Recruiting

Digital Health

Sponsor:

Brigham and Women's Hospital

Code:

NCT05282654

Conditions

Multiple Chronic Conditions

Adverse Event

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Not accepted

Interventions

ePRO Application

Study Details

Brief summary:

This study aims to predict and minimize post-discharge adverse events (AEs) during care transitions through early identification and escalation of patient-reported symptoms to inpatient and ambulatory clinicians by way of predictive algorithms and clinically integrated digital health apps. We will (1) develop and prospectively validate a predictive model of post-discharge AEs for patients with multiple chronic conditions (MCC); (2) combine, adapt, extend, and iteratively refine our EHR-integrated digital health infrastructure in a series of design sessions with patient and clinician participants; (3) conduct a RCT to evaluate the impact of ePRO monitoring on post-discharge AEs for MCC patients discharged from the general medicine service across Brigham Health; and (4) use mixed methods to evaluate barriers and facilitators of implementation and use as we develop a plan for sustainability, scale, and dissemination.

Conditions

Multiple Chronic Conditions

Adverse Event

Study ID

NCT05282654

Start date

Feb 1, 2022

Status verified date

Mar, 2026

Completion date

Oct 15, 2026

Anticipated

Primary completion date

Sep 15, 2026

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Not accepted

Inclusion Criteria:

  • Adult (18 years or older)
  • Hospitalized on the general medicine services at Brigham and Women's Hospital or Brigham and Women's Faulkner Hospital for at least 24 hours
  • Have a discharge status of home, home with services, or facility
  • English-speaking patients or their English-speaking legally designated healthcare proxy or next of kin (i.e., a family caregiver)
  • Non-English-speaking patients who have an English-speaking legally designated healthcare proxy or next of kin (i.e., a family caregiver)
  • Two or more chronic conditions: Anxiety, Asthma\*, Arthritis (Osteoarthritis, Rheumatoid), Atrial Fibrillation, Cancer\*, Cerebral vascular accident, Chronic kidney disease\*, Chronic obstructive pulmonary disease (COPD)\*, Cirrhosis, Coronary artery disease/Ischemic heart disease, Dementia, Depression, Diabetes mellitus\*, End-stage renal disease\*, Heart failure\*, Hepatitis B, C\*, HIV/AIDs, Hyperlipidemia, Hypertension, Inflammatory bowel disease, Osteoporosis, Sickle cell disease, Substance abuse (Alcohol/Opioid)

Exclusion Criteria:

  • Less than 18 years of age
  • Less than two chronic conditions
  • Hospitalized less than 24 hours
  • No identifiable healthcare proxy or next of kin (i.e., a family caregiver)

Study Design

Enrollment

1300 participants

Anticipated

Allocation

Randomized

Intervention Model

Parallel Assignment

Primary purpose

Prevention

Interventions and Outcome Measures

Arms

no intervention: Usual Care (Arm 1)

During the 18-month Baseline Period (Arm 1, n=450) patients will be enrolled and receive usual care to develop the initial predictive model.

no intervention: Usual Care (Arm 2)

During the 30-month Main Trial (RCT) Period, patients will be randomized to usual care (Arm 2, n=425). Data collection for post-discharge AE determination will occur during both periods.

experimental: Intervention (Arm 3)

During the 30-month Main Trial (RCT) Period, patients will be randomized to the intervention (Arm 3, n=425). Data collection for post-discharge AE determination will occur during both periods.

Interventions

ePRO Application

The intervention consists of a patient portal, EHR-integrated web-app to communicate risk of post-discharge adverse events using patient-reported outcome questionnaires, discharge preparation checklist during hospitalization. After discharge, the intervention will provide real-time symptom monitoring using ePROs and facilitate communication with clinicians based on prediction model-informed ePRO score trends exceeding escalation thresholds.

Primary outcome measure

  • Actual adverse events (AEs) [ Time Frame: Up to 30-days after discharge from index hospitalization ]
  • Actual preventable adverse events (AEs) [ Time Frame: Up to 30-days after discharge from index hospitalization ]

Central Contacts and Locations

Central contacts

Anuj Dalal, MD

(617) 525-8891adalal1@bwh.harvard.edu

Savanna Plombon, MPH

857-307-2668splombon@bwh.harvard.edu

Locations

Brigham and Women's Faulkner Hospital

Recruiting

Boston, Massachusetts, United States, 02115

Brigham and Women's Hospital

Recruiting

Boston, Massachusetts, United States, 02115

Principal Investigator:

Anuj K Dalal, MD

More Information

Sponsor

Brigham and Women's Hospital

Last update posted

Apr 20, 2026

Last verified

Mar, 2026

Keywords

  • Digital Health
  • Patient Reported Outcomes
  • Symptom Monitoring
  • Predictive Model
  • Care Transitions
  • Post Acute Care

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by Brigham and Women's Hospital on 2026-04-20.