The Development, Implementation, and Evaluation of a Social Engagement Support System
University of Maryland, Baltimore County
Summary
The goal of this clinical trial is to determine if artificial intelligence and machine learning (AI/ML) models can help address social needs in Medicaid enrollees. The main questions it aims to answer are: Can AI/ML models accurately identify social needs from administrative healthcare data? Can AI/ML models accurately predict which people will engage with social supports? Researchers will compare individuals who live in different regions to see if AI/ML models perform better than the status quo.
Description
Social drivers of health (SDoH) are the largest factors affecting our health and wellbeing but are difficult for healthcare systems to address. Despite new models that provide incentives for health plans and providers to reach beyond clinical care to improve patient health outcomes, existing data infrastructures lack relevant information to support such interventions. The first problem is one of identification; providers undercode social needs in existing schemas and ancillary data collection methods such as social screens are not common, standardized, or easily shared. The second problem is a…
Eligibility
- Age range
- 18–64 years
- Sex
- All
- Healthy volunteers
- Yes
Inclusion Criteria: * Members of partner health plan aged 18-64 Exclusion Criteria: \-
Interventions
- OtherSocial Engagement Support System
In this protocol, we will develop and deploy a set of machine learning models that use multiple individual- and community-level data sources to predict which members use the emergency department to fulfill social or non-urgent needs as opposed to treatment for urgent medical conditions. These models will identify individuals whose social needs are driving inappropriate utilization so that high-risk individuals will be given enhanced outreach services to facilitate completion of a comprehensive social needs assessment. We will also develop and deploy an engagement support system that identifies and displays the characteristics of members that prevent them from engaging with a Community Based Organization (CBO). This system will use artificial intelligence techniques to identify characteristics of individuals who have historically disengaged from the social service pipeline before receiving social services and suggest potential strategies for increasing engagement.
Location
- University of Maryland, Baltimore CountyBaltimore, Maryland