Working Paper: NBER ID: w23765
Authors: Keith Marzilli Ericson; Kimberley Geissler; Benjamin Lubin
Abstract: 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.
Keywords: Risk Adjustment; Healthcare Market Competition; Partial-Year Enrollment
JEL Codes: I11; I13; I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| enrollment duration (C41) | likelihood of missed diagnoses (C52) |
| missed diagnoses (I12) | lower predicted spending for partial-year enrollees (H51) |
| one-month enrollees (I13) | systematically less care than full-year enrollees (I18) |
| scaling method for observed diagnoses (C22) | correction of underpayment issue (H26) |
| missed diagnosis effect (C32) | systematic underprediction of spending for partial-year enrollees (H51) |
| partial-year enrollment (I23) | systematic underprediction of spending (H68) |