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Clinical Trial Summary

In recent years, mobile health (mHealth) apps have promised improved monitoring of health conditions to improve clinical outcomes. The objective of this study is to conduct a pilot randomized clinical trial (RCT) to evaluate the impact of using remotely collected patient generated health data (PGHD) from older patients undergoing bypass surgery due to chronic limb threatening ischemia. The hypothesis is that integrating PGHD with an EHR system will help providers manage post-surgical symptoms and thus improve post-operative mobility and quality of life health outcomes.


Clinical Trial Description

This pilot study aims to evaluate the feasibility of collecting patient generated health data (PGHD) remotely for aiding care management of patients with chronic limb threatening ischemia following vascular bypass or revascularization. DRemote data collected from a publicly available smartwatch will be displayed on an EHR interface for providers to view PGHD. The test of feasibility entails multiple components that include implementing a provider interface for viewing and acting on PGHD, establishing safety, ensuring quality assurance (e.g. quality of remote data collection), successful recruitment and retention of participants, and sufficient remote response rates from patients. This is a single-masked RCT pilot study design. The work leverages our existing mobile health platform called Real-Time and Online Assessment and Mobility Monitor (ROAMM) to integrate ecological PGHD with the UF Epic® EHR system. We will randomize 50 older adults (>=60 yrs) to either ROAMM-EHR or an active comparison group. Importantly, both groups will receive smartwatches with the ROAMM app. This removes the potential influence that interacting with a smartwatch and reporting symptoms may have patient behaviors and post-surgical outcomes. However, only data from the ROAMM-EHR group will be seen by physician teams; data from the active comparison group will be stored but not displayed. All participants will be prompted multiple times per day to report their symptoms (see table 2 for description), wound healing and any complications. Smartwatch sensors will capture information about activity levels and community mobility via the location services (GPS). Provider teams will be trained to use the EPIC interface that displays data from the ROAMM app under the Technology Acceptance Model. They will be asked to do regular checks to monitor patient's symptoms, complications and activity patterns. Participants: We will enroll 50 older adult patients (age >=60 years) scheduled for vascular bypass or revascularization. Patients will be randomized (stratified by gender) across comparison groups. Eligibility criteria are as follows. Inclusion criteria: age >= 60; Patients with chronic limb threatening ischemia who are undergoing re-vascular surgery [endovascular or open re-vascularization (bypass)]. Exclusion criteria: High risk of post-surgical amputation based on study physician judgement, non-english speaker, diagnosis of an age-related dementia (e.g. Alzheimer's Disease); unable to communicate because of severe hearing loss; uncorrectable vision impairment that compromises clinical assessments or would cause a safety concern, other significant co-morbid disease that in the opinion of the investigators and study physician would impair the ability to participate in the study or be a safety concern; We will evaluate whether ROAMM-EHR information impacts traditional clinically relevant measures of lower extremity function and overall quality of life. We will measure the change in 6-min walk distance at post-surgery (window: 30-50 days) versus pre-surgery. For the self-reported quality of life, we chose the Medical Outcomes Study 36-Item Short Form (SF-36) and modified Brief Pain Inventory. We propose a total sample size of 50 participants - 2 randomized groups of 25. In pilot studies, the goal is to have a sample size for estimating the margin of error that is sufficiently small for planning future trials. With a conservative 10% loss to follow-up, the margin of error in a 90% confidence interval will not exceed 12% of the point estimate in the SF-36 physical composite score (1.88 points) or 6-min walk distance (22.9 meters). Thus, all confidence interval widths are sufficiently small to plan future studies. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06263322
Study type Interventional
Source University of Florida
Contact Institute_on_Aging
Phone 352-273-5919
Email recruit@aging.ufl.edu
Status Recruiting
Phase N/A
Start date November 16, 2023
Completion date October 17, 2026

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