Risk Adjustment in Health Insurance Markets: Do Not Overlook the “Real” Healthy

Richard van Kleef*, Rene van Vliet, Michel Oskam

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Objectives:
The goals of this paper are (1) to identify groups of healthy people and (2) to quantify the extent to which the Dutch risk adjustment (RA) model overpays insurers for these groups.

Background:
There have been strong signals that insurers in the Dutch regulated health insurance market engage in actions to attract healthy people. A potential explanation for this behavior is that the Dutch RA model overpays insurers for healthy people.

Methods:
We identify healthy groups using 3 types of ex-ante information (ie, information available before the start of the health insurance contract): administrative data on prior spending for specific health care services (N = 17 m), diagnoses from electronic patient records (N = 1.3 m), and health survey data (N = 457 k). In a second step, we calculate the under/overpayment for these groups under the Dutch RA model (version: 2021).

Results:
We distinguish eight groups of healthy people using various “identifiers.” Although the Dutch RA model substantially reduces the predictable profits that insurers face for these groups, significant profits remain. The mean per person overpayment ranges from 38 euros (people with hospital spending below the third quartile in each of 3 prior years) to 167 euros (those without any medical condition according to their electronic patient record).

Conclusions:
The Dutch RA model does not eliminate the profitability of healthy groups. The identifiers used for flagging these groups, however, seem inappropriate for serving as risk adjuster variables. An alternative way of exploiting these identifiers and eliminating the profitability of healthy groups is to estimate RA models with “constrained regression.”
Original languageEnglish
JournalMedical Care
DOIs
Publication statusE-pub ahead of print - 3 Dec 2023

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