JMIR Publications

ABSTRACT

Background:

Managing patients with multiple chronic comorbidities is complex and challenging within traditional healthcare systems due to the need for multidisciplinary expertise, longitudinal tracking, and coordination. The development of collaborative online platforms leveraging user-driven healthcare (UDHC) and medical cognition principles offers new avenues for addressing these complexities by facilitating remote, participatory, and evidence-informed case management.

Objective:

To demonstrate the application of a collaborative online Case Based Blended Learning Ecosystem (CBBLE) integrated with Patient Journey Records (PaJR) for the comprehensive remote management and review of a complex patient case with multiple chronic conditions. The study aimed to evaluate how participatory medical cognition through this platform supports decision-making, patient empowerment, and clinical outcomes in a resource-constrained rural setting.

Methods:

A single case study of a 44-year-old female patient from rural India with multiple chronic conditions—including type 2 diabetes mellitus, Meesmann’s corneal epithelial dystrophy post-phototherapeutic keratectomy, recurrent infections, lateral epicondylalgia, and hypertension—was managed remotely from December 2024 to May 2025. De-identified health data, patient-reported outcomes, biometric monitoring, images, and historical records were shared asynchronously via an online e-log book platform. A global community of multidisciplinary experts engaged in collaborative review, critical evidence appraisal (including AI-assisted literature retrieval), and ongoing clinical discussions. The patient advocate facilitated detailed symptom and lifestyle logging. AI tools supplemented information synthesis without replacing expert judgment. Outcomes were documented using structured PaJR case reports.

Results:

The participatory platform enabled multi-specialty expert input and integrated patient context to optimize management. The patient reduced anti-diabetic medication significantly (from a previous higher dosage regimen to 750 mg/day Metformin alone) and discontinued all blood pressure and heart rate medications by March 2025. Lifestyle modifications, muscle strengthening exercises, and diet adjustments were effectively supported. Expert consensus reclassified her irregular heart rate symptoms as anxiety-related palpitations, safely withdrawing beta-blockers. Collaborative discussions guided conservative management of eye infections and pain syndromes. AI tools facilitated rapid evidence retrieval and debate over therapeutic uncertainties. Despite ongoing challenges with some symptoms (e.g., eye issues, arm function), the patient reported improved quality of life, confidence, and satisfaction from reduced medication burden and comprehensive monitoring. The platform fostered shared learning for clinicians and empowered the patient to become an active knowledge contributor.

Conclusions:

This case exemplifies the value of collaborative, multidisciplinary, and technology-enabled participatory medical cognition platforms for managing complex multimorbidity. By integrating patient-reported data, AI-supported evidence synthesis, and asynchronous expert consultation, such ecosystems can enable holistic, evidence-based care, reduce overtreatment, support patient empowerment, and enhance clinical education—particularly in resource-limited and geographically dispersed contexts. Challenges remain in data completeness and remote physical assessment. Wider adoption of these platforms could significantly improve management of complex patients and foster a new model of user-driven, participatory healthcare and learning.