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Drug Therapy01:28

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Using Natural Language Processing and Network Analysis to Develop a Conceptual Framework for Medication Therapy

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This study developed a conceptual framework for medication therapy management (MTM) research by analyzing MTM in chronic disease care. Medication adherence and self-management interventions were key findings for the new model.

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Area of Science:

  • Health Services Research
  • Pharmacoeconomics
  • Clinical Pharmacy

Background:

  • Medication Therapy Management (MTM) is crucial for managing chronic diseases.
  • Existing conceptual frameworks may not fully capture the complexities of MTM research.
  • Developing a robust framework is essential for advancing MTM research and practice.

Purpose of the Study:

  • To derive and present a conceptual framework for medication therapy management (MTM) research.
  • To identify core concepts and their relationships within MTM for chronic disease care.
  • To provide a foundation for future MTM research and intervention development.

Main Methods:

  • A systematic review of abstracts on MTM in chronic disease care (2000-2016) was conducted.
  • Natural Language Processing (NLP) tool MetaMap was used for concept extraction.
  • Network graph analysis of concept co-occurrence was performed to build the framework.

Main Results:

  • Analysis of 142 abstracts revealed key concepts in MTM research.
  • Medication adherence was the most frequently studied problem, linked to self-management interventions.
  • The developed framework comprises 65 concepts organized into 14 constructs.

Conclusions:

  • A novel conceptual framework for MTM research has been established.
  • The framework highlights the importance of medication adherence and patient-centered interventions.
  • Further validation is needed to ensure the framework's applicability across diverse populations and settings.