Evidence map›Paper›PMID 34450285›Full record

ArticleJournal of biomedical informatics2021

Enhancing narrative clinical guidance with computer-readable artifacts: Authoring FHIR implementation guides based on WHO recommendations.

Jennifer Shivers, Joseph Amlung, Natschja Ratanaprayul, Bryn Rhodes, Paul Biondich

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Jennifer ShiversGlobal Health Informatics, Regenstrief Institute, Indianapolis, IN, United States. Electronic address: jeshiver@regenstrief.org.
Joseph AmlungGlobal Health Informatics, Regenstrief Institute, Indianapolis, IN, United States.
Natschja RatanaprayulPublic Digital Health Technology, Department of Digital Health and Innovation, World Health Organization, Geneva, Switzerland.
Bryn RhodesAlphora, Orem, UT, United States.
Paul BiondichGlobal Health Informatics, Regenstrief Institute, Indianapolis, IN, United States.

Funding

World Health Organization 001
6 · The paper itself

Abstract

introductionNarrative clinical guidelines often contain assumptions, knowledge gaps, and ambiguities that make translation into an electronic computable format difficult. This can lead to divergence in electronic implementations, reducing the usefulness of collected data outside of that implementation setting. This work set out to evolve guidelines-based data dictionaries by mapping to HL7 Fast Health Interoperability Resources (FHIR) and semantic terminology, thus progressing toward machine-readable guidelines that define the minimum data set required to support family planning and sexually transmitted infections. MATERIAL AND

methodsThe data dictionaries were first structured to facilitate mapping to FHIR and semantic terminologies, including ICD-10, SNOMED-CT, LOINC, and RxNorm. FHIR resources and codes were assigned to data dictionary terms. The data dictionary and mappings were used as inputs for a newly developed tool to generate FHIR implementation guides.

resultsImplementation guides for core data requirements for family planning and sexually transmitted infections were created. These implementation guides display data dictionary content as FHIR resources and semantic terminology codes. Challenges included the use of a two-dimensional spreadsheet to facilitate mapping, the need to create FHIR profiles and resource extensions, and applying FHIR to a data dictionary that was created with a user interface in mind.

conclusionsAuthoring FHIR implementation guides is a complex and evolving practice, and there are limited examples for this groundbreaking work. Moving toward machine-readable guidelines by mapping to FHIR and semantic terminologies requires a thorough understanding of the context and use of terminology, an applied information model, and other strategies for optimizing the creation and long-term management of implementation guides. Next steps for this work include validation and, eventually, real-world application. The process for creating the data dictionary and for generating implementation guides should also be improved to prepare for this expanding work.

fundingThis work was supported by the World Health Organization, which also worked as a collaborative partner throughout the study.

Indexed as

ArtifactsSystematized Nomenclature of MedicineComputersElectronic Health RecordsVocabulary, ControlledWorld Health OrganizationFast Healthcare Interoperability Resources (FHIR)Global HealthMedical InformaticsPractice GuidelineTerminology

Identifiers

PMID34450285
PMCPMC8524423

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.