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Completed NCT05846685

Patient Perspectives of an Automated Falls-Risk Screening and Referral Tool in the Emergency Department (ED)

Conditions: Falls-Risk

Sex: All
Ages: 65 Years – N/A
Healthy volunteers: No
Enrollment: 10
Sponsor: University of Wisconsin, Madison

Location: Swedish American Emergency Department Rockford Illinois

Summary

The purpose of the overall study to evaluate implementation-related outcomes of a falls-risk clinical decision support (CDS) system using patient electronic health records (EHR) data to automatically screen and identify older adult ED patients at high risk of future falls and allowing ED clinicians to place referral orders to the UW Health Mobility and Falls clinic. This CDS tool has already been implemented at the UWHC ED, and will be additionally implemented at The American Center and Swedish American Hospital EDs (all QI initiatives) over the next two years. This study involves engaging a sample of referred patients from each site to gather their perspectives on the delivery of the referral in the ED, their experiences in making and completing appointments at the Falls Clinic (if applicable), and perceived benefits of the intervention overall.

Eligibility Criteria

Inclusion Criteria: * ED patients identified by the automated system as being high-risk of future falls, and subsequently referred to the UW Health Mobility and Falls Clinic by the ED provider at discharge. * English-speaking * Reliable access to a working telephone and can accept incoming phone calls * For In-person interviews in the ED: * ED patients age 65 and older in the emergency department for any reason who are identified as likely to be discharged by their clinical team. Exclusion Criteria: * Incarcerated or in police custody * Lacks capacity to consent * Unable to hear or speak on the telephone, even with the use of assistive devices

Interested in this study? View the official listing for contact and enrollment details.

View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT05846685). StuddyBuddy aggregates publicly available trial information.