Decision Support System for Social Needs in ER

Recruiting at 1 trial location

Overseen By Joshua R Vest, PhD, MPH

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Indiana University

Disqualifiers: Critical illness, Transferred patients, Death, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

48000 Participants Needed

Trial Summary

Do I have to stop taking my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment Health-related social needs decision support system?

Research shows that screening for social needs in emergency departments can help connect patients with necessary social services, potentially improving health outcomes and reducing healthcare costs. Additionally, decision support systems can enhance patient safety by providing best practice guidelines, which can be customized to fit different clinical environments. ^{1 2 3 4 5}

Is the Decision Support System for Social Needs in the ER safe for humans?

The research articles do not provide specific safety data for the Decision Support System for Social Needs in the ER or similar systems. ^{2 6 7 8 9}

How does the Decision Support System for Social Needs in ER differ from other treatments for addressing social needs in healthcare?

This treatment is unique because it uses a decision support system that leverages natural language processing to identify and document social needs from unstructured electronic health records, making it easier for healthcare providers to address these needs without increasing their documentation workload. ^{5 7 10 11 12}

What is the purpose of this trial?

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.

Research Team

Joshua R Vest, PhD,MPH

Principal Investigator

Indiana University

Eligibility Criteria

This trial is for emergency department (ED) staff. It's designed to see if using a decision support system, which includes machine learning model results, helps them better screen patients for health-related social needs and potentially reduce repeat ED visits.

Exclusion Criteria

Individuals seeking care in other settings

Timeline

Screening

Participants are screened for eligibility to participate in the trial

At time of emergency department encounter (or within 24 hours)

Intervention

Introduction of the decision support system with health-related social needs risk scores for all adult patients at one emergency department

Ongoing during emergency department encounters

Follow-up

Participants are monitored for emergency department revisits and primary care visits after the initial encounter

30 days

Treatment Details

Interventions

• Health-related social needs decision support system

Trial Overview The intervention being tested is a decision support system that provides reminders to ED providers about patients' social needs based on past data. The study will measure the effectiveness of this tool in increasing screening rates and reducing return visits to the ER.

Participant Groups

Group I: Decision support intervention group Experimental Treatment 1 Intervention

Adult ED patients seeking care the ED site with the health-related social needs decision support system live.

Group II: Comparison group Active Control 1 Intervention

Adult ED patients created using statistical matching from ED sites in the same metropolitan area.

Who Is Running the Clinical Trial?

Indiana University

Lead Sponsor

Trials

1,063

Recruited

1,182,000+

References

1. United States pubmed.ncbi.nlm.nih.gov

Evaluating a social risk screening and referral program in an urban safety-net hospital emergency department. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

A descriptive study of screening and navigation on health-related social needs in a safety-net hospital emergency department. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

Decision support and patient safety: the time has come. [2011]

4. England pubmed.ncbi.nlm.nih.gov

Patients' needs in hospital: nurses' and patients' views. [2019]

5. United States pubmed.ncbi.nlm.nih.gov

Addressing Social Needs in the Clinical Setting: Description of Needs Identified in a Quality Improvement Pilot Across 3 Community Hospital Service Areas. [2022]

6. United States pubmed.ncbi.nlm.nih.gov

"Addressing the bigger picture": A qualitative study of internal medicine patients' perspectives on social needs data collection and use. [2023]

7. England pubmed.ncbi.nlm.nih.gov

Implementation context for addressing social needs in a learning health system: a qualitative study. [2022]

8. United States pubmed.ncbi.nlm.nih.gov

Prevalence of Emergency Department Social Risk and Social Needs. [2021]

9. United States pubmed.ncbi.nlm.nih.gov

2021 SAEM Consensus Conference Proceedings: Research Priorities for Developing Emergency Department Screening Tools for Social Risks and Needs. [2022]

10. United States pubmed.ncbi.nlm.nih.gov

Application of natural language processing to identify social needs from patient medical notes: development and assessment of a scalable, performant, and rule-based model in an integrated healthcare delivery system. [2023]

11. United States pubmed.ncbi.nlm.nih.gov

Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration. [2019]

12. United States pubmed.ncbi.nlm.nih.gov

Supporting the Capture of Social Needs Through Natural Language Processing. [2023]