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Understanding Collaborative CT and MRI Utilization Through Network Analysis: Retrospective Study Using Administrative

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Area of Science:

  • Health Services Research
  • Medical Imaging Informatics
  • Network Science Applications in Healthcare

Background:

  • Japan faces challenges in efficient allocation of advanced diagnostic imaging resources like computed tomography (CT) and magnetic resonance imaging (MRI) due to high scanner density.
  • Demographic shifts and regional healthcare disparities exacerbate the need for optimized resource utilization in medical imaging services.

Purpose of the Study:

  • To develop and apply an analytic framework utilizing network analysis techniques.
  • To understand the collaborative utilization patterns of CT and MRI scanners across healthcare facilities within a Japanese prefecture.
  • To inform strategies for efficient resource allocation of diagnostic imaging equipment.

Main Methods:

  • A retrospective observational study analyzed outpatient receipt data from National Health Insurance and Late-Stage Elderly Medical System (2016-2019).
  • Network analysis, including graph visualization with community detection, was employed to map interinstitutional sharing of CT and MRI devices.
  • Metrics such as network density and reciprocity were calculated to quantify the extent and nature of collaboration.

Main Results:

  • Both CT and MRI examinations saw an increase in volume from 2016 to 2019, with collaborative use also rising.
  • Network density for CT and MRI remained stable, but reciprocity significantly decreased, indicating a trend towards less mutual sharing.
  • Community detection revealed dynamic shifts in the clustering of medical institutions over the study period.

Conclusions:

  • Network analysis identified evolving collaborative patterns in CT and MRI usage, characterized by declining reciprocity and potentially more unidirectional referrals.
  • The developed analytic framework offers a valuable tool for healthcare planners to assess interinstitutional cooperation for diagnostic imaging equipment.
  • Findings support informed decision-making for resource allocation strategies concerning shared medical imaging technologies.