A Study of Workflow-Integrated Artificial Intelligence for RPM Enrollment

October 7, 2024 updated by: Tufia C. Haddad, Mayo Clinic

Pragmatic Analysis of the Impact and Utilization of Workflow-Integrated Artificial Intelligence for RPM Enrollment

The objective of this study is to evaluate effectiveness, usability and clinical utility of the remote patient monitoring (RPM) "fit" score when choosing patients to enter the RPM Program.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Actual)

10

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • Minnesota
      • Rochester, Minnesota, United States, 55905
        • Mayo Clinic Minnesota

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • The study participants will be nurses who are part of the RPM care team that cares for adult patients ≥18 years.
  • A patient's data will be included in the analysis if the patient is ≥18 years old and receives care from a participating nurse.
  • Patient data will only be collected if permitted (based on the use of the Minnesota Research Authorization Retrieval Tool).
  • Patients who will be considered for this study will be assessed based on standard RPM program inclusion and exclusion criteria for the any of the chronic disease RPM programs (congestive heart failure, coronary artery disease, hypertension, type 2 diabetes, COPD, and general complex care).

Exclusion Criteria:

- < 18 years old.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: Arm Not Applicable
Other: Interventional
The FitScore is a machine learning algorithm embedded within the electronic health record that identifies patients most likely to benefit from remote patient monitoring.
Other Names:
  • FitScore

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Evaluation of the effectiveness, usability, and clinical utility of the RPM "fit" score as displayed in the Acute Multipatient Viewer (AMP) and underlying AI models in the real-world setting
Time Frame: 1 year
FitScore effectiveness will determined by the patient care utilization outcomes of those who did or did not participate in RPM (for those enrolled with or without the FitScore). Usability and clinical utility will be self-reported by nursing staff collected through surveys or as directly observed by study staff (as to experience with or without the FitScore).
1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Assessment of "fit" score overall effect on nursing efficiency and clinical workflows
Time Frame: 1 year
Efficiency will be measured by timing studies of nurse patient screening for RPM eligibility as directly observed by study staff. The effect on clinical workflows will be self-reported by nursing staff collected through surveys (as to experience with or without the FitScore).
1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Mayo Clinic

Investigators

  • Principal Investigator: Tufia Haddad, MD, Mayo Clinic

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 19, 2023

Primary Completion (Actual)

January 16, 2024

Study Completion (Actual)

January 16, 2024

Study Registration Dates

First Submitted

February 2, 2023

First Submitted That Met QC Criteria

February 15, 2023

First Posted (Actual)

February 24, 2023

Study Record Updates

Last Update Posted (Estimated)

October 9, 2024

Last Update Submitted That Met QC Criteria

October 7, 2024

Last Verified

October 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • 22-008014

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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