Clinical trial NCT05128006: Direct-to-patient Teledermatology and Computer-assisted Diagnosis
Official title: Improving Dermatology Access by Direct-to-Patient Teledermatology and Computer-Assisted Diagnosis
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: New Patient Use of Teledermatology Mobile App
Keywords: teledermatology
ehealth
mobile health
telemedicine
artificial intelligence
telehealth
access
Lead sponsor: VA Office of Research and Development
Sponsor class: FED
Collaborators: name: VA Boston Healthcare System
name: Durham VA Health Care System
name: Providence VA Medical Center
First posted: 2021-11-19
Enrollment: 63200
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: All patients referred as new patients to dermatology at sites in study.

Brief summary: This study will examine access to dermatology care. The operational partner will implement a direct-to-new patient teledermatology clinical care pathway while the research will study the effects of that implementation, use data associated with deployment to develop and test an Artificial Intelligence system, and understand key stakeholders' attitudes regarding and readiness for remote dermatology care.

Detailed description: VA is uniquely positioned to develop and study direct-to-patient teledermatology in parallel with computer vision for skin disease. The following aims will assess the performance of these emerging patient-facing dermatology innovations and assess their ability to improve access to quality skin care VA-wide.

1. Assess the impact of direct-to-patient teledermatology on access and health system utilization. In collaboration with the VA operational partner, Office of Connected Care, the My VA Images app will be deployed to three VA facilities where the app will be introduced as an option to refer eligible new patients for dermatology consultation. Multiple access metrics, including time to consult completion and geographic distance traveled. will be measured in exposed patients and compared with patients referred to usual in-person and consultative teledermatology pathways. Facility-centric measures of access such as clinic appointment wait times and in-person dermatology clinic and community care utilization will also be measured. To better understand end-user experiences, the investigators will survey patients and staff at each study site to evaluate their satisfaction with My VA Images as well as the overall process.
2. Assess, refine and augment computer-assisted evaluation of patient-submitted images. An artificial intelligence-powered computer vision model, trained and validated on clinic-captured images of melanoma and nevi, will be tested and refined on patient-submitted teledermatology images from the My VA images app. The investigators will also extend the computer vision model by using all patient submissions to train and validate the model on a wider variety of skin diagnoses. Patient-submitted teledermatology images at study sites will be prospectively evaluated by the investigators' own computer vision model as well as by a commercial system currently available to VA clinicians and patients, and results will be compared with benchmark diagnoses to measure concordance across a range of diagnostic categories.
3. Assess readiness of VA and Veterans' acceptance to implement direct-to-patient care. The investigators will survey Veterans and key VA leadership and staff at three selected VA facilities, supplemented by interviews of key VA stakeholders, to understand patients' and organizational readiness, including facilitators and barriers, for transitioning to patient-facing technologies in general, and direct-to-patient dermatologic care in particular. National Veteran surveys, and VA Mobile Health user satisfaction data will help place local observations in perspective. Implementation and sustainability of the patient-facing teledermatology app technology will also be measured.

Eligibility criteria: Inclusion Criteria:

* New patient referrals to dermatology at San Francisco, Decatur, and Aurora from 2021-2025

Exclusion Criteria:

* Patients who are not dermatology patients
* Dermatology patients who are not seen at San Francisco, Decatur, and Aurora
* Dermatology patients at San Francisco, Decatur, and Aurora who have visits only before 2021 or after 2025

Primary outcomes:
measure: New patient in-person dermatology visits
timeFrame: 4 years
measure: Consult completion time
timeFrame: 4 years
measure: Appointment completion time
timeFrame: 4 years
measure: Travel distance for VA care
timeFrame: 4 years
measure: Third next available dermatology clinic appt completion time
timeFrame: 4 years
measure: New Patient Teledermatology encounters
timeFrame: 4 years
measure: Organizational Readiness to implement mobile teledermatology for direct new patient care
timeFrame: 4 years
measure: Readiness of Veterans to use mobile teledermatology for direct new patient care
timeFrame: 4 years
measure: Patient Satisfaction of different types of dermatologic care
timeFrame: 4 years
measure: Readiness of Veterans to use Artificial Intelligence for dermatologic care
timeFrame: 4 years
Secondary outcomes:
measure: Scheduled compared to clinically indicated appointment date
timeFrame: 4 years
measure: Whether patient had a no-show event for an intended encounter
timeFrame: 4 years
Other outcomes:
Locations:
city: San Francisco
country: United States
facility: San Francisco VA Medical Center, San Francisco, CA
state: California
city: Aurora
country: United States
facility: Rocky Mountain Regional VA Medical Center, Aurora, CO
state: Colorado
city: Decatur
country: United States
facility: Atlanta VA Medical and Rehab Center, Decatur, GA
state: Georgia
Study officials:
affiliation: San Francisco VA Medical Center, San Francisco, CA
name: Dennis H. Oh, MD PhD
role: PRINCIPAL_INVESTIGATOR
References: