Synthesizing analytic evidence to refine care pathways. Academic Article uri icon

Overview

abstract

  • Care pathways play significant roles in delivering evidence-based and coordinated care to patients with specific conditions. In order to put care pathways into practice, clinical institutions always need to adapt them based on local care settings so that the best local practices can be incorporated and used to develop refined pathways. However, it is knowledge-intensive and error-prone to incorporate various analytic insights from local data sets. In order to assist care pathway developers in working effectively and efficiently, we propose to automatically synthesize the analytical evidences derived from multiple analysis methods, and recommend modelling operations accordingly to derive a refined care pathway for a specific patient cohort. We validated our method by adapting a Congestive Heart Failure (CHF) Ambulatory Care Pathway for patients with additional condition of COPD through synthesizing the results of variation analysis and frequent pattern mining against patient records.

publication date

  • January 1, 2015

Research

keywords

  • Data Mining
  • Decision Support Systems, Clinical
  • Electronic Health Records
  • Evidence-Based Medicine
  • Machine Learning

Identity

Scopus Document Identifier

  • 84937418325

PubMed ID

  • 25991104

Additional Document Info

volume

  • 210