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Automated clinical pathway standardization using SNOMED CT- based semantic relatedness.

Ayman Alahmar1, Mohannad AlMousa1, Rachid Benlamri1

  • 1Department of Software Engineering, Lakehead University, Thunder Bay, Ontario, Canada.

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|April 8, 2022
PubMed
Summary
This summary is machine-generated.

Automating clinical pathway standardization using a semantic score-based algorithm significantly improves efficiency. This approach helps physicians quickly find appropriate SNOMED CT terms, enhancing healthcare informatics.

Keywords:
Automation in health careSNOMED CTclinical pathwaydata analyticshealth information systemontologypublic health caresemantic relatednesssemantic score

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Area of Science:

  • Health Informatics
  • Medical Terminology Standardization
  • Clinical Pathway Computerization

Background:

  • Healthcare institutions face increasing patient loads and workloads, necessitating efficient and cost-effective care delivery.
  • Clinical pathways offer a promising solution for reducing costs and optimizing resource use, but are often paper-based.
  • Computerizing clinical pathways requires standardizing terminology to align with digital systems, a process currently manual and difficult to automate.

Purpose of the Study:

  • To introduce automation into the clinical pathway standardization process.
  • To develop a system that assists physicians in standardizing clinical pathway terminology using SNOMED CT.
  • To enhance the efficiency and accuracy of integrating clinical pathways into health information systems.

Main Methods:

  • Development of a semantic score-based algorithm for automated SNOMED CT term searching.
  • Implementation of the algorithm into a software system with a graphical user interface for physician use.
  • Validation of the system and algorithm using SNOMED CT ontology and case studies.

Main Results:

  • The algorithm achieved a maximum search space reduction of 98.9% in single iterations and an overall average reduction of 71.3%.
  • The system enables physicians to locate relevant SNOMED CT terms precisely and efficiently.
  • Case studies demonstrated the effectiveness of human-guided automation in clinical pathway standardization.

Conclusions:

  • Automating clinical pathway standardization is feasible and beneficial for healthcare informatics.
  • The developed system significantly improves the speed and accuracy of terminology standardization.
  • Human-guided automation represents a promising methodology for advancing clinical pathway computerization.