| Autor: |
Chernew ME; Michael E. Chernew (Chernew@hcp.med.harvard.edu) is the Leonard D. Schaeffer Professor of Health Care Policy in the Department of Health Care Policy, Harvard Medical School, in Boston, Massachusetts., Carichner J; Jessica Carichner is a research assistant in the Department of Health Care Policy, Harvard Medical School, and a master of public health student in the Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, in Boston, Massachusetts., Impreso J; Jeron Impreso is an advisory analyst for Medicaid at Mathematica in Washington, D.C. He was a research associate for health policy, Committee for a Responsible Federal Budget, in Washington, D.C., when this work was conducted., McWilliams JM; J. Michael McWilliams is the Warren Alpert Foundation Professor of Health Care Policy in the Department of Health Care Policy, Harvard Medical School, and a professor of medicine and general internist at Brigham and Women's Hospital, in Boston, Massachusetts., McGuire TG; Thomas G. McGuire is a professor of health economics in the Department of Health Care Policy, Harvard Medical School., Alam S; Sartaj Alam is a statistician in the Department of Health Care Policy, Harvard Medical School., Landon BE; Bruce E. Landon is a professor of health care policy in the Department of Health Care Policy, Harvard Medical School, and a professor of medicine and practicing internist at Beth Israel Deaconess Medical Center, in Boston, Massachusetts., Landrum MB; Mary Beth Landrum is a professor of health care policy in the Department of Health Care Policy, Harvard Medical School. |
| Abstrakt: |
Claims data, which form the foundation of risk adjustment in payment for health care services, may reflect efforts to capture more-or more severe-clinical conditions rather than true changes in health status. This can distort payments. We quantify this in the context of Medicare's accountable care organization (ACO) program by comparing risk scores derived from two different measurement approaches. One approach uses diagnoses coded on claims based on Centers for Medicare and Medicaid Services Hierarchical Condition Categories (HCC), and the other uses self-reported, survey-based health data from the Consumer Assessment of Healthcare Providers and Systems (CAHPS). During 2013-16 HCC-based risk scores grew faster than CAHPS-based risk scores (2.1 percent versus 0.3 percent annually), and the gap in HCC- and CAHPS-based risk score growth varied widely across ACOs. The average gap in risk score growth appears to be the result primarily of HCC coding practices rather than poor performance of the CAHPS model, suggesting that coding practices (not necessarily driven by ACO contracts) may account for most of the observed risk score growth for ACO beneficiaries. |
