The Role of Wearable Devices in Predicting and Detecting Complications and Adverse Events

Purpose

The overarching goal of this research is to use machine learning analysis of high-resolution data-collected by wearable technology-to predict complications and poor recovery in patients undergoing treatment for benign or malignant conditions.

Conditions

  • Recovery
  • Treatment Complication

Eligibility

Eligible Ages
Over 18 Years
Eligible Sex
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  1. Age 18 years or older 2. Individuals scheduled to undergo one of the following surgical or non-surgical treatments: cardiothoracic surgery, orthopedic surgery, vascular surgery, colorectal surgery, pancreatic surgery, other major abdominal surgeries, treatment for chronic disease, or systemic therapy (i.e., chemotherapy, immunotherapy, or targeted therapy), radiotherapy, or ablation. 3. Amenable to using one of the wearable devices of interest (Fitbit, iWatch, Biostrap). 4. Individuals willing to provide informed consent and who have capacity for all study procedures

Exclusion Criteria

  1. Individuals with mental incapacity and/or cognitive impairment that would preclude adequate understanding of, or cooperation with the study protocol. 2. Any pregnant participant.

Study Design

Phase
Study Type
Observational
Observational Model
Cohort
Time Perspective
Prospective

Arm Groups

ArmDescriptionAssigned Intervention
Treatment Group Adults patients who are scheduled to undergo treatment for a benign or malignant condition and meet the inclusion and exclusion criteria.
  • Device: Device: Wearable Device
    A Wearable Device will be placed on the wrist of the patient ~30 days prior to the patient's scheduled treatment and for up to 5 years following treatment. The device will record activity in terms of steps, sleep quality, heart rate, etc.

Recruiting Locations

Massachusetts General Hospital
Boston, Massachusetts 02114
Contact:
Chi-Fu J Yang, M.D.
814-574-8695
cjyang@mgh.harvard.edu

More Details

Status
Recruiting
Sponsor
Massachusetts General Hospital

Study Contact

Chi-Fu Jeffrey Yang, MD
617-726-5200
cjyang@mgh.harvard.edu

Detailed Description

This is a multi-center non-randomized prospective cohort study using wearable devices and machine learning to predict complications and poor recovery in patients undergoing treatment for benign or malignant conditions. Patients who meet the inclusion and exclusion criteria will be enrolled consecutively with verbal informed consent from the time this protocol is approved by the IRB until 2,400 subjects are enrolled. At ~30 days before treatment the subjects will have a wearable device (such as a Fitbit) placed on their wrist and will wear the device for up to 5 years following treatment. This device will wirelessly transmit data regarding activity and sleep quality to a smartphone application for the duration of wear and data will be analyzed by our collaborators at Case Western Reserve University.