At a glance
ClinicalIndex Comparison RecordStandardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Protocol for Evaluating the Effectiveness of a Clinical Decision Support System With Prediction Modeling to Identify Patients With Health-related Social Needs in the Emergency Department
In Brief
A clinical study evaluating Health-related social needs decision support system for Emergency Service, Hospital and Social Determinants of Health. Completed, enrolled 518,512 participants across 1 site.
Detailed Summary
The overall objective of this study is to support emergency department management of patients' health-related social needs. This study will measure the impact of a decision support system that informs clinicians about which patients are likely to screen positive for a health-related social need. The system uses statistical models to create a health-related social need risk score for each patient. The main questions, the study aims to answer are: * Does providing emergency department clinicians with risk scores on health-related social needs increase screening and referral activities? * Does providing emergency department clinicians with risk scores on health-related social needs change patients' use of healthcare services? The decision support system with health-related social needs risk scores will be introduced for all adult patients at one emergency department. Screening rates, referrals, and subsequent healthcare encounters will be compared with emergency departments that did not have access to the decision support system.
Study Details
Timeline
Interventions
The clinical decision support intervention will present emergency department clinicians at an Indianapolis, IN ED with a likelihood score for an adult patient screening positive for the following health-related social needs (HRSNs): housing instability, food insecurity, transportation barriers, financial strain, and history of legal involvement. For each HRSN, the likelihood of screening positive is reported as "high", "medium", or "low". These categorizations are the product of logistic regression models. The clinical decision support intervention will be delivered through an existing FHIR (Fast Healthcare Interoperability Resources) standards-based clinical decision support platform.