{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T18:06:39Z","timestamp":1788977199831,"version":"build-2803163510"},"reference-count":39,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Online J Public Health Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Multimorbidity, defined as the coexistence of two or more chronic conditions, challenges traditional, single-disease health care models. Although digital health technologies are increasingly applied to complex patient care, most interventions remain disease-specific and fail to account for interactions between coexisting conditions.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This scoping review aimed to systematically map and synthesize existing evidence on digital health interventions that explicitly address multimorbidity, focusing on how these solutions integrate disease interdependencies between coexisting diseases in their design, implementation, and evaluation. We aimed to identify underlying concepts, map frequently targeted disease clusters, and assess reported outcomes and barriers to real-world application.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and informed by PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension) recommendations, we conducted systematic searches in PubMed and CINAHL for studies published in English or German between January 2014 and May 2024. Eligible studies described digital health interventions targeting patients with two or more conditions and explicitly addressed interactions among diseases, symptoms, or treatments. We strictly excluded studies of digital solutions that addressed multiple conditions through isolated modules or separate functionalities without cross-condition integration. In addition, research focusing solely on technical development, polypharmacy, or usability was excluded. Two reviewers independently screened records and extracted data using a structured charting form. Data were synthesized using descriptive statistics and thematic analysis.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of 1660 records identified, 11 studies representing seven distinct digital health projects met the inclusion criteria. Most interventions focused on older adults with cardiometabolic or respiratory multimorbidity and combined mobile apps, telemonitoring platforms, and decision-support or analytic modules. While most interventions demonstrated feasibility and user acceptance, only a minority operationalized disease interactions beyond aggregated data. Approaches to multimorbidity included cross-disease analytics, composite risk indicators, and guideline-based decision support; however, systematic reconciliation of competing clinical recommendations was rare. Evaluation outcomes mainly addressed usability, engagement, and feasibility, whereas evidence regarding clinical effectiveness remained limited and inconsistent. Only two studies assessed clinical outcomes, with mixed findings.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This review provides a novel synthesis of how digital health interventions explicitly address multimorbidity as an interconnected phenomenon rather than as a set of isolated conditions. Current evidence suggests feasibility and user acceptance of digital tools, whereas robust implementation of multimorbidity-aware functionalities and evidence regarding benefit remain limited. Advancing this field will require interoperable, data-integrative systems capable of supporting coordinated multimorbidity care across conditions and care settings. These findings highlight the need for a shift from disease-centric toward integrated multimorbidity-oriented digital care models.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/88021","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T21:55:05Z","timestamp":1785189305000},"page":"e88021-e88021","source":"Crossref","is-referenced-by-count":0,"title":["eHealth Approaches to Multimorbidity Management: Scoping Review of Interventions and Multidisease Strategies"],"prefix":"10.2196","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3897-9604","authenticated-orcid":false,"given":"Katja","family":"Bochtler","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8452-4263","authenticated-orcid":false,"given":"Salima","family":"Houta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"issue":"16","key":"R1","doi-asserted-by":"publisher","DOI":"10.1186\/s12875-015-0344-4","article-title":"Challenges of managing people with multimorbidity in today\u2019s healthcare systems","volume":"16","author":"Moffat","journal-title":"BMC Fam Pract"},{"issue":"6","key":"R2","doi-asserted-by":"publisher","first-page":"3073","DOI":"10.1111\/hex.13614","article-title":"Patient co-design of digital health storytelling tools for multimorbidity: a phenomenological study","volume":"25","author":"Cummings","journal-title":"Health Expect"},{"key":"R3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2023.101860","article-title":"Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis","volume":"57","author":"Chowdhury","journal-title":"EClinicalMedicine"},{"key":"R4","unstructured":"\u201cJust one thing after another\u201d living with multiple conditions. 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