Objective: To assess how beneficiary premiums, expected out-of-pocket costs, and plan finances in the Medicare Advantage (MA) market are related to coding intensity.
Data sources/study setting: MA plan characteristics and administrative records from the Centers for Medicare and Medicaid Services (CMS) for the sample of beneficiaries enrolled in both MA and Part D between 2008 and 2015. Medicare claims and drug utilization data for Traditional Medicare (TM) beneficiaries were used to calibrate an independent measure of health risk.
Study design: Coding intensity was measured by comparing the CMS risk score for each MA contract with a contract level risk score developed using prescription drug data. We conducted regressions of plan outcomes, estimating the relationship between outcomes and coding intensity. To develop prescription drug scores, we assigned therapeutic classes to beneficiaries based on their prescription drug utilization. We then regressed nondrug spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used the coefficients to predict relative risk.
Principal findings: We found that, for each $1 increase in potential revenue resulting from coding intensity, MA plan bid submissions declined by $0.10 to $0.19, and another $0.21 to $0.45 went toward reducing plans' medical loss ratios, an indication of higher profitability. We found only a small impact on beneficiary's projected out-of-pocket costs in a plan, which serves as a measure of the generosity of plan benefits, and a $0.11 to $0.16 reduction in premiums. As expected, coding intensity's effect on bids was substantially larger in counties with higher levels of MA competition than in less competitive counties.
Conclusions: While coding intensity increases taxpayers' costs of the MA program, enrollees and plans both benefit but with larger gains for plans. The adoption of policies to more completely adjust for coding intensity would likely affect both beneficiaries and plan profits.
Keywords: Medicare advantage; clinical coding; cost sharing; insurance premiums; managed competition.
© 2020 Health Research and Educational Trust.