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Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial.

Jacopo Vanoli1,2, Consuelo Rubina Nava3, Chiara Airoldi4

  • 1London School of Hygiene and Tropical Medicine (LSHTM), London WC1E 7HT, UK.

International Journal of Environmental Research and Public Health
|December 24, 2021
PubMed
Summary
This summary is machine-generated.

State sequence analysis (SSA) offers a novel way to understand medication patterns in pharmacoepidemiology. This method reveals hidden prescription trends and predicts future treatment discontinuation, especially for opioid use in non-cancer pain patients.

Keywords:
data-miningpharmacoepidemiologystate-sequence analysis

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Area of Science:

  • Pharmacoepidemiology
  • Social Sciences
  • Data Science

Background:

  • State sequence analysis (SSA) is underutilized in pharmacoepidemiology despite its utility in social sciences.
  • SSA's visual nature aids in uncovering latent information within complex prescription data.
  • Identifying specific medication use patterns and potential misuse is crucial in pharmacoepidemiology.

Purpose of the Study:

  • To provide an educational primer on state sequence analysis (SSA) methods for pharmacoepidemiology.
  • To demonstrate the application of SSA in identifying patterns within real-world prescription data.
  • To explore the association between identified prescription patterns and future treatment outcomes.

Main Methods:

  • Measurement of dissimilarities between state sequences.
  • Application of clustering methods for sequence pattern identification.
  • Utilizing complexity measures and graphical visualization of sequences.
  • Incorporation of SSA into predictive models.

Main Results:

  • SSA successfully identified complex opioid prescription patterns in non-cancer pain patients that were not apparent with standard statistical methods.
  • These identified patterns were significantly associated with the future discontinuation of opioid therapy.
  • The study highlights SSA's capability to reveal nuanced information from real-world prescription data.

Conclusions:

  • State sequence analysis (SSA) is a valuable and accessible tool for pharmacoepidemiological research.
  • SSA facilitates the discovery of clinically relevant medication use patterns and aids in predicting treatment trajectories.
  • The application of SSA can enhance the understanding of medication adherence and effectiveness in real-world settings.