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Identification of documented medication non-adherence in physician notes
Alexander Turchin1, Holly I Wheeler, Matthew Labreche
1Clinical Informatics Research and Development, Partners HealthCare, Boston, MA USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|November 13, 2008
Summary
Physicians
Area of Science:
- Medical Informatics
- Clinical Research
Background:
- Medication non-adherence is prevalent and impacts clinical decisions.
- Physician awareness of non-adherence is crucial but data is limited.
Purpose of the Study:
- To develop and validate an algorithm for detecting medication non-adherence documentation in physician notes.
- To assess the relationship between documented non-adherence and patient blood pressure control.
Main Methods:
- An algorithm was created to identify eight semantic classes of medication non-adherence in clinical notes.
- The algorithm was evaluated against manual ratings on 200 hypertensive patient records.
- Performance metrics included detection rate, specificity, and positive predictive value.
Main Results:
- The algorithm achieved an 89% detection rate for documented medication non-adherence.
- Specificity was 84.7% and positive predictive value was 80.2%.
- In 1,000 documents, non-adherence documentation correlated with significantly elevated systolic and diastolic blood pressure.
Conclusions:
- A novel, clinically validated algorithm effectively identifies medication non-adherence in physician notes.
- This tool enhances data availability for researchers studying medication non-adherence.
- Documented non-adherence is linked to poorer blood pressure control in hypertensive patients.
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