Findings from Johns Hopkins University Provides New Data about Electronic Medical Records (Impact of Social Needs In Electronic Health Records and Claims On Health Care Utilization and Costs Risk-adjustment Models Within Medicaid Population): Information Technology – Electronic Medical Records

2022 JUL 19 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on Information Technology - Electronic Medical Records are presented in a new report. According to news reporting originating from Baltimore, Maryland, by NewsRx correspondents, research stated, “Patients enrolled in Medicaid have significantly higher social needs (SNs) than others. Using claims and electronic health records (EHRs) data, managed care organizations (MCOs) could systemically identify high-risk patients with SNs and develop population health management interventions.”

Our news editors obtained a quote from the research from Johns Hopkins University, “Impact of SNs on models predicting health care utilization and costs was assessed. This retrospective study included claims and EHRs data on 39,267 patients younger than age 65 years who were continuously enrolled during 2018-2019 in a Medicaid-managed care plan. SN marker was developed suggesting presence of International Classification of Diseases, 10th revision codes in any of the 5 SN domains. Impact of SN marker was compared across demographic and 2 diagnosis-based (ie, Charlson and Adjusted Clinical Groups risk score) prediction models of emergency department (ED) visit and hospitalizations, and total, medical, and pharmacy costs. After combining data sources, prevalence of documented SN marker increased from 11% and 13% to 18% of the study population across claims, EHRs, and both combined, respectively. SN marker improved predictions of demographic models for all utilization and total costs outcomes (area under the curve [AUC] of ED model increased from 0.57 to 0.61 and R-2 of total cost model increased from 10.9 to 12.2). In both diagnosis-based models, adding SN marker marginally improved outcomes prediction (AUC of ED model increased from 0.65 to 0.66).”

According to the news editors, the research concluded: “This study demonstrated feasibility of using claims and EHRs data to systematically capture SNs and incorporate in prediction models that could enable MCOs and policy makers to adjust and develop effective population health interventions.”

This research has been peer-reviewed.

For more information on this research see: Impact of Social Needs In Electronic Health Records and Claims On Health Care Utilization and Costs Risk-adjustment Models Within Medicaid Population. Population Health Management, 2022. Population Health Management can be contacted at: Mary Ann Liebert, Inc, 140 Huguenot Street, 3RD Fl, New Rochelle, NY 10801, USA. (Mary Ann Liebert, Inc. - www.liebertpub.com; Population Health Management - http://www.liebertpub.com/overview/population-health-management-formerly-disease-management/301/)

The news editors report that additional information may be obtained by contacting Chintan J. Pandya, Johns Hopkins University Bloomberg Sch Publ Hlth, Ctr Populat Hlth Informat Technol, Dept. of Health Policy and Management, 624 N Broadway, Room 602, Baltimore, MD 21205, United States. Additional authors for this research include Elham Hatef, Thomas Richards, Jonathan P. Weiner, Hadi Kharrazi and JunBo Wu.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1089/pop.2022.0069. 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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