Harvard University Reports Findings in Healthcare Information Technology (Identifying undercompensated groups defined by multiple attributes in risk adjustment): Information Technology – Healthcare Information Technology

2021 OCT 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Information Technology - Healthcare Information Technology is the subject of a report. According to news originating from Cambridge, Massachusetts, by NewsRx correspondents, research stated, “To identify undercompensated groups in plan payment risk adjustment that are defined by multiple attributes with a systematic new approach, improving on the arbitrary and inconsistent nature of existing evaluations. Extending the concept of variable importance for single attributes, we construct a measure of ‘group importance’ in the random forests algorithm to identify groups with multiple attributes that are undercompensated by current risk adjustment formulas.”

Funders for this research include National Science Foundation, National Institute of Health.

Our news journalists obtained a quote from the research from Harvard University, “Using 2016-2018 IBM MarketScan and 2015-2018 Medicare claims and enrolment data, we evaluate two risk adjustment scenarios: the risk adjustment formula used in the individual health insurance Marketplaces and the risk adjustment formula used in Medicare. A number of previously unidentified groups with multiple chronic conditions are undercompensated in the Marketplaces risk adjustment formula, while groups without chronic conditions tend to be overcompensated in the Marketplaces. The magnitude of undercompensation when defining groups with multiple attributes is many times larger than with single attributes. No complex groups were found to be consistently undercompensated or overcompensated in the Medicare risk adjustment formula. Our method is effective at identifying complex undercompensated groups in health plan payment risk adjustment where undercompensation creates incentives for insurers to discriminate against these groups.”

According to the news editors, the research concluded: “This work provides policy-makers with new information on potential targets of discrimination in the healthcare system and a path towards more equitable health coverage.”

For more information on this research see: Identifying undercompensated groups defined by multiple attributes in risk adjustment. BMJ Health & Care Informatics, 2021;28(1).

The news correspondents report that additional information may be obtained from Anna Zink, PhD Candidate in Health Policy, Harvard University, Cambridge, Massachusetts, United States.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1136/bmjhci-2021-100414. 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.

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