Evidence map›Paper›PMID 41814351›Full record

ArticleBMC health services research2026

Mapping digital health maturity models and accreditation-linked standards: a scoping review to position the National Accreditation Board for Hospitals & Healthcare Providers (NABH) digital health standards of India.

Margeyi Mehta, Jigish Shah, Urvish Joshi, Sharon Baisil, Sanjay Kini B

Abstract readScoping Review
In one paragraph

Article in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Margeyi MehtaDepartment of Clinical Biochemistry, Medical College Baroda, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India.ORCID http://orcid.org/0009-0003-3326-1952
Jigish ShahDepartment of Microbiology, Parul Institute of Medical Sciences & Research, Parul University, Vadodara, Gujarat, India.ORCID http://orcid.org/0009-0005-6901-8131
Urvish JoshiDepartment of Community Medicine, Narendra Modi Medical College, Gujarat University, Ahmedabad, Gujarat, India.ORCID http://orcid.org/0000-0002-9204-5614
Sharon BaisilDepartment of Community Medicine, Malankara Orthodox Syrian Church Medical College, Kerala University of Health Sciences, Kolenchery, Kerala, India.ORCID http://orcid.org/0000-0002-3347-8014
Sanjay Kini BDepartment of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India. sanjay.kb@manipal.edu.ORCID http://orcid.org/0000-0002-3571-2337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital transformation in healthcare is guided globally by digital health maturity models and accreditation-linked standards. In India, the National Accreditation Board for Hospitals & Healthcare Providers (NABH) introduced landmark Digital Health Standards (DHS) for hospitals (2025 draft). This provides a national framework, but its positioning within the complex global landscape is unclear, making it challenging for stakeholders to benchmark progress and plan strategically.

objectivesThe primary objective was to map the features, domains, and assessment approaches of prominent international digital health maturity models and accreditation-linked standards. The secondary objective was to conduct a comparative analysis of these frameworks against the NABH-DHS to identify areas of convergence, divergence, and critical gaps.

methodsA scoping review adhering to PRISMA-ScR guidelines was conducted. Peer-reviewed databases (PubMed, Embase, Scopus) and grey literature sources were searched from inception to 26 July 2025. We included sources describing national or international maturity models or accreditation standards for healthcare provider organizations. Data were charted using a customized form, synthesized narratively (SWiM), and comparatively analysed using a conceptual crosswalk matrix and thematic gap map.

results38 sources were included, comprising systematic/scoping reviews (n = 8), official reports/standards (n = 17), and primary studies (n = 13). Key international frameworks mapped include HIMSS EMRAM, NHS England’s WGLL, WHO-PAHO IS4H, JCI, and Australian models. The NABH-DHS (structured across 8 chapters) shows strong alignment with these frameworks in core domains: Leadership, Governance, Clinical & Patient Safety, and Information & Data Management. However, the comparative analysis identified emerging gaps vis-à-vis global best practices. These include absent or minimal coverage for explicit AI governance, advanced cybersecurity maturity (e.g., alignment with NIST CSF 2.0), granular interoperability maturity assessment, a dedicated health-equity lens, and the systematic integration of Patient-Generated Health Data (PGHD).

conclusionsThe NABH-DHS provide a robust and comprehensive foundation for core digital assurance in India, converging well with international best practices on foundational elements. Our mapped findings are presented as external policy guidance. We recommend that future NABH revisions incorporate pragmatic, light-weight requirements to address the identified gaps (AI governance, advanced cybersecurity, interoperability metrics, and equity). This can be achieved through annexes or tiered ‘Digital Plus’ badges that reference mature external frameworks (e.g., ISO/IEC 42001, NIST CSF 2.0), ensuring a future-proof, phased implementation that safeguards patient trust as the Indian digital health ecosystem matures.

Indexed as

AccreditationDigital HealthHospitalsHumansIndiaAI governanceCybersecurityDigital health governanceDigital health maturity modelHealthcare accreditationHealth equityHealth Information Systems (HIS)InteroperabilityNABH Digital Health StandardsScoping review

Identifiers

PMID41814351
PMCPMC13032403

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.