AI steps in to keep HIV patients out of the ER

NCT ID NCT07279376

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study tests a computer program that predicts which HIV patients are most likely to need emergency care in the next two weeks. Care managers use this list to reach out and offer support, compared to usual care where they rely on schedules and judgment. The goal is to see if this smart alert system can reduce ER visits and hospital stays while improving viral suppression and immune health. About 2,600 HIV patients are taking part.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
predictive emergency room alerts (pERA) - a machine-learning algorithm
What this could lead to
If successful, this could help care managers better support HIV patients, reducing emergency room visits and improving overall health outcomes.
What could go wrong
This is an early-stage implementation study, not a treatment trial. The algorithm may not work as expected in real-world settings, and results may not apply to all HIV care programs.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • Community Care Management Partners Health Home

    New York, New York, 10016, United States

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