Evidence map›Paper›PMID 25796595›Full record

SynthesisJournal of the American Medical Informatics Association : JAMIA2015

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis.

Alberto Moreno-Conde, David Moner, Wellington Dimas da Cruz, Marcelo R Santos, José Alberto Maldonado, Montserrat Robles, Dipak Kalra

Abstract readComparative StudySystematic Review
In one paragraph

Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 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

31 citing papers in PubMed, 4 syntheses or guidelines 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

7 authors.

Alberto Moreno-CondeCentre for Health Informatics and Multiprofessional Education, University College London, London, UK Hospital Universitario Virgen del Rocío, Sevilla, Spain albertomorenoconde@gmail.com.
David MonerInstituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Valencia, Spain.
Wellington Dimas da CruzUniversidade FUMEC, Belo Horizonte, Brazil.
Marcelo R SantosCentro de Informática em Saúde (CINS), Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
José Alberto MaldonadoInstituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Valencia, Spain VeraTech for Health SL, Valencia, Spain.
Montserrat RoblesInstituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Valencia, Spain.
Dipak KalraCentre for Health Informatics and Multiprofessional Education, University College London, London, UK.

Funding

Medical Research Council MR/K006584/1
6 · The paper itself

Abstract

objectiveThis systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. MATERIAL AND

methodsFollowing the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles.

resultsThree hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. DISCUSSION: Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality.

conclusionIndependently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler.

Indexed as

Medical InformaticsVocabulary, ControlledElectronic Health RecordsInformation SystemsModels, TheoreticalSemanticsSystems Integrationclinical information modelclinical information modelingelectronic health recordsemantic interoperabilitysystematic review

Identifiers

PMID25796595
PMCPMC11737645

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.