2021 OCT 06 (NewsRx) – By a Journalist-Staff News Editor at Daily Insurance News – New research on information technologies – Information technologies for health are the subject of a report. According to news from Cambridge, Massachusetts, per NewsRx correspondents, the research said: “To identify the undercompensated groups in the scheme payment risk adjustment that are defined by multiple attributes with a new systematic approach, improving the arbitrary and inconsistent nature of assessments existing. By expanding the concept of variable importance for unique attributes, we construct a measure of “group importance” in the random forests algorithm to identify groups with multiple attributes that are undercompensated by the adjustment formulas. current risk. “
Funders of this research include National Science Foundation, National Institute of Health.
Our press reporters got a research citation from Harvard University, âUsing IBM MarketScan 2016-2018 and Medicare claims and enrollment data 2015-2018, we assess two risk adjustment scenarios: the risk adjustment formula used in the individual health insurance and the risk adjustment formula used in Medicare. A number of previously unidentified groups with multiple chronic conditions are undercompensated in the markets risk adjustment formula, while groups without chronic conditions tend to be overcompensated in the markets. The extent of undercompensation when defining groups with multiple attributes is several times greater than with single attributes. No complex group has been consistently undercompensated or overcompensated in Medicare’s risk adjustment formula. Our method is effective in identifying complex undercompensated groups in health plan payment risk adjustment, where undercompensation causes insurers to discriminate against these groups.
According to the editors, the research concluded: âThis work provides policy makers with new information on potential targets of discrimination in the health system and a path to more equitable health coverage.
For more information on this research, see: Identifying Undercompensated Groups Defined by Multiple Attributes in Risk Adjustment. BMJ health and care informatics, 2021; 28 (1).
Press correspondents report that further information can be obtained from Anna zink, PhD student in health policy, Harvard University, Cambridge, Massachusetts, United States.
The direct object identifier (DOI) for this additional information is: https://doi.org/10.1136/bmjhci-2021-100414. This DOI is a link to an electronic document online that is free or to purchase, and can be your direct source for a journal article and its citation.
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