Digital Health and Personalized Care for Chronic Disease Management in Primary Health Care

Abla Almalik¹, Asim Ahmed², Leon Zimmermann³, Mia Hoffmann⁴

Abstract

https://doi.org/10.5281/zenodo.20778168 

 Follow-up in primary health care. Traditional models that depend mainly on episodic clinic visits may miss early deterioration, treatment non-response, poor adherence, and emerging cardiometabolic risk. Objective: This scoping review mapped how digital health tools and personalized care approaches are used to support chronic disease management in primary health care and community-based outpatient settings. Methods: The review followed the PRISMA extension for scoping reviews, with reference to the PRISMA 2020 framework. Searches were conducted in PubMed, Scopus, Web of Science, Google Scholar, Elicit, Semantic Scholar, and citation tracking. Eligible evidence sources involved adults with chronic non-communicable diseases and described digital health, remote monitoring, telemedicine, mobile health, electronic health records, artificial intelligence-supported follow-up, risk stratification, or personalized care. Results: A total of 418 records were identified. After removal of 103 duplicates, 315 records were screened, 257 were excluded at title and abstract stage, 58 full-text reports were assessed, and 16 evidence sources were included. The mapped evidence covered diabetes, hypertension, dyslipidemia and cardiovascular risk, chronic obstructive pulmonary disease, heart failure, multimorbidity, and humanitarian or low-resource settings. Digital approaches included telemonitoring, mobile applications, electronic health record-linked prompts, patient portals, automated reminders, digital education, clinical decision support, and emerging digital twin models. The clearest evidence concentration was found in diabetes, hypertension, and cardiometabolic risk, while COPD, heart failure, low-resource settings, and humanitarian contexts were less consistently represented. Conclusion: Digital health and personalized care can support continuity, early intervention, patient engagement, and risk-based chronic disease management in primary health care. Implementation requires clinical integration, equity-sensitive design, workflow alignment, data governance, and sustainable service models rather than technology deployment alone.