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OpenTrials
Completed

NCT Number: NCT05744180

A Study 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.

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Key information

Conditions

Nursing

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Mayo Clinic Minnesota

Rochester, Minnesota, 55905, United States

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Interventional

Other

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

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

    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).

Secondary outcomes

  1. 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).

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

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

Important dates

Study start
2023
Primary completion
2024
Study completion
2024
First posted
Feb 24, 2023
Registry last updated
Oct 9, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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