Real-time Symptom Monitoring Using ePROs to Prevent Adverse Events During Care Transitions

Adverse Event Clinical Trial

Official title:

Real-time Symptom Monitoring Using ePROs to Prevent Adverse Events During Care Transitions

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05282654
• Other study ID #: 2021P002593
• Status: Recruiting
• Phase: N/A
• Start date: February 1, 2022
• Est. completion date: October 15, 2026

Study information

• Verified date: December 2023
• Source: Brigham and Women's Hospital
• Contact: Anuj Dalal, MD
• Phone: (617) 525-8891
• Email: adalal1[@]bwh.harvard.edu
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Description:

Adverse events (AE) during care transitions range from 19-28% and may lead to readmissions, representing an ongoing threat to patient safety. Early identification and escalation of patient-reported symptoms to inpatient and ambulatory clinicians is critical, especially for patients with multiple chronic conditions (MCC). Clinically integrated digital health apps have the potential to more accurately predict post-discharge AEs and improve communication for patients, their caregivers, and the care team. Such tools can provide individualized risk assessments of AEs by systematically collecting relevant patient-reported outcomes (PROs) and leveraging standardized application programming interfaces (API) to combine them with electronic health record (EHR) data. While patient-reported outcomes (PROs) are increasingly used in ambulatory settings, their use for real-time symptom monitoring and escalation during transitions from the hospital is novel and potentially transformative-by both empowering patients to better understand their individualized risks of post-discharge AEs, and improving monitoring while transitioning out of the hospital. Our proposed intervention is grounded in evidence-based frameworks for care transitions, and scaling and spread of digital health tools. To inform our intervention, we propose developing and validating a predictive model of post-discharge AEs for 450 MCC patients using relevant PRO questionnaires and electronic health record (EHR) derived variables during our baseline pre-implementation period. Simultaneously, we will combine, adapt, extend, and refine our previously developed EHR-integrated hospital and ambulatory-focused digital health infrastructure to support MCC patients in real-time symptom monitoring using PROs when transitioning out of the hospital. Our intervention uses interoperable, data exchange standards and APIs to seamlessly integrate with existing vendor patient portal offerings, thereby addressing critical gaps and supporting the complete continuum of care. Our multidisciplinary team uses principles of user-centered design and agile software development to rapidly identify, design, develop, refine, and implement requirements from patients and clinicians. Our team will rigorously evaluate this intervention in a large-scale randomized controlled trial of 850 in which we compare our real-time symptom monitoring intervention (425) to usual care (425) for patients with MCCs transitioning out of the hospital. Finally, we will conduct a robust mixed methods evaluation to generate new knowledge and best practices for disseminating, implementing, and using this interoperable intervention at similar institutions with different EHR vendors

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1300
• Est. completion date: October 15, 2026
• Est. primary completion date: September 15, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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)

Related Conditions & MeSH terms

• Adverse Event
• Chronic Disease
• Multiple Chronic Conditions

Intervention

Behavioral:
• 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.

Locations

Country	Name	City	State
United States	Brigham and Women's Faulkner Hospital	Boston	Massachusetts
United States	Brigham and Women's Hospital	Boston	Massachusetts

Sponsors (2)

Lead Sponsor	Collaborator
Brigham and Women's Hospital	RAND

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Time to actual AE	The number of days until first AE detected	Up to 30-days after discharge from index hospitalization
Other	Time to potential AE	The number of days until first potential AE detected	Up to 30-days after discharge from index hospitalization
Primary	Actual adverse events (AEs)	The number of actual AEs during the 30-day post-discharge period	Up to 30-days after discharge from index hospitalization
Primary	Actual preventable adverse events (AEs)	The number of actual AEs during the 30-day post-discharge period	Up to 30-days after discharge from index hospitalization
Secondary	Potential adverse events (AEs)	The number of new or worsening symptoms reported by the patient	Up to 30-days after discharge from index hospitalization
Secondary	Post-discharge healthcare utilization events (hospital readmissions)	Hospital readmissions	Up to 30-days after discharge from index hospitalization
Secondary	Post-discharge healthcare utilization (ambulatory events)	Composite of unanticipated ambulatory, urgent care, ED visits	Up to 30-days after discharge from index hospitalization