Frailty, a disorder of impaired recovery after illness, is closely linked to mortality, but is not accounted for by many large-scale risk adjustment metrics since rigorous measurement of frailty can be time-intensive. Thus, it is unclear if failure to account for frailty in risk adjustment methods results in undue penalties for hospitals taking care of large numbers of frail individuals.
In a retrospective cohort analysis of 785,127 Medicare Fee-for-Service beneficiaries, Kundi et al. used a claims-based frailty index – known as the Hospital Frailty Risk Score (HFRS) –to overcome the problem of time-intensive frailty measurement. The HFRS is a frailty index tied to clusters of resource utilization developed in a British population and subsequently externally validated in a Canadian population. The HFRS was created to further define patients at risk for poor outcomes by evaluating which administrative billing codes best identify individuals with prolonged hospital stay, increased rates of readmission, and increased rates of mortality. These billing codes were then tallied to categorize patients into 3 risk groups including low (<5), intermediate (5-15), and high (>15) risk. The HFRS has subsequently been associated with increased mortality after transcatheter aortic valve replacement (TAVR) within the United States.
In the current study, Kundi et al. found that including the HFRS in the risk adjustment model used to calculate risk-standardized 30-day readmission rates (RSRSs) for acute myocardial infarction, heart failure, and pneumonia hospitalizations improved prediction of 30-day readmission and short-term mortality compared to use of clinical comorbidities alone. Across all 3 conditions, addition of the HFRS resulted in a statistically significant (p < 0.001) improvement in prediction of 30-day readmission and short-term mortality after adjusting for age, sex, race, and other comorbidities. These results imply that hospitals caring for high numbers of frail individuals may be disproportionately penalized for the quality of care delivered if frailty is not considered in risk adjustment algorithms, including the one used by the Centers for Medicare and Medicaid Services (CMS).
Notably, frailty as defined by the HFRS only moderately correlates with two common definitions used by Fried and Rockwood. The HFRS defines frailty according to clusters of increased health resource utilization and adverse outcomes, so-called “utilization frailty,” and thus represents a distinct definition that may correlate only moderately with “syndromic frailty.” Nevertheless, as this and other papers suggest, this definition identifies a higher risk subpopulation that is relevant to both clinical risk prediction and high healthcare utilization. This classification of frailty is increasingly important as the Medicare population continues to age and hospitals seek to tailor their post-discharge care for these high utilizing individuals.
In summary, the recent publication by Kundi et al. highlights the importance of risk adjustment for “utilization frailty” when assessing risk of short-term readmission and mortality after hospitalizations for three common acute medical conditions. As detailed in the study, the HFRS could be used to identify and create care plans for patients that are high risk for readmission and mortality. Future research is needed to identify if hospitals that take care of higher numbers of frail patients are disproportionality penalized under the Hospital Readmissions Reduction Program (HRRP). In addition, the role of hospital-based interventions for high-risk frail patients to prevent adverse post-acute care outcomes warrants further inquiry.
By: Lila M Martin, MD, MPH; Jordan B Strom, MD, MSc, FACC, FASE
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