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Methods of Documentation VI: Case Management Model01:15

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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
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Related Experiment Video

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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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Exploring Multimorbidity Patterns in older hospitalized Norwegian patients using Network Analysis modularity.

Mohsen Askar1, Beate Hennie Garcia1, Kristian Svendsen1

  • 1Department of Pharmacy, Faculty of Health Sciences, UiT, The Arctic University of Norway, Norway.

International Journal of Medical Informatics
|April 29, 2025
PubMed
Summary

Network analysis reveals complex multimorbidity patterns (MPs) in older hospitalized patients. Identifying these condition clusters aids healthcare planning and improves patient outcomes by understanding disease interactions.

Keywords:
Chronic conditionsCommunity detectionComorbidityDisease patternsModularityMultimorbidityNetwork analysis

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Area of Science:

  • Gerontology
  • Network Science
  • Public Health

Background:

  • Understanding multimorbidity patterns (MPs) is essential for effective healthcare planning and resource allocation.
  • Identifying these patterns can significantly improve patient outcomes.

Purpose of the Study:

  • To demonstrate the application of Network Analysis (NA) for exploring multimorbidity patterns in hospitalized elderly Norwegian patients.
  • To identify and interpret clusters of co-occurring chronic conditions.

Main Methods:

  • Utilized data from the Norwegian Patient Registry (2017-2019) for patients aged 65+ with multiple chronic conditions.
  • Defined multimorbidity and identified chronic conditions using the Chronic Condition Indicator Refined (CCIR) list.
  • Employed Relative Risk and Phi-correlation to assess condition associations, constructing a multimorbidity network analyzed with Louvain community detection.

Main Results:

  • A network of 539 chronic conditions revealed distinct multimorbidity patterns, including cardiorenal, metabolic-cardiovascular, and respiratory disorders.
  • Identified influential conditions within each pattern using network centrality measures.
  • Developed interactive network and sunburst graphs for public access to visualize these patterns.

Conclusions:

  • Network analysis and modularity detection effectively identify multimorbidity patterns in older adults.
  • The study underscores the complex interplay of chronic conditions in the elderly.
  • NA methodology offers a powerful approach to exploring these intricate disease relationships.