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Using correspondence analysis in pharmacy practice
John F Inciardi1, Theo Stijnen, Kay McMahon
1Department of Pharmaceutical Services, University of California, Davis Medical Center, 2315 Stockton Boulevard, Sacramento, CA 95817, USA.
Summary
Correspondence analysis (CA) helps identify medication risks in elderly patients. This method links central nervous system agents to moderate-to-major falls, aiding pharmacy practice and patient care strategies.
Area of Science:
- Pharmacy Practice
- Data Analysis
- Geriatrics
Background:
- Falls are a significant concern for elderly individuals living at home.
- Medication use is a potential contributing factor to falls in this population.
- Existing data analysis methods may not effectively reveal complex associations between drug use and fall severity.
Purpose of the Study:
- To describe Correspondence Analysis (CA) and its application in pharmacy practice.
- To explore the association between medication use and the number/severity of falls in elderly patients.
- To demonstrate how CA can visualize multidimensional data in a reduced dimensional space.
Main Methods:
- Correspondence Analysis (CA), a multivariate graphical technique, was employed.
- Contingency tables of medication use and fall severity were analyzed.
- Row profiles were calculated using relative frequencies to represent data in a reduced dimensional plot.
Main Results:
- CA identified associations between specific drug classes and fall severity.
- Central nervous system (CNS) agents were linked to moderate to major falls.
- Psychotherapeutic agents were associated with moderate falls, and anticoagulants with moderate to minimum falls.
Conclusions:
- CA is a valuable tool for identifying patients at risk for drug-related complications.
- Pharmacists can use CA to allocate resources effectively and generate research hypotheses.
- This method facilitates the analysis of large datasets to uncover hidden associations and improve patient care strategies.