Mobile App Health Data Collection for Peripheral Arterial Disease

(ROAMM-EHR Trial)

Overseen By HOBI department

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Florida

Disqualifiers: Dementia, Hearing loss, Vision impairment, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

50 Participants Needed

Trial Summary

What is the purpose of this trial?

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.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the study team or your doctor.

What data supports the effectiveness of this treatment for Peripheral Arterial Disease?

Research shows that using mobile health apps for supervised exercise therapy can be an effective way to manage Peripheral Arterial Disease (PAD). These apps help patients follow exercise programs more easily and allow healthcare providers to monitor progress, which can improve health outcomes. ^{1 2 3 4 5}

Is the mobile app for health data collection safe for humans?

The research does not provide specific safety data for the mobile app used in health data collection for peripheral arterial disease, but it suggests that using mobile health applications for delivering therapy is acceptable to patients and healthcare professionals. ^{1 4 6 7 8}

How does the mobile app treatment for peripheral arterial disease differ from other treatments?

This treatment is unique because it uses a mobile app to deliver supervised exercise therapy (SET) remotely, making it more accessible and convenient for patients compared to traditional in-person sessions. The app allows for monitoring by healthcare professionals and includes features like exercise videos and walking distance tracking, which are tailored to the needs of patients with peripheral arterial disease. ^{1 2 9 10 11}

Research Team

Todd Manini, PhD

Principal Investigator

University of Florida

Eligibility Criteria

This trial is for individuals aged 60 or older with chronic limb-threatening ischemia who are undergoing bypass surgery. It's not suitable for those at high risk of post-surgical amputation, non-English speakers, dementia patients, those with severe hearing loss or vision impairment that affects assessments and safety, or other serious diseases as judged by the study physician.

Inclusion Criteria

I am undergoing surgery to improve blood flow in my limbs due to severe blockage.

I am 60 years old or older.

Exclusion Criteria

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

I have been diagnosed with a dementia related to aging, like Alzheimer's.

Non-English speaker

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Pre-Surgery Monitoring

Participants wear a smartwatch equipped with the ROAMM app before their surgery to collect baseline data

1-2 weeks

Daily monitoring via smartwatch

Post-Surgery Monitoring

Participants continue to wear the smartwatch for approximately a month after surgery to report symptoms and activity levels

4 weeks

Daily monitoring via smartwatch

Follow-up

Participants are monitored for safety and effectiveness after treatment, including assessments of 6-min walk distance and quality of life

4 weeks

Treatment Details

Interventions

• Actionable remotely generated health data
• Non-Actionable remotely generated health data

Trial Overview The ROAMM-EHR Study tests if patient health data collected remotely can help manage symptoms after bypass surgery for critical limb ischemia. Participants will either receive actionable health data alerts integrated with their EHR system or non-actionable information to compare outcomes.

Participant Groups

Group I: ROAMM-EHR Experimental Treatment 1 Intervention

Patients will wear a smartwatch equipped with a smartwatch app before their surgery and for approximately a month after the surgery. Patients will be asked to wear the watch every day when awake. When wearing the smartwatch, patients will be asked questions about their symptoms following surgery and data will be sent to providers electronically and displayed in their EHR portal. Healthcare Providers will use this information along with patient medical history to decide on the next course of action. The study does not provide specific instructions about how to care for the patient. Those decisions are made by the provider team and their clinical judgement.

Group II: Active Comparison Active Control 1 Intervention

The active comparison patients will wear and respond to questions on the smartwatch. However, the information will not be viewable by their doctor and medical team. All standard of care procedures will remain.

Who Is Running the Clinical Trial?

University of Florida

Lead Sponsor

Trials

1,428

Recruited

987,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

Findings from Research

A study involving 62 patients and 44 healthcare professionals found that 84% of patients preferred their supervised exercise therapy (SET) to be monitored by their vascular team, indicating a strong desire for professional oversight in their treatment.

Patients showed significant interest in features like exercise videos (76%) and communication tools for interaction with their healthcare team, while healthcare professionals valued the documentation of physical activity and wearable technology, highlighting differing priorities between the two groups.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patient and Healthcare Professional Priorities for a Mobile Phone Application for Patients With Peripheral Arterial Disease. Sivagangan, P., Harwood, AE., Stather, PW.[2023]

In a pilot study involving 39 patients with peripheral arterial disease, the TrackPAD app significantly improved the 6-minute walking distance by an average of 83 meters over 3 months, while the control group experienced a decrease in walking distance.

The app also enhanced patients' quality of life related to their condition, particularly in symptom perception and physical functioning, indicating its potential as a supportive tool for managing chronic diseases.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Supervised Exercise Therapy Using Mobile Health Technology in Patients With Peripheral Arterial Disease: Pilot Randomized Controlled Trial. Paldán, K., Steinmetz, M., Simanovski, J., et al.[2021]

The integration of Patient-Reported Outcomes (PROs) into clinical practice for managing Peripheral Artery Disease (PAD) is essential for improving care quality, as it allows for individualized management and better assessment of treatment impact.

The proposed framework for using PRO measures as performance indicators (PRO-PMs) aims to reduce variability in care and promote health equity, highlighting the need for proper training and competencies to effectively handle and interpret PRO-PM data.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Advancing Peripheral Artery Disease Quality of Care and Outcomes Through Patient-Reported Health Status Assessment: A Scientific Statement From the American Heart Association. Smolderen, KG., Alabi, O., Collins, TC., et al.[2023]

A consensus was reached among 25 international vascular experts on a minimum core data set for evaluating outcomes of peripheral arterial revascularization, which includes 79 recommended items covering patient characteristics, comorbidities, procedures, and complications.

This standardized data set aims to enhance collaboration among global registries, improve data quality, and facilitate the development of real-world evidence in vascular surgery, addressing limitations of single-country studies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

International Consortium of Vascular Registries Consensus Recommendations for Peripheral Revascularisation Registry Data Collection. Behrendt, CA., Bertges, D., Eldrup, N., et al.[2021]

A new automated risk prediction tool for patients with peripheral arterial disease was developed using electronic health records, analyzing data from 1,676 patients over a 5-year follow-up period, which showed a strong ability to predict survival with a c-statistic of 0.76.

The tool stratifies patients into different risk categories, revealing significantly increased mortality risks for higher-risk groups, which can help healthcare providers make more informed decisions at the point of care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Leveraging the Electronic Health Record to Create an Automated Real-Time Prognostic Tool for Peripheral Arterial Disease. Arruda-Olson, AM., Afzal, N., Priya Mallipeddi, V., et al.[2023]

In a study of 796 patients with peripheral arterial disease (PAD), maintaining good glucose control was found to significantly reduce the risk of adverse limb events and death, with a hazard ratio of 0.74, indicating a protective effect.

African American patients were found to be at a higher risk (2.8 times) for adverse limb events compared to White or Hispanic patients, but this increased risk was mitigated when their glucose levels were well-controlled.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Process of care and outcomes in patients with peripheral arterial disease. Collins, TC., Beyth, RJ., Nelson, DB., et al.[2022]

A multidisciplinary group reviewed the limitations of existing studies on paclitaxel-coated devices, highlighting the need for improved study design and data quality to better assess safety and efficacy.

The group recommends actionable steps, such as creating standardized data points and reducing missing data, to enhance future research in peripheral arterial disease, ultimately aiming to improve patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Important considerations for trials for peripheral arterial disease: Lessons learned from the paclitaxel mortality signal: A report on behalf of the registry assessment for peripheral interventional Devices (RAPID) Paclitaxel Pathways Program. Lottes, AE., Whatley, EM., Royce, SM., et al.[2021]

A machine learning model developed from electronic health records (EHR) demonstrated high accuracy in identifying undiagnosed peripheral artery disease (PAD), achieving an average AUC of 0.96, significantly outperforming traditional models.

Physicians showed a strong acceptance of an automated PAD risk assessment tool integrated into EHR systems, with 75% expressing interest in its use, highlighting the potential for improved patient outcomes through better diagnosis and management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records. Ghanzouri, I., Amal, S., Ho, V., et al.[2023]

An automated algorithm developed to analyze accelerometer data effectively detected home-based exercise sessions in patients with peripheral artery disease (PAD), achieving a sensitivity of 85% and specificity of 90%.

The exercise sessions identified by the algorithm were correlated with improvements in peak walking time after 6 months of training, indicating that monitored home exercise can enhance performance in PAD patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Automated Detection of Exercise Sessions in Patients With Peripheral Artery Disease: EVIDENCE FOR AN EXERCISE DOSE RESPONSE TO TRAINING. Mays, RJ., Wesselman, CW., White, R., et al.[2022]

Out of 1,446 identified patients with peripheral arterial disease (PAD), only 64 participants (4.4%) were successfully enrolled in a feasibility study, highlighting significant challenges in recruiting this population.

The study identified that patients with PAD often face difficulties due to coexisting health issues and travel limitations, suggesting that future recruitment strategies need to be tailored to address these barriers for better participation rates.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Recruiting older patients with peripheral arterial disease: evaluating challenges and strategies. Brostow, DP., Hirsch, AT., Kurzer, MS.[2022]

The VascTrac iPhone app, designed to monitor walking distance in patients with peripheral artery disease (PAD), showed that the iPhone's built-in distance algorithm significantly overestimated walking distance by 43%, indicating a need for custom algorithms for accurate monitoring.

While the iPhone accurately counted steps, with a bias of -7.2%, further research is needed to determine if step counting can be a clinically meaningful measure for assessing walking ability in PAD patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical validation of smartphone-based activity tracking in peripheral artery disease patients. Ata, R., Gandhi, N., Rasmussen, H., et al.[2021]

References

1. United States pubmed.ncbi.nlm.nih.gov

Patient and Healthcare Professional Priorities for a Mobile Phone Application for Patients With Peripheral Arterial Disease. [2023]

2. Canada pubmed.ncbi.nlm.nih.gov

Supervised Exercise Therapy Using Mobile Health Technology in Patients With Peripheral Arterial Disease: Pilot Randomized Controlled Trial. [2021]

3. United States pubmed.ncbi.nlm.nih.gov

Advancing Peripheral Artery Disease Quality of Care and Outcomes Through Patient-Reported Health Status Assessment: A Scientific Statement From the American Heart Association. [2023]

4. England pubmed.ncbi.nlm.nih.gov

International Consortium of Vascular Registries Consensus Recommendations for Peripheral Revascularisation Registry Data Collection. [2021]

5. England pubmed.ncbi.nlm.nih.gov

Leveraging the Electronic Health Record to Create an Automated Real-Time Prognostic Tool for Peripheral Arterial Disease. [2023]

6. United States pubmed.ncbi.nlm.nih.gov

Process of care and outcomes in patients with peripheral arterial disease. [2022]

7. United States pubmed.ncbi.nlm.nih.gov

Important considerations for trials for peripheral arterial disease: Lessons learned from the paclitaxel mortality signal: A report on behalf of the registry assessment for peripheral interventional Devices (RAPID) Paclitaxel Pathways Program. [2021]

8. England pubmed.ncbi.nlm.nih.gov

Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records. [2023]

9. United States pubmed.ncbi.nlm.nih.gov

Automated Detection of Exercise Sessions in Patients With Peripheral Artery Disease: EVIDENCE FOR AN EXERCISE DOSE RESPONSE TO TRAINING. [2022]

10. New Zealand pubmed.ncbi.nlm.nih.gov

Recruiting older patients with peripheral arterial disease: evaluating challenges and strategies. [2022]

11. England pubmed.ncbi.nlm.nih.gov

Clinical validation of smartphone-based activity tracking in peripheral artery disease patients. [2021]