{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:12:26Z","timestamp":1787505146226,"version":"build-2736575974"},"reference-count":36,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Particip Med"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Managing patients with multiple chronic comorbidities is complex and challenging within traditional health care systems due to the need for multidisciplinary expertise, longitudinal tracking, and coordination. The development of collaborative online platforms leveraging user-driven health care (UDHC) and medical cognition principles offers new avenues for addressing these complexities by facilitating remote, participatory, and evidence-informed case management.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n The aim of this study was to demonstrate the application of a collaborative online case-based blended learning ecosystem (CBBLE) integrated with a patient journey record (PaJR) for the comprehensive remote management and review of a complex patient case with multiple chronic conditions. The study also aimed to evaluate how participatory medical cognition through this platform supports decision-making, patient empowerment, and clinical outcomes in a resource-constrained rural setting.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A single case study of a 44-year-old female patient from rural India with multiple chronic conditions\u2014including type 2 diabetes mellitus, Meesmann corneal epithelial dystrophy postphototherapeutic keratectomy, recurrent infections, lateral epicondylalgia, and hypertension\u2014was managed remotely from December 2024 to May 2025. Deidentified 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 artificial intelligence [AI]\u2013assisted literature retrieval), and ongoing clinical discussions. The patient advocate facilitated detailed symptoms and lifestyle logging. This case is intended to illustrate feasibility rather than establish generalizability.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The participatory platform enabled multispecialty expert input and integrated patient context to optimize management. The patient reduced antidiabetic medication significantly 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. Despite ongoing challenges with some symptoms (eg, eye issues and arm function), the patient reported improved quality of life, confidence, and satisfaction from reduced medication burden and comprehensive monitoring.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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. Although this study presents a single case, wider adoption of similar digital platforms could significantly improve management of complex patients and foster a new model of user-driven, participatory health care and learning.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/81950","type":"journal-article","created":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T14:55:07Z","timestamp":1759071307000},"page":"e81950-e81950","source":"Crossref","is-referenced-by-count":1,"title":["Rethinking Complex Care Using Participatory Medical Cognition and User-Driven Learning Amidst Multimorbidity: Participatory Action Research 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