Association of entirely claims-based frailty indices with long-term outcomes in patients with acute myocardial infarction, heart failure, or pneumonia: a nationwide cohort study in Turkey

Abstract

ABSTRACT Background Several countries have increasingly focused on improving care for acute myocardial infarction (AMI), heart failure (HF), and pneumonia to reduce their readmissions and mortality rates. Frailty is becoming increasingly important to accurately predict healthcare utilization for the aging population. The preferred method for the measurement of frailty remains unclear, and current risk-adjustment models do not account for frailty. We sought to compare commonly used frailty indices in terms of the ability to predict clinical adverse outcomes in AMI, HF, and pneumonia patients. Methods A nationwide cohort study included AMI, HF, and pneumonia with 65 years and older patients in the Turkey between January 1 and December 31, 2018. The primary predictor of interest was frailty. We used two claims-based frailty indices (Johns Hopkins Claims-Based Frailty Index and Hospital Frailty Risk Score) to assess frailty. The main outcome was all-cause long-term mortality up to 3 years. Time to death was calculated as the time period between the date of first admission and the date of death. Patients were censored as of September 30, 2020, which marked the end of the follow-up period. Findings Of the 200,948 patients, 35,096 (17.5%) had AMI, 62,403 (31.1%) had HF, and 103,449 (51.5%) had pneumonia. Johns Hopkins Claims-Based Frailty Index (c-statistics for long-term mortality: 0.68 in AMI, 0.61 in HF, 0.64 in pneumonia) was better compared to Hospital Frailty Risk Score (c-statistics for long-term mortality: AMI=0.62, HF=0.58, pneumonia=0.62) (DeLong p Interpretation Readmission and mortality rates after AMI, HF, and pneumonia gradually increases with increasing frailty score. While the Hospital Frailty Risk Score had a better discrimination for predicting readmissions, Johns Hopkins Claims-Based Frailty Index had a better discrimination for predicting mortality. These findings should be taken into account for a better evaluation of hospital performance. Funding This study was supported by funding from The Scientific and Technological Research Council of Turkey (grant 120S422, HK).