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Cited by 378

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The Barriers to Electronic Medical Record Systems and How to Overcome Them

Open access
McDonald, C. J.·1997·Journal of the American Medical Informatics Association

Abstract

Institutions all want electronic medical record (EMR) systems. They want them to solve their record movement problems, to improve the quality and coherence of the care process, to automate guidelines and care pathways to assist clinical research, outcomes management, and process improvement. EMRs are very difficult to construct because the existing electronic data sources, e.g., laboratory systems, pharmacy systems, and physician dictation systems, reside on many isolated islands with differing structures, differing levels of granularity, and different code systems. To accelerate EMR deployment we need to focus on the interfaces instead of the EMR system. We have the interface solutions in the form of standards: IP, HL7/ASTM, DICOM, LOINC, SNOMED, and others developed by the medical informatics community. We just have to embrace them. One remaining problem is the efficient capture of physician information in a coded form. Research is still needed to solve this last problem.

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Crossref · 10.1136/jamia.1997.0040213

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Metadata

Authors
McDonald, C. J.
Venue
Journal of the American Medical Informatics Association
Published
1997-05-01
Volume
4
Issue
3
Pages
213-221
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
OpenAlex
W2128716459
Cited by
378
References
1
FWCI
37.15
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The Barriers to Electronic Medical Record Systems and How to Overcome Them. https://app.cochat.ai/papers/10.1136/jamia.1997.0040213
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McDonald, C. J. (1997). The Barriers to Electronic Medical Record Systems and How to Overcome Them. Journal of the American Medical Informatics Association. https://doi.org/10.1136/jamia.1997.0040213

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.