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Exploring openEHR-based clinical guidelines in acute stroke care and research

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posted on 2024-09-02, 21:36 authored by Nadim Anani

Largely speaking, health information systems today are not able to exchange data between each other and understand the data’s meaning automatically by means of their information technology components. This lack of ‘interoperability’ also leads to patients experiencing an undesired discontinuity in their care. This thesis is a part of a health informatics field which tackles interoperability barriers by offering standardised information models for electronic health records. More specifically, this work explores possibilities of combining standardised information models offered by the openEHR interoperability approach with knowledge from evidence-based clinical practice guidelines. The applied methodology includes openEHR archetypes, the openEHR reference information model, standard medical terminologies such as SNOMED CT, the international stroke treatment registry SITS, a newly developed model for representing guideline knowledge (the ‘Care Entry-Network Model’), and rules authored in the Guideline Definition Language, a formalism recently endorsed by openEHR as a part of its specifications. The study design used is based on evaluating the work done by means of retrospectively checking the compliance of completed patient cases with guidelines from the domain of acute stroke management in Europe, both experimentally and using thousands of real patient cases from SITS. Our overall findings are that i) the Care Entry-Network Model facilitates an intermediate step between narrative guideline text and computer-interpretable guidelines to be deployed in openEHR systems, ii) the Guideline Definition Language is practicable for creating and automatically running openEHR-based computer-interpretable guidelines, where we also provide detailed accounts of our employed GDL technologies, and iii) the Guideline Definition Language combined with real patient data from patient data registries can generate new clinical knowledge, which in our case has benefited stroke carers and researchers working with acute stroke thrombolysis. In conclusion, using our methodology, health care stakeholders would get evidence-based knowledge components in their electronic health records based on shareable, well maintainable information and knowledge models in the form of archetypes and GDL rules respectively. However, our approach still needs to be tested at the point of clinical decision making and compared to other approaches for providing exchangeable computer-interpretable guidelines.

List of scientific papers

I. Anani N, Chen R, Prazeres Moreira T, Koch S. OpenEHR-based representation of guideline compliance data through the example of stroke clinical practice guidelines. Studies in Health Technology and Informatics. 2012;180:487-491.
https://doi.org/10.3233/978-1-61499-101-4-487

II. Anani N, Chen R, Prazeres Moreira T, Koch S. Retrospective checking of compliance with practice guidelines for acute stroke care : a novel experiment using openEHR’s Guideline Definition Language. BMC Medical Informatics and Decision Making. 2014 May 10;14:39.
https://doi.org/10.1186/1472-6947-14-39

III. Anani N, Mazya MV, Chen R, Prazeres Moreira T, Bill O, Ahmed N, Wahlgren N, Koch S. Retrospective checking of compliance with practice guidelines : applying openEHR’s Guideline Definition Language to the SITS international stroke treatment registry. [Manuscript]

IV. Anani N, Mazya MV, Bill O, Chen R, Koch S, Ahmed N, Wahlgren N, Prazeres Moreira T. Changes in European label and guideline adherence after updated recommendations for stroke thrombolysis : results from the Safe Implementation of Treatments in Stroke registry. Circulation: Cardiovascular Quality and Outcomes. 2015 Oct;8(6 Suppl 3):S155-S162.
https://doi.org/10.1161/CIRCOUTCOMES.115.002097

History

Defence date

2016-02-12

Department

  • Department of Medicine, Solna

Publisher/Institution

Karolinska Institutet

Main supervisor

Koch, Sabine

Publication year

2016

Thesis type

  • Doctoral thesis

ISBN

978-91-7676-204-2

Number of supporting papers

4

Language

  • eng

Original publication date

2016-01-18

Author name in thesis

Anani, Nadim

Original department name

Department of Medicine, Solna

Place of publication

Stockholm

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