{"doi":"10.4239/wjd.v16.i8.107733","title":"Digital health for rural diabetes care: Implementation experience from China and India","abstract":"Diabetes affects an estimated 828 million people globally, with approximately 44% living in China and India. Rural residents with diabetes in these countries face significant challenges in access to care. Although digital health interventions are increasingly used to reach underserved populations, considerable knowledge gaps exist. This mini-review presents the first comparative analysis of digital health implementations for diabetes care in rural China and India, comprising clinical decision support tools, telemedicine, and mobile health applications. The review examines how their distinct health system structures influence technology adoption and clinical outcomes. China's hierarchical administrative structure facilitates standardized nationwide platforms with consistent protocols, while India's federal system enables diverse localized innovations that accommodate regional diversity. Cluster-randomized trials for digital health tools in rural China show significant improvements in glycemic control. In India, interventions examined in this review were associated with improved health behaviors and medication adherence. Both countries demonstrate that digital interventions leveraging existing social structures and co-created with stakeholders yield better outcomes than standard care approaches. This analysis provides actionable insights for policymakers globally while identifying valuable opportunities for knowledge exchange between these two nations that together are home to nearly half of all people living with diabetes worldwide.","journal":"World Journal of Diabetes","year":2025,"id":524430,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9432,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":413289,"name":"David Beran","orcid":"0000-0001-7229-3920","position":1,"is_corresponding":false},{"id":525112,"name":"Pengpeng Ye","orcid":"0000-0002-2924-1436","position":2,"is_corresponding":false},{"id":590216,"name":"Surabhi Joshi","orcid":null,"position":3,"is_corresponding":false},{"id":954340,"name":"Xuejun Yin","orcid":"0000-0001-8446-9591","position":4,"is_corresponding":false},{"id":22843,"name":"Nikhil Tandon","orcid":"0000-0003-4604-1986","position":5,"is_corresponding":false},{"id":1397945,"name":"Ruitai Shao","orcid":"0000-0003-1977-7445","position":6,"is_corresponding":false},{"id":1397944,"name":"Alon Rasooly","orcid":"0000-0002-0388-9883","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:50:12.083054Z","pmid":"40948670","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}