JMIR Publications

ABSTRACT

Background:

Adverse events (AEs) after hospitalization are common and disproportionately affect adults with multiple chronic conditions (MCC). Patient-reported symptoms and self-assessed health may enable earlier detection of post-discharge AEs, but scalable, workflow-integrated approaches are limited.

Objective:

To identify user requirements for, and field test, an automated remote monitoring system to enhance AE surveillance during transitions.

Methods:

We conducted a mixed-methods study using an iterative, user-centered design approach. Semi-structured interviews with patients and clinicians informed system requirements, followed by real-world field testing. The prototype leveraged interoperable electronic health record data services, delivered automated post-discharge check-ins using symptom questionnaires and patient-reported outcomes (PROs), provided risk-stratified health advice, and escalated high-risk symptoms to clinicians. Descriptive statistics assessed feasibility and utilization; conventional content analysis identified user needs and implementation considerations.

Results:

Thirty-seven patients with MCC and 23 clinicians participated. Key requirements included clear communication of personalized risk based on red-flag symptoms, actionable guidance aligned with discharge instructions, explicit delineation of responsibility between inpatient and outpatient clinicians, and selective escalation to minimize burden. In field testing with 20 patients, 60% of automated questionnaires were completed. Seven patients received risk-stratified advice for new or worsening symptoms; among those with moderate- or high-risk alerts, emergency department visits occurred within one week of discharge. Patients found the system understandable and helpful, while clinicians noted challenges interpreting PRO trends.

Conclusions:

A user-informed, automated remote monitoring system was feasible and acceptable for AE surveillance during transitions but should prioritize clear risk communication, role clarity, and interpretable patient-reported data to support safer transitions in this population.