Machine Learning to Reduce Hypertension Treatment Clinical Inertia

NANot yet recruitingINTERVENTIONAL
Enrollment

50

Participants

Timeline

Start Date

April 25, 2025

Primary Completion Date

May 31, 2025

Study Completion Date

July 31, 2025

Conditions
Hypertension
Interventions
OTHER

Predicted uncontrolled BP status (yes/no) at follow up visit, derived using a machine learning algorithm

The investigators have created a machine learning algorithm to predict uncontrolled blood pressure (BP) status (yes/no) at a follow up visit among adults with uncontrolled BP at their current visit. The investigators will determine whether adding this information to a vignette describing a patient will increase the likelihood that a clinician will intensify antihypertensive medication treatment.

All Listed Sponsors
lead

Temple University

OTHER

NCT05406336 - Machine Learning to Reduce Hypertension Treatment Clinical Inertia | Biotech Hunter | Biotech Hunter