Toward Standardized Monitoring of Patients With Chronic Diseases in Primary Care Using Electronic Medical Records: Development of a Tool by Adapted Delphi Procedure.

arterial hypertension asthma chronic heart failure diabetes mellitus type 2 electronic medical record indicators monitoring of chronic diseases osteoarthritis primary care

Journal

JMIR medical informatics
ISSN: 2291-9694
Titre abrégé: JMIR Med Inform
Pays: Canada
ID NLM: 101645109

Informations de publication

Date de publication:
25 Mar 2020
Historique:
received: 24 04 2019
accepted: 21 01 2020
revised: 18 09 2019
entrez: 27 3 2020
pubmed: 27 3 2020
medline: 27 3 2020
Statut: epublish

Résumé

Long-term care for patients with chronic diseases poses a huge challenge in primary care. There are deficits in care, especially regarding monitoring and creating structured follow-ups. Appropriate electronic medical records (EMR) could support this, but so far, no generic evidence-based template exists. The aim of this study is to develop an evidence-based standardized, generic template that improves the monitoring of patients with chronic conditions in primary care by means of an EMR. We used an adapted Delphi procedure to evaluate a structured set of evidence-based monitoring indicators for 5 highly prevalent chronic diseases (ie, diabetes mellitus type 2, asthma, arterial hypertension, chronic heart failure, and osteoarthritis). We assessed the indicators' utility in practice and summarized them into a user-friendly layout. This multistep procedure resulted in a monitoring tool consisting of condensed sets of indicators, which were divided into sublayers to maximize ergonomics. A cockpit serves as an overview of fixed goals and a set of procedures to facilitate disease management. An additional tab contains information on nondisease-specific indicators such as allergies and vital signs. Our generic template systematically integrates the existing scientific evidence for the standardized long-term monitoring of chronic conditions. It contains a user-friendly and clinically sensible layout. This template can improve the care for patients with chronic diseases when using EMRs in primary care.

Sections du résumé

BACKGROUND BACKGROUND
Long-term care for patients with chronic diseases poses a huge challenge in primary care. There are deficits in care, especially regarding monitoring and creating structured follow-ups. Appropriate electronic medical records (EMR) could support this, but so far, no generic evidence-based template exists.
OBJECTIVE OBJECTIVE
The aim of this study is to develop an evidence-based standardized, generic template that improves the monitoring of patients with chronic conditions in primary care by means of an EMR.
METHODS METHODS
We used an adapted Delphi procedure to evaluate a structured set of evidence-based monitoring indicators for 5 highly prevalent chronic diseases (ie, diabetes mellitus type 2, asthma, arterial hypertension, chronic heart failure, and osteoarthritis). We assessed the indicators' utility in practice and summarized them into a user-friendly layout.
RESULTS RESULTS
This multistep procedure resulted in a monitoring tool consisting of condensed sets of indicators, which were divided into sublayers to maximize ergonomics. A cockpit serves as an overview of fixed goals and a set of procedures to facilitate disease management. An additional tab contains information on nondisease-specific indicators such as allergies and vital signs.
CONCLUSIONS CONCLUSIONS
Our generic template systematically integrates the existing scientific evidence for the standardized long-term monitoring of chronic conditions. It contains a user-friendly and clinically sensible layout. This template can improve the care for patients with chronic diseases when using EMRs in primary care.

Identifiants

pubmed: 32209535
pii: v8i3e14483
doi: 10.2196/14483
pmc: PMC7142740
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e14483

Informations de copyright

©Leandra Christina Falck, Marco Zoller, Thomas Rosemann, Nahara Anani Martínez-González, Corinne Chmiel. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 25.03.2020.

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Auteurs

Leandra Falck (L)

Institute of Primary Care, University of Zurich and University Hospital of Zurich, Zurich, Switzerland.

Marco Zoller (M)

Institute of Primary Care, University of Zurich and University Hospital of Zurich, Zurich, Switzerland.

Thomas Rosemann (T)

Institute of Primary Care, University of Zurich and University Hospital of Zurich, Zurich, Switzerland.

Nahara Anani Martínez-González (NA)

Institute of Primary Care, University of Zurich and University Hospital of Zurich, Zurich, Switzerland.

Corinne Chmiel (C)

Institute of Primary Care, University of Zurich and University Hospital of Zurich, Zurich, Switzerland.

Classifications MeSH