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来源类型Working Paper
规范类型报告
DOI10.3386/w23765
来源IDWorking Paper 23765
The Impact of Partial-Year Enrollment on the Accuracy of Risk Adjustment Systems: A Framework and Evidence
Keith Marzilli Ericson; Kimberley Geissler; Benjamin Lubin
发表日期2017-09-11
出版年2017
语种英语
摘要Accurate risk adjustment facilitates healthcare market competition. Risk adjustment typically aims to predict annual costs of individuals enrolled in an insurance plan for a full year. However, partial-year enrollment is common and poses a challenge to risk adjustment, since diagnoses are observed with lower probability when individual is observed for a shorter time. Due to missed diagnoses, risk adjustment systems will underpay for partial-year enrollees, as compared to full-year enrollees with similar underlying health status and usage patterns. We derive a new adjustment for partial-year enrollment in which payments are scaled up for partial-year enrollees’ observed diagnoses, which improves upon existing methods. We simulate the role of missed diagnoses using a sample of commercially insured individuals and the 2014 Marketplace risk adjustment algorithm, and find the expected spending of six-month enrollees is underpredicted by 19%. We then examine whether there are systematically different care usage patterns for partial-year enrollees in this data, which can offset or amplify underprediction due to missed diagnoses. Accounting for differential spending patterns of partial-year enrollees does not substantially change the underprediction for six-month enrollees. However, one-month enrollees use systematically less than one-twelfth the care of full-year enrollees, partially offsetting the missed diagnosis effect.
主题Health, Education, and Welfare ; Health
URLhttps://www.nber.org/papers/w23765
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/581439
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Keith Marzilli Ericson,Kimberley Geissler,Benjamin Lubin. The Impact of Partial-Year Enrollment on the Accuracy of Risk Adjustment Systems: A Framework and Evidence. 2017.
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