admission selection (single admission only first-in-year vs. random sample; or multiple admissions in year with vs. without 30-day blanking period), (3) variable denominator (number alive at discharge vs. number alive at 30-days), (4) follow-up period start (discharge date vs day following discharge), and (5) annual reference-period (calendar vs fiscal). The impact of different factors was assessed using linear-regression. The calculated 30-day readmission rate for HF varied more than 2-fold depending solely on the methodological approach (6.5% to 15.0%). All-cause admission rates exhibited similar variation (18.8% to 29.9%). The highest rates included all consecutive index admissions (HF 11.1-15.0%, all-cause 24.0-29.9%), and lowest only one index admission per patient per year (HF 6.5-11.3%, all-cause 18.8-22.7%). When including multiple index admissions and compared to blanking the 30-days post-discharge, not blanking was associated with 2.3% higher readmission rates. Selecting a single admission per year with a first-in-year approach lowered readmission rates by 1.5%, while random-sampling admissions lowered estimates further by 5.2% (p<0.001). Calculated 30-day readmission rates varied more than 2-fold by altering methods. Transparent and consistent methods are needed to ensure reproducible and comparable reporting.