Measuring Frailty More Accurately Predicts Cost of Care
A team of researchers, led by Kenton Johnston, Ph.D., of Saint Louis University’s College for Public Health and Social Justice, identified a way to measure frailty using patients’ medical claims that more accurately predicts costs-of-care, especially for clinicians with disproportionate shares of frail patients.
The findings, “Relationship of a Claims-Based Frailty Index to Annualized Medicare Costs: A Cohort Study,” published online April 7 in the Annals of Internal Medicine.
Johnston, an assistant professor of health management and policy, and his co-authors Hefei Wen, Ph.D., of Harvard Medical School and Harvard Pilgrim Health Care Institute, and Karen E. Joynt Maddox, M.D., assistant professor of cardiology at Washington University School of Medicine in St. Louis, find that adding this measure to Medicare’s value-based payment models could lead to fairer reimbursement for clinicians with high-needs patients.
The researchers used the annual Medicare Current Beneficiary Survey (MCBS) linked to respondents' fee-for-service (FFS) Medicare claims and administrative data for 2006 to 2013 to determine whether adding a claims-based frailty index (CFI) measure could improve Medicare cost prediction. The MCBS is an annual, nationally representative survey of the Medicare population.
Frail patients are those who exhibit an accumulation of functional health deficits such as difficulty with activities of daily living (e.g. bathing and dressing) as well as those who exhibit physical signs such as exhaustion, weakness, slowing, loss of energy, and reduced activity.
Medicare currently does not adjust for patient frailty in its value-based payment models which reward Medicare clinicians for keeping patient cost-of-care low despite complex needs. But as Medicare moves toward value-based payments, entities are held increasingly accountable for beneficiaries’ cost of care.
“This means that clinicians who care for a disproportionate share of frail patients, such as geriatricians, may be unfairly financially penalized for caring for vulnerable frail patients,” Johnston said.
They found that incorporating CFI data into cost prediction for annualized Medicare costs (AMCs) improved on the standard Centers for Medicare & Medicaid Services Hierarchical Condition Category (CMS-HCC) model on average, especially among frail and dually enrolled Medicare beneficiaries.
“Accurately predicting AMCs for frail patients matters because it means clinicians will receive fairer performance-based reimbursement that does not penalize them for applying the additional medical resources they need to treat frail patients,” Johnston said. “As a result, more clinicians will be willing to treat frail patients, a growing population in an aging society.”
The researchers caution that because individual-level cost prediction remains poor, ongoing advancements in methodology are needed.
Saint Louis University purchased and provided access to the data used in this study. The funder had no role in the design or conduct of the study.
The Saint Louis University College for Public Health and Social Justice is the only academic unit of its kind, studying social, environmental and physical influences that together determine the health and well-being of people and communities. It also is the only accredited school or college of public health among nearly 250 Catholic institutions of higher education in the United States.
Guided by a mission of social justice and focus on finding innovative and collaborative solutions for complex health problems, the College offers nationally recognized programs in public health, social work, health administration, applied behavior analysis, and criminology and criminal justice.