NCT05406336

Brief Summary

Among individuals with an uncontrolled BP at the current visit, the objective of this study is to compare clinical management of hypertension with and without information from a machine learning algorithm on whether a patient will have uncontrolled blood pressure at their next follow up visit through a case-vignette study.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
50

participants targeted

Target at P25-P50 for not_applicable hypertension

Timeline
Completed

Started Apr 2025

Shorter than P25 for not_applicable hypertension

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

May 25, 2022

Completed
12 days until next milestone

First Posted

Study publicly available on registry

June 6, 2022

Completed
2.9 years until next milestone

Study Start

First participant enrolled

April 25, 2025

Completed
1 month until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 31, 2025

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

July 31, 2025

Completed
Last Updated

April 10, 2025

Status Verified

April 1, 2025

Enrollment Period

1 month

First QC Date

May 25, 2022

Last Update Submit

April 7, 2025

Conditions

Hypertension

Keywords

Uncontrolled blood pressureAntihypertensive medicationHypertension treatmentClinical inertiaMachine learning

Outcome Measures

Primary Outcomes (3)

  • Vignette #1 - antihypertensive medication treatment intensification

    A clinical vignette of a patient with uncontrolled blood pressure will be presented to clinicians. They will then be asked to assess wether they would intensify antihypertensive medication treatment. This will be assessed using a 5-point Likert scale with scores ranging from 1 ("Strongly disagree") to 5 ("Strongly agree"). Likert scale scores will be compared between clinicians in the control and intervention group.

    Immediately after clinical vignette

  • Vignette #2 - antihypertensive medication treatment intensification

    A second clinical vignette of a patient with uncontrolled blood pressure will be presented to clinicians. They will then be asked to assess wether they would intensify antihypertensive medication treatment. This will be assessed using a 5-point Likert scale with scores ranging from 1 ("Strongly disagree") to 5 ("Strongly agree"). Likert scale scores will be compared between clinicians in the control and intervention group.

    Immediately after clinical vignette

  • Vignette #3 - antihypertensive medication treatment intensification

    A third clinical vignette of a patient with uncontrolled blood pressure will be presented to clinicians. They will then be asked to assess wether they would intensify antihypertensive medication treatment. This will be assessed using a 5-point Likert scale with scores ranging from 1 ("Strongly disagree") to 5 ("Strongly agree"). Likert scale scores will be compared between clinicians in the control and intervention group.

    Immediately after clinical vignette

Study Arms (2)

No Information from Machine Learning Algorithm

NO INTERVENTION

The investigators will create case vignettes to assess clinician hypertension management behavior, specifically antihypertensive medication intensification among individuals with uncontrolled blood pressure (BP). This arm will not include information from a machine learning algorithm designed to predict uncontrolled BP at a follow up visit.

Information from Machine Learning Algorithm

EXPERIMENTAL

The investigators will create case vignettes to assess clinician hypertension management behavior, specifically antihypertensive medication intensification among individuals with uncontrolled blood pressure (BP). This arm will include information from a machine learning algorithm designed to predict uncontrolled BP at a follow up visit about whether the algorithm predicts that the patient will have uncontrolled BP at the next visit.

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

Interventions

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

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.

Information from Machine Learning Algorithm

Eligibility Criteria

Age20 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Hypertension

Condition Hierarchy (Ancestors)

Vascular DiseasesCardiovascular Diseases

Study Officials

  • Gabriel Tajeu, DrPH

    University of Alabama at Birmingham

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Gabriel Tajeu, DrPH

CONTACT

2055312258gtajeu@uab.edu

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
DOUBLE
Who Masked
PARTICIPANT, INVESTIGATOR
Purpose
TREATMENT
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 25, 2022

First Posted

June 6, 2022

Study Start

April 25, 2025

Primary Completion

May 31, 2025

Study Completion

July 31, 2025

Last Updated

April 10, 2025

Record last verified: 2025-04

Data Sharing

IPD Sharing
Will not share