Implementing Digital Health in a Learning Health System (ASE-INNOVATE)

Scripps Health

Status: Completed

Conditions: Hypertension; Atrial Fibrillation; Genetic Disease; Cardiovascular Diseases; Heart Failure; Metabolic Syndrome

Treatments: Diagnostic Test: Digital Health Device Diagnostics

Study type: Interventional

Funder types: Other

Identifiers

NCT03713333

Pro00029622

Details and patient eligibility

About

The need for new models of integrated care that can improve the efficiency of healthcare and reduce the costs are key priorities for health systems across the United States. Treatment costs for patients with at least one chronic medical or cardiovascular condition make up over 4-trillion dollars in spending on healthcare, with estimations of a population prevalence of 100-million affected individuals within the next decade. Therefore, the management of chronic conditions requires innovative and new implementation methods that improve outcomes, reduce costs, and increase healthcare efficiencies. Digital health, the use of mobile computing and communication technologies as an integral new models of care is seen as one potential solution. Despite the potential applications, there is limited data to support that new technologies improve healthcare outcomes. To do so requires; 1) robust methods to determine the impact of new technologies on healthcare outcomes and costs; and 2) evaluative mechanisms for how new devices are integrated into patient care. In this regard, the proposed clinical trial aims to advance the investigator's knowledge and to demonstrate the pragmatic utilization of new technologies within a learning healthcare system providing services to high-risk patient populations.

Full description

Objective #1: Determine the effectiveness of handheld imaging and digital health devices on long term health and patient-reported outcomes through pragmatic and randomized clinical trial designs.

Objective #2: Assess the impact of digital health devices and remote patient monitoring (RPM) on measures of healthcare efficiency. Measures of healthcare efficiency directly related to digital health technologies and RPM include: identify which interventions can improve care; define the variations in care and; demonstrate within which patient populations digital health technologies are most effective.

Objective #3: Apply integration methods for handheld imaging and digital health devices used for clinical decisions.

Achieving integration and interoperability-the ability of different information technology systems and software applications to communicate and exchange data with each other-requires identification for precisely how new innovations merge into systems of care and are applied to various practice settings.

Enrollment: 374 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• All participants of the ASE 2018 Outreach Event who are at least 18 years old who are referred for a cardiac evaluation

Exclusion criteria

• Those not willing to consent

Trial design

Primary purpose: Screening

Allocation: Randomized

Interventional model: Sequential Assignment

Masking: Triple Blind

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374 participants in 2 patient groups

Technology-Enabled Visitations

Experimental group

Description:

Technology-enabled visitations with digital health will include the following devices used at the time of a patient-physician encounter. These findings will be available to the treating physician at the time the visitation and to be used for clinical decisions.

Treatment:

Diagnostic Test: Digital Health Device Diagnostics

Standard-Care Visitations

No Intervention group

Description:

Standard-care is defined as the range of services available during usual patient care. Handheld Imaging and digital health screening will be performed in the control group after the patient-physician encounter. As such, patients and physicians will be blinded to the diagnostic findings unless an abnormal finding is detected that requires physician review and triage for further care.