PERsonal ContExtual Precision healTh

NCT03349918 | Completed

• 1 other identifier: PERCEPT
• Study Type: interventional
• Target: 164
• Locations: 1 country
• Sites: 1

Brief Summary

The exponential growth of physiological, behavioral and environmental data generated through consumer mobile health (mHealth) devices and Internet of Things (IoT) technology provide unprecedented sources of personalized and contextual health information. If linked to clinical health data from the Electronic Health Record (EHR), these data can provide dynamic and individualized views of patient health states and trajectories that can greatly inform clinical care and health-related research. The investigators propose to advance precision health through the development and evaluation of a mobile application and data platform that collects, harmonizes and integrates mHealth and environmental data from patients' daily lives with their clinical histories and electronic health record data. The investigators propose a participatory design approach to implement and evaluate a precision health platform through the study and modeling of hypertension (HTN) and depression in patient communities of UC Davis (UCD) and UC San Francisco (UCSF). These chronic diseases have high prevalence across geography, socioeconomic status, and race/ethnicity, and have significant economic, societal and personal costs. They are considerably challenging to manage due to difficulties in acquiring high-quality and consistent data from patients outside of their clinical care appointments that is so needed for a full view of the patient's disease state. Despite a broad array of self-monitoring devices and consumer applications, mHealth data are not getting into the clinical care process, and patients do not regularly monitor their own health states, particularly during periods of medication change, when frequent assessments are especially important. The investigators propose to conduct a 6-month single arm feasibility study of 200 ambulatory men and women (100 each at UCSF and UCD) with either hypertension or depression to implement an open, web-accessible, standards driven and patient-centric data platform for the integration of patient-reported and clinical data.

Conditions

Hypertension; Depression

Outcome Measures

Primary Outcomes (1)

• Capture medication transition data from electronic health record

  Number of medication changes captured in our system vs. the number reported by participants at the end of the study

  24 weeks

Secondary Outcomes (1)

• Monitoring health condition

  3 months and 6 month

Study Arms (1)

Mobile Health Monitoring

EXPERIMENTAL

Participants will monitor their blood pressure using a wireless-enabled blood pressure cuff or mood using a mobile health application once per week at baseline. The investigators will monitor their medical records to determine if a medication change has occurred. After this, the investigators will increase the frequency of notifications to monitor the participant's specific health condition to once daily for 1 month. This monitoring will continue for a study duration of 6 months.

Behavioral: Mobile Health Monitoring

Interventions

Mobile Health Monitoring BEHAVIORAL

Use of mobile health application to monitor blood pressure and mood.

Mobile Health Monitoring

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Primary care patient at UCD or UCSF
• Able to speak and read English
• Male or female 18-80 years of age at Telephone screening
• Documentation of a diagnosis of hypertension (defined as SBP \>= 140 mmHg or DBP \>= 90 mmHg on anti-hypertensive medication including beta-blockers, ACE-I, ARB, alpha-blockers, calcium-channel blockers) OR depression (PHQ-8 \> 5) on an antidepressant medication
• Written informed consent (and assent when applicable) obtained from subject or subject's legal representative and ability for subject to comply with the requirements of the study
• Have an Android or Apple iOS smartphone
• Willing to install the PERCEPT, iHealth (for hypertension cohort) and Moves mobile applications
• Willing to self-report blood pressure (for those with hypertension and with provided iHealth and/or standard blood pressure cuff) or mood data (for those with depression) at specified frequency
• Willing to be have your location and activity tracked
• Have downloaded a mobile application from the appropriate mobile app store (App store for iPhones or Google Play for Android) within the past 1 year
• Have home Wifi access.

You may not qualify if:

• High blood pressure or depression being managed by a physician outside of UCD or UCSF
• Current participation in any other mobile app-based clinical study
• A diagnosis of both hypertension and depression
• A diagnosis of depression with psychosis (ICD-9: 296.24, 296.34) bipolar disorder (ICD-9: 296.0, 296.1, 296.4, 296.5, 296.6, 296.7, 296.8, 296.9) schizophrenia (ICD-9: 295.x), schizoaffective disorder (ICD-9 295.70)
• Planning to relocate from area within the study duration
• Impaired vision that could limit the use of the mobile apps (participant-reported)
• Primary care patient of the Investigator, Dr. Meghana Gadgil

Sponsors & Collaborators

• University of California, San Francisco: lead
• University of California, Davis: collaborator
• California Initiative to Advance Precision Medicine: collaborator

Study Sites (1)

University of California, San Francisco

San Francisco, California, 94143, United States

Location

MeSH Terms

Conditions

Hypertension; Depression

Condition Hierarchy (Ancestors)

Vascular Diseases; Cardiovascular Diseases; Behavioral Symptoms; Behavior

Study Officials

• Meghana D Gadgil, MD

  University of California, San Francisco

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 17, 2017
• First Posted: November 22, 2017
• Study Start: November 6, 2017
• Primary Completion: December 31, 2018
• Study Completion: December 31, 2018
• Last Updated: March 5, 2019

Record last verified: 2019-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)