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Evaluating an Algorithm-Based Implementation Strategy to Improve HIV Care Outcomes
Sponsor: Hunter College of City University of New York
Summary
This study tests a strategy for helping Care Management Agencies prioritize patients with HIV (PWH) for outreach and support. Under the new strategy, care managers are given a list of highest-priority patients who have been identified by a computer algorithm as being at high risk of going to the emergency room in the next two weeks. This strategy is compared to traditional (standard of care) care management, in which care managers reach out to patients based on a set schedule and their clinical judgement (but not based on a computerized report). We are looking at whether the use of the computer report helps care managers reach the right patients at the right time, preventing them from having to go to the emergency room.
Official title: Harnessing Data Science to Improve HIV Care Continuum Outcomes: A Hybrid Type 2 Trial Evaluating a Machine-Learning Algorithm-Based Implementation Strategy
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
2600
Start Date
2025-11-18
Completion Date
2029-08
Last Updated
2026-01-27
Healthy Volunteers
No
Conditions
Interventions
predictive emergency room alerts (pERA)
pERA is a machine-learning algorithm-driven implementation strategy that identifies patients at higher risk of emergency room visits and alerts the care manager to follow-up with them.
Standard of care
Care managers interact with patients according to their standard of care protocols
Locations (1)
Community Care Management Partners Health Home
New York, New York, United States