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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Automated conflict resolution between multiple clinical pathways: a technology report.

Ian Litchfield¹, Alice Turner², Ruth Backman³

¹University of Birmingham. i.litchfield@bham.ac.uk.

Journal of Innovation in Health Informatics

|November 7, 2018

Summary

This summary is machine-generated.

Managing patients with multiple long-term conditions (multimorbidity) is complex. This study developed a software tool to automatically detect and resolve conflicts between clinical guidelines, aiding healthcare providers.

Keywords:

Computer Software Applications care pathways multimorbidity

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Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion

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Published on: January 20, 2019

Area of Science:

Health Informatics
Clinical Decision Support
Computational Medicine

Background:

Growing prevalence of multimorbidity in the UK presents complex patient management challenges.
Identifying guideline conflicts in multimorbidity care is currently manual and clinician-dependent.
Existing approaches require individual clinicians to collate disparate information, increasing the risk of errors.

Purpose of the Study:

To develop a framework for modeling diverse care pathways.
To investigate automated detection and resolution of conflicts between clinical guidelines.
To create a software tool for clinicians to map guidelines, identify conflicts, and suggest resolutions.

Main Methods:

Phase 1: Accurate modeling of clinical pathways for six common chronic diseases.
Phase 2: Automated identification and detection of inter-pathway conflicts and resolution strategies.
Phase 3: Case study validating the approach with clinicians and comparing manual vs. automated conflict resolution for a complex patient.

Main Results:

Development of a novel software-based method for identifying conflicts within clinical guidelines.
Demonstration of automated conflict detection and resolution capabilities.
Validation through a case study involving a fictional patient with multiple common morbidities.

Conclusions:

The developed software provides a crucial tool for clinicians managing patients with multimorbidity.
This approach supports both primary and secondary care settings by streamlining guideline conflict resolution.
Findings will enhance the safety and efficiency of care for patients with complex health needs.