A prospective observational concordance study to evaluate computational model-driven clinical practice guidelines for Type 2 diabetes mellitus.

Clinical decision support system Clinical practice guideline Evidence-based medicine Type 2 diabetes mellitus

Journal

International journal of medical informatics
ISSN: 1872-8243
Titre abrégé: Int J Med Inform
Pays: Ireland
ID NLM: 9711057

Informations de publication

Date de publication:
10 2023
Historique:
received: 13 05 2023
revised: 18 08 2023
accepted: 30 08 2023
medline: 3 10 2023
pubmed: 14 9 2023
entrez: 13 9 2023
Statut: ppublish

Résumé

Clinical Practice Guidelines (CPGs) provide healthcare professionals with performance and decision-making support during the treatment of patients. Sometimes, however, they are poorly implemented. The IDE The main objective of this paper is to present the results of the clinical validation of the IDE National and international knowledge sources on T2DM were selected and reviewed and used to define a diabetes CPG model on the IDE A concordance analysis was performed with the kappa value. Overall agreement between the recommendations provided by the system and those recorded in each patient's EHR was good (0.61 - 0.80) with a total kappa index of 0.701, leading to the conclusion that the system provided appropriate recommendations for each patient and was therefore well-functioning. A series of possible improvements were identified based on the limitations for the recovery of variables related to the quality of these recolected variables, the detection of duplicate recommendations based on different input variables for the same patient, and clinical usability, such as the capacity to generate reports based on the recommendations generated. Nevertheless, the project resulted in the IDE

Sections du résumé

BACKGROUND
Clinical Practice Guidelines (CPGs) provide healthcare professionals with performance and decision-making support during the treatment of patients. Sometimes, however, they are poorly implemented. The IDE
OBJECTIVE
The main objective of this paper is to present the results of the clinical validation of the IDE
METHODS
National and international knowledge sources on T2DM were selected and reviewed and used to define a diabetes CPG model on the IDE
RESULTS
A concordance analysis was performed with the kappa value. Overall agreement between the recommendations provided by the system and those recorded in each patient's EHR was good (0.61 - 0.80) with a total kappa index of 0.701, leading to the conclusion that the system provided appropriate recommendations for each patient and was therefore well-functioning.
CONCLUSIONS
A series of possible improvements were identified based on the limitations for the recovery of variables related to the quality of these recolected variables, the detection of duplicate recommendations based on different input variables for the same patient, and clinical usability, such as the capacity to generate reports based on the recommendations generated. Nevertheless, the project resulted in the IDE

Identifiants

pubmed: 37703798
pii: S1386-5056(23)00226-5
doi: 10.1016/j.ijmedinf.2023.105208
pii:
doi:

Types de publication

Observational Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

105208

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Carlos Luis Parra-Calderón reports financial support was provided by Ministerio de Economía y Competitividad. Carlos Luis Parra-Calderon reports a relationship with Andalusian Health Service that includes: employment. Carlos Luis Parra-Calderon reports a relationship with Andalusian Public Foundation for Health Research Management in Seville that includes: non-financial support. Esther Román Villarán reports a relationship with Andalusian Public Foundation for Health Research Management in Seville that includes: employment. Celia Alvarez Romero reports a relationship with Andalusian Public Foundation for Health Research Management in Seville that includes: employment. Alicia Martínez García reports a relationship with Andalusian Public Foundation for Health Research Management in Seville that includes: employment. Germán Antonio Escobar Rodríguez reports a relationship with Andalusian Public Foundation for Health Research Management in Seville that includes: employment. Maria Asunción Martínez-Brocca reports a relationship with Andalusian Health Service that includes: employment. Julián Alberto García García reports a relationship with University of Seville that includes: employment. María José Escalona Cuaresma reports financial support was provided by Ministerio de Economía y Competitividad. María José Escalona Cuaresma reports a relationship with University of Seville that includes: employment.

Auteurs

Carlos Luis Parra-Calderón (CL)

Computational Health Informatics' Group. Seville Institute of Biomedicine (IbiS)/"Virgen del Rocío" University Hospital/CSIC/University of Seville, Avenida Manuel Siurot, 41013 Seville, Spain. Electronic address: carlos.parra.sspa@juntadeandalucia.es.

Esther Román-Villarán (E)

Computational Health Informatics' Group. Seville Institute of Biomedicine (IbiS)/"Virgen del Rocío" University Hospital/CSIC/University of Seville, Avenida Manuel Siurot, 41013 Seville, Spain. Electronic address: esther.roman@juntadeandalucia.es.

Celia Alvarez-Romero (C)

Computational Health Informatics' Group. Seville Institute of Biomedicine (IbiS)/"Virgen del Rocío" University Hospital/CSIC/University of Seville, Avenida Manuel Siurot, 41013 Seville, Spain. Electronic address: celia.alvarez@juntadeandalucia.es.

Germán Antonio Escobar-Rodríguez (GA)

Computational Health Informatics' Group. Seville Institute of Biomedicine (IbiS)/"Virgen del Rocío" University Hospital/CSIC/University of Seville, Avenida Manuel Siurot, 41013 Seville, Spain. Electronic address: german.antonio.er@gmail.com.

Maria Asunción Martínez-Brocca (MA)

Virgen Macarena" University Hospital, Seville, Spain; Comprehensive Plan for Diabetes in Andalusia, Andalusian Health Service, Calle Doctor Fedriani, 3, 41009 Seville, Spain. Electronic address: carlos.parra.sspa@juntadeandalucia.es.

Alicia Martínez-García (A)

Computational Health Informatics' Group. Seville Institute of Biomedicine (IbiS)/"Virgen del Rocío" University Hospital/CSIC/University of Seville, Avenida Manuel Siurot, 41013 Seville, Spain. Electronic address: alicia.martinez.ga.sspa@juntadeandalucia.es.

Julián Alberto García-García (JA)

Computer Languages and Systems Department, Escuela Técnica Superior de Ingeniería Informática, Avda. Reina Mercedes s/n. 41012 Seville, Spain. Electronic address: juliangg@us.es.

María José Escalona-Cuaresma (MJ)

Computer Languages and Systems Department, Escuela Técnica Superior de Ingeniería Informática, Avda. Reina Mercedes s/n. 41012 Seville, Spain. Electronic address: mjescalona@us.es.

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Classifications MeSH