Findings from Yale University School of Public Health in the Area of Managed Care Described (Residual Confounding In Health Plan Performance Assessments: Evidence From Randomization In Medicaid): Managed Care - Insurance News | InsuranceNewsNet

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May 25, 2022 Newswires
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Findings from Yale University School of Public Health in the Area of Managed Care Described (Residual Confounding In Health Plan Performance Assessments: Evidence From Randomization In Medicaid): Managed Care

Insurance Daily News

2022 MAY 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on Managed Care are presented in a new report. According to news reporting originating in New Haven, Connecticut, by NewsRx journalists, research stated, “Risk adjustment is used widely in payment systems and performance assessments, but the extent to which it distinguishes plan or provider effects from confounding due to patient differences is typically unknown. To assess the degree to which risk-adjusted measures of health plan performance adequately adjust for the variation across plans that arises because of differences in patient characteristics (residual confounding).”

Financial supporters for this research include Tobin Center for Economic Policy, Arnold Ventures.

The news reporters obtained a quote from the research from the Yale University School of Public Health, “Comparison between plan performance estimates based on enrollees who made plan choices (observational population) and estimates based on enrollees assigned to plans (randomized population). Natural experiment in which more than two thirds of a state’s Medicaid population in 1 region was randomly assigned to 1 of 5 plans. 137933 enrollees in 2013 to 2014, of whom 31.1% selected a plan and 68.9% were randomly assigned to 1 of the same 5 plans. Annual total spending (that is, payments to providers), primary care use, dental care use, and avoidable emergency department visits, all scored as plan-specific deviations from the ‘average’ plan performance within each population. Enrollee characteristics were appreciably imbalanced across plans in the observational population, as expected, but were not in the randomized population. Annual total spending varied across plans more in the observational population (SD, $147 per enrollee) than in the randomized population (SD, $70 per enrollee) after accounting for baseline differences in the observational and randomized populations and for differences across plans. On average, a plan’s spending score (its deviation from the ‘average’ performance) in the observational population differed from its score in the randomized population by $67 per enrollee in absolute value (95% CI, $38 to $123), or 4.2% of mean spending per enrollee (P= 0.009, rejecting the null hypothesis that this difference would be expected from sampling error). The difference was reduced modestly by risk adjustment to $62 per enrollee (P= 0.012). Residual confounding was similarly substantial for most other performance measures. Further adjustment for social factors did not materially change estimates. Potential heterogeneity in plan effects between the 2 populations.”

According to the news reporters, the research concluded: “Residual confounding in risk-adjusted performance assessments can be substantial and should caution policymakers against assuming that risk adjustment isolates real differences in plan performance.”

This research has been peer-reviewed.

For more information on this research see: Residual Confounding In Health Plan Performance Assessments: Evidence From Randomization In Medicaid. Annals of Internal Medicine, 2022;175(3). Annals of Internal Medicine can be contacted at: Amer Coll Physicians, Independence Mall West 6TH And Race St, Philadelphia, PA 19106-1572, USA.

Our news correspondents report that additional information may be obtained by contacting Jacob Wallace, Yale University School of Public Health, New Haven, CT 06510, United States. Additional authors for this research include Anthony Lollo, Chima D. Ndumele, J. Michael McWilliams and Janet Eaton.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.7326/M21-0881. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

(Our reports deliver fact-based news of research and discoveries from around the world.)

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