gms | German Medical Science

G-I-N Conference 2012

Guidelines International Network

22.08 - 25.08.2012, Berlin

PLUGGED-IN (Providing Likeable and Understandable Guidelines using GRADE in the EMR with Direct links to INdividual patient data) phase 1

Meeting Abstract

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  • L. Brandt - Department of Medicine, Innlandet Hospital Trust, Gjøvik, Norway
  • P.O. Vandvik - Department of Medicine, Innlandet Hospital Trust, Gjøvik, Norway

Guidelines International Network. G-I-N Conference 2012. Berlin, 22.-25.08.2012. Düsseldorf: German Medical Science GMS Publishing House; 2012. DocO58

doi: 10.3205/12gin090, urn:nbn:de:0183-12gin0901

Veröffentlicht: 10. Juli 2012

© 2012 Brandt et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



Background: Traditional Clinical decision support systems (CDSS) in Electronic Medical Records (EMR) provide clinicians with recommendations based on algorithms/rules using patient-specific information as inclusion/exclusion riteria. Improved systems (GRADE) for developing evidence-based guidelines result in the majority of recommendations being weak and warrant balanced clinical judgments without clear inclusion/exclusion criteria. Presentation of patient-specific information together with recommendations is relevant to facilitate use of guidelines, also in absence of such criteria.

Objectives: To develop a novel approach and data model for CDSS that allow direct presentation of high quality guidelines shown together with relevant patient-specific information in the EMR instead of relying solely on algorithms/rules.

Methods: We explored the content of recent guidelines from several different clinical areas and used these as basis for development of our data model.

Results: GRADE guidelines are particularly well suited for structured authoring and presentation through generic and standardized components (e.g. PICO, evidence profiles, structured recommendations). We have developed a data model and an authoring tool prototype that should allow production and presentation of standardized components in the EMRs, linked to relevant patient specific information selected by guideline authors during the authoring process. Functions to connect to structured languages (e.g. MesH) allow interoperability and increase practical value.

Discussion: Our simplistic approach to CDSS alleviate the major obstacles of content updating, alert fatigue and imprecision found in traditional algorithm-based CDSS.

Implications for guideline developers/users: PLUGGED-IN provides a model for incorporation of guidelines into EMRs.