Harnessing Data Science to Improve HIV Care Continuum Outcomes: A Hybrid Type 2 Trial Evaluating a Machine-Learning Algorithm-Based Implementation Strategy

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.

Description

Eligibility

Age range

18+ years

Sex

All

Healthy volunteers

No

Interventions

• Other
  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.

• Other
  Standard of care

  Care managers interact with patients according to their standard of care protocols

Location