A Study of Workflow-Integrated Artificial Intelligence for RPM Enrollment
Pragmatic Analysis of the Impact and Utilization of Workflow-Integrated Artificial Intelligence for RPM Enrollment
1 other identifier
interventional
10
1 country
1
Brief Summary
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Jun 2023
Shorter than P25 for not_applicable
1 active site
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
February 2, 2023
CompletedFirst Posted
Study publicly available on registry
February 24, 2023
CompletedStudy Start
First participant enrolled
June 19, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
January 16, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
January 16, 2024
CompletedOctober 9, 2024
October 1, 2024
7 months
February 2, 2023
October 7, 2024
Conditions
Outcome Measures
Primary Outcomes (1)
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
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 Outcomes (1)
Assessment of "fit" score overall effect on nursing efficiency and clinical workflows
1 year
Study Arms (1)
Arm Not Applicable
OTHERInterventions
The FitScore is a machine learning algorithm embedded within the electronic health record that identifies patients most likely to benefit from remote patient monitoring.
Eligibility Criteria
You may qualify if:
- 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).
You may not qualify if:
- \- \< 18 years old.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Mayo Cliniclead
Study Sites (1)
Mayo Clinic Minnesota
Rochester, Minnesota, 55905, United States
Related Links
MeSH Terms
Interventions
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Tufia Haddad, MD
Mayo Clinic
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal Investigator
Study Record Dates
First Submitted
February 2, 2023
First Posted
February 24, 2023
Study Start
June 19, 2023
Primary Completion
January 16, 2024
Study Completion
January 16, 2024
Last Updated
October 9, 2024
Record last verified: 2024-10
Data Sharing
- IPD Sharing
- Will not share