Applications of Claims-Based Frailty Index to Advance Evidence for Frailty-Guided Decision-Making

PROJECT SUMMARY/ABSTRACT Older adults with frailty are more likely to experience poor health outcomes after acute illnesses, drug-related adverse events, and surgeries. Health care costs for frail patients double due to acute hospital care, post-acute care, and treatments for preventable conditions. Despite clinical and societal consequences of frailty, frailty is rarely assessed in clinical practice and little evidence exists on how to integrate frailty to inform clinical care and population health management. The critical step to generate this evidence is to measure frailty on a large scale with high accuracy and efficiency. To address this need, the investigator team recently developed and validated a claims-based frailty index (CFI), which enables measurement of frailty from Medicare data for large populations when in-person assessment is not feasible. The objective of this application is to generate evidence needed for frailty-guided clinical care and population health management by applying CFI to claims data-based studies of drug therapy; pragmatic clinical trials of procedural therapy; and electronic health records (EHR)-Medicare linked data of a health care system. The central hypothesis is that frailty information will improve care of older adults by uncovering meaningful variations in the treatment benefit-harm profile, costs, and resource needs. To test this hypothesis, the investigator team with extensive expertise in frailty, pharmacoepidemiologic methods, and health services research will accomplish the following specific aims in the next 5 years: 1) determine how frailty changes the benefits and harms of 10 prescription drugs for chronic conditions in older adults by applying CFI to the 2014-2022 5% Medicare random sample; 2) determine how frailty changes the benefits and harms of procedural therapies in older adults by applying CFI to Medicare data linked to 2 ongoing pragmatic clinical trials of endovascular vs surgical revascularization therapy for peripheral arterial disease and acupuncture vs usual care for chronic low back pain; and 3) determine whether implementing CFI to EHR-Medicare linked data can predict high-cost and high-need patients in a large health care system in Boston, Massachusetts. The innovative applications of CFI are readily scalable to claims-based comparative effectiveness and safety studies, clinical trials, and EHR in health care systems. The impact of this research is significant because the clinically actionable evidence generated from this research can enable optimal choice of drug and procedural therapy and a health system-wide risk stratification based on frailty. Ultimately, these results will accelerate integration of frailty in routine care and facilitate frailty-guided clinical care and population health management.