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Training Residents in the Application of Clinical Guidelines for Differential Diagnosis of the Most Frequent Causes of Arterial Hypertension with Decision Tables

  • Francis Real
  • David RiañoEmail author
  • José Ramón Alonso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8903)

Abstract

Arterial hypertension (AH) is an abnormal high blood pressure in the arteries with many possible etiologies. Differential diagnosis of the causes of AH is a complex clinical process that requires the simultaneous consideration of many clinical practice guidelines.

Training clinicians to manage, assimilate, and correctly apply the knowledge contained in the guidelines of the most frequent causes of AH is a challenge that we have addressed with the combined use of different sorts of decision tables. After extracting the diagnostic knowledge available in eight clinical practice guidelines of the most frequent secondary causes of hypertension, we have represented this knowledge as decision tables, and have used these tables to train 23 residents at the Hospital Clínic de Barcelona. During the training, the decisions of the residents along the differential diagnostic steps were compared with the decisions provided by the decision tables so that we could analyze the progressive adaptation of clinicians’ decisions to the guidelines’ recommendations.

The study shows a progressive improvement of the adherence of the residents to the guidelines as new AH cases are considered, reaching full adherence after a training with 30 clinical cases.

Keywords

Arterial Hypertension Final Diagnosis Clinical Practice Guideline Training System Decision Table 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Francis Real
    • 1
  • David Riaño
    • 1
    Email author
  • José Ramón Alonso
    • 2
  1. 1.Research Group on Artificial IntelligenceUniversitat Rovira i VirgiliTarragonaSpain
  2. 2.Emergency DepartmentHospital Clínic de BarcelonaBarcelonaSpain

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