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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Improving descriptive terminology using a descriptive algorithm as an educational intervention to improve referral

David W Middleton1, Olivia Dolan2

  • 1Craigavon Area Hospital Group Trust, Portadown, UK.

Clinical and Experimental Dermatology
|August 31, 2023
PubMed
Summary

Improving clinical communication in dermatology referrals is crucial. A new descriptive algorithm significantly increased accurate terminology in referrals from 37% to 70%.

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Area of Science:

  • Medical Education
  • Dermatology
  • Clinical Communication

Background:

  • Clinical communication accuracy in dermatology referrals is often suboptimal.
  • Baseline analysis revealed only 37% of inpatient referrals used accurate descriptive terminology.

Purpose of the Study:

  • To assess knowledge deficits in descriptive terminology for dermatology referrals.
  • To develop and evaluate a novel educational intervention to improve descriptive accuracy.

Main Methods:

  • The Belfast Dermatology Descriptive Algorithm was developed as a scaffolding resource.
  • The algorithm aids in identifying morphological features of eruptions and common pitfalls.
  • It was designed based on adult learning principles.

Main Results:

  • Following the algorithm's introduction, referral description accuracy increased to 70%.
  • This represents a significant improvement in clinical communication.

Conclusions:

  • Accessible educational resource tools can effectively enhance clinical practice education.
  • The Belfast Dermatology Descriptive Algorithm serves as a successful model for improving dermatology referral accuracy.