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A quantitative approach to evaluating open-source EHR systems for Indian healthcare: a metadata perspective

Biswanath Dutta & D J Bain

Informatics for Health and Social Care2026https://doi.org/10.1080/17538157.2026.2641129article
ABDC C
Weight
0.50

What the paper says

The standardization of Electronic Health Records (EHRs) is a nationally significant priority in India, given the scale and diversity of its healthcare system. To promote uniform clinical documentation, the Ministry of Health and Family Welfare (MoHFW), Government of India, introduced the Electronic Health Record Minimum Data Set (EHRMDS). However, the structural alignment of existing Open-Source Electronic Health Record Systems (OS-EHRS) with this mandated dataset remains insufficiently examined. This study presents a field-level, metadata-based quantitative assessment of alignment between EHRMDS and OS-EHRS, focusing on metadata presence rather than semantic, workflow, or technical interoperability. A structured crosswalk methodology combining syntactic similarity and ontology-supported semantic evaluation was applied to compare EHRMDS elements with those exposed by selected OS-EHRS data models. A closeness percentage metric is introduced as a heuristic benchmarking measure of relative metadata alignment. Results show that OpenEMR has the highest alignment (73.81%), while OpenClinic has the lowest (33.33%). The study identifies 47 clinically relevant metadata elements present across OS-EHRS but absent from EHRMDS, consolidated into an extended schema (EHRMDS-ext.) proposed as an enhancement rather than a replacement. The primary novelty of this work lies in introducing a quantitative benchmarking framework for evaluating EHR metadata alignment in Indian context, moving beyond prior descriptive or qualitative analyses. The findings are intended to support standard development and future interoperability research.

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https://doi.org/https://doi.org/10.1080/17538157.2026.2641129

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@article{biswanath2026,
  title        = {{A quantitative approach to evaluating open-source EHR systems for Indian healthcare: a metadata perspective}},
  author       = {Biswanath Dutta & D J Bain},
  journal      = {Informatics for Health and Social Care},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/17538157.2026.2641129},
}

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A quantitative approach to evaluating open-source EHR systems for Indian healthcare: a metadata perspective

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.