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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
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A Bayesian Network-Based Browsing Model for Patients Seeking Radiology-Related Information on Hospital Websites:

Ryusuke Suzuki1, Teppei Suzuki1,2, Shintaro Tsuji1

  • 1Graduate School of Health Sciences, Hokkaido University, Sapporo, Japan.

Journal of Medical Internet Research
|January 19, 2021
PubMed
Summary
This summary is machine-generated.

Hospital websites need improvement to meet patient information needs, especially in radiation departments. Analyzing website behavior with Bayesian networks can enhance patient access to crucial radiology information.

Keywords:
hospitalsinformation-seeking behaviorinternetradiologyweb marketing

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Area of Science:

  • Medical Informatics
  • Health Services Research

Background:

  • Patient engagement with hospital websites is increasing for service and treatment information.
  • Current hospital websites often fail to meet patient needs, particularly for detailed radiation department information.
  • Information on radiation modality and diagnosis is frequently fragmented on hospital websites.

Purpose of the Study:

  • To develop a hospital website search behavior model using Bayesian networks.
  • To analyze patient browsing behavior for one-to-one marketing insights.
  • To identify improvements for hospital website usability in radiology departments.

Main Methods:

  • Analysis of website access logs from Hokkaido University Hospital (Sept 2016 - Aug 2017) using Google Analytics.
  • Identification of radiology-related access records, browsing pages, and keywords.
  • Construction of three Bayesian network models for radiotherapy, nuclear medicine examination, and radiological diagnosis.

Main Results:

  • The radiotherapy model indicated 74% of visitors reached their target page, but only 2% accessed the central inspection information page.
  • Analysis revealed that linking radiotherapy and radiological diagnosis pages improves patient access to desired information.
  • Visitor behavior analysis identified barriers to accessing specific radiology information.

Conclusions:

  • A Bayesian network model was proposed to enhance patient web-browsing accessibility.
  • Further research is needed to validate the proposed model against alternatives.
  • Implementing these findings is expected to improve the quality of information on hospital websites.