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Related Experiment Video

Updated: Dec 25, 2025

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
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Quantification and visualisation methods of data-driven chronic care delivery pathways: protocol for a systematic

Luiza Siqueira do Prado1, Samuel Allemann2,3, Marie Viprey2,4

  • 1Health Services and Performance Research EA 7425, Université Claude Bernard Lyon 1, Lyon, France luiza.siqueira-do-prado@univ-lyon1.fr.

BMJ Open
|March 21, 2020
PubMed
Summary

This systematic review protocol outlines a method to analyze how electronic healthcare databases are used to create care delivery pathways (CDPs) for chronic conditions. The goal is to develop recommendations for constructing better CDPs to improve integrated care.

Keywords:
clinical decision support systemsclinical pathwaydata visualisationdelivery of health care, integratedelectronic healthcare databasesmedical informatics application

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Area of Science:

  • Health Informatics
  • Data Science
  • Healthcare Management

Background:

  • Chronic conditions necessitate long-term, integrated care, increasing healthcare system burden.
  • Electronic healthcare databases (EHD) offer valuable data for understanding and improving care delivery.
  • Care delivery pathways (CDPs) constructed from EHD can reveal insights into current practices and identify areas for enhancement.

Purpose of the Study:

  • To systematically review and describe the content and development of methods for quantifying and visualizing data-driven chronic care delivery pathways (CDPs).
  • To derive common recommendations for the construction of CDPs using electronic healthcare data.
  • To support integrated care initiatives by improving the efficiency and effectiveness of chronic disease management.

Main Methods:

  • A systematic literature search will be conducted across multiple databases (PubMed, Scopus, IEEE, CINAHL, EMBASE) without date restrictions.
  • Methods for chronic CDPs will be analyzed based on clinical, data science, and behavioral characteristics relevant to EHD use in long-term care.
  • Data extraction will involve deductive content analysis supplemented by inductive analysis to capture all relevant features.

Main Results:

  • The review will present a descriptive analysis of current CDP methods, comparing their approaches and characteristics.
  • Key findings will highlight the diversity in CDP quantification and visualization techniques.
  • The study will identify commonalities and differences in how clinical, data science, and behavioral aspects are addressed by existing methods.

Conclusions:

  • This systematic review will provide a comprehensive overview of existing CDP methods.
  • The findings will inform the development of standardized recommendations for constructing robust and effective CDPs.
  • Ultimately, this work aims to enhance integrated care for chronic conditions through improved data utilization in EHD.