International journal of medical informatics · 2026
From digital adoption to health-system transformation: A systematic review of outcomes, implementation barriers, and conditions for scale across global health systems.
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Alhazmi Ali
Аннотация
BACKGROUND: Digital adoption does not equate to health-system transformation, and evidence of sustained benefit remains insufficient, partly because empirical and review/framework evidence is rarely distinguished.
OBJECTIVE: To synthesize evidence on outcomes, implementation barriers, and conditions for scale of digital transformation across global health systems, and derive a testable implementation-to-impact pathway.
METHODS: Reports published between 2015 and July 2026 were identified in PubMed, Scopus, IEEE Xplore, ACM Digital Library, and Google Scholar (supplementary source). Of 4420 result entries, 198 full texts were retrieved and 193 unique reports were assessed for eligibility; a second researcher verified all inclusions and a random 20% of exclusions. Reports were classified as direct empirical or review/framework evidence, appraised with the Mixed Methods Appraisal Tool and design-appropriate checklists (JBI, RAMESES, SANRA), and synthesized qualitatively using a normalized codebook; heterogeneity precluded meta-analysis.
RESULTS: Forty-six reports were included (23 empirical, 23 review/framework); 33 (71.7%) were published in 2024-2026. Among the 22 primary-synthesis empirical reports, the most frequent outcomes were workforce experience (12), perceived efficiency (8), data capability (6), and access (5); population health, cost, safety, and equity evidence was largely absent. Workforce (14), infrastructure and workflow (12 each), and governance (10) led empirical barrier domains, versus governance (19), workforce (17), and infrastructure (13) in the review layer; this pattern held among 39 higher/moderate-weight reports. Evidence on scaling clustered around eight gates - value, fit, adoption, finance, safety, equity, institutionalization, and adaptive learning - each supported by 13 to 31 reports; all eight were retained in an empirical-only sensitivity analysis.
CONCLUSION: Measurable health-system change was more often reported when governance, finance, infrastructure, interoperability, workflow, workforce participation, trust, safety, and equity were aligned around a defined public value than when technology deployment alone was scaled. These associations, drawn largely from qualitative and observational studies, inform a review-derived implementation-to-impact pathway offered for prospective testing.
OBJECTIVE: To synthesize evidence on outcomes, implementation barriers, and conditions for scale of digital transformation across global health systems, and derive a testable implementation-to-impact pathway.
METHODS: Reports published between 2015 and July 2026 were identified in PubMed, Scopus, IEEE Xplore, ACM Digital Library, and Google Scholar (supplementary source). Of 4420 result entries, 198 full texts were retrieved and 193 unique reports were assessed for eligibility; a second researcher verified all inclusions and a random 20% of exclusions. Reports were classified as direct empirical or review/framework evidence, appraised with the Mixed Methods Appraisal Tool and design-appropriate checklists (JBI, RAMESES, SANRA), and synthesized qualitatively using a normalized codebook; heterogeneity precluded meta-analysis.
RESULTS: Forty-six reports were included (23 empirical, 23 review/framework); 33 (71.7%) were published in 2024-2026. Among the 22 primary-synthesis empirical reports, the most frequent outcomes were workforce experience (12), perceived efficiency (8), data capability (6), and access (5); population health, cost, safety, and equity evidence was largely absent. Workforce (14), infrastructure and workflow (12 each), and governance (10) led empirical barrier domains, versus governance (19), workforce (17), and infrastructure (13) in the review layer; this pattern held among 39 higher/moderate-weight reports. Evidence on scaling clustered around eight gates - value, fit, adoption, finance, safety, equity, institutionalization, and adaptive learning - each supported by 13 to 31 reports; all eight were retained in an empirical-only sensitivity analysis.
CONCLUSION: Measurable health-system change was more often reported when governance, finance, infrastructure, interoperability, workflow, workforce participation, trust, safety, and equity were aligned around a defined public value than when technology deployment alone was scaled. These associations, drawn largely from qualitative and observational studies, inform a review-derived implementation-to-impact pathway offered for prospective testing.