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Published on: December 1, 2020
Understanding pharmacist decision making for adverse drug event (ADE) detection
Shobha Phansalkar1, Jennifer M Hoffman, John F Hurdle
1Brigham and Women's Hospital, Boston, MA, USA. sphansalkar@partners.org
Pharmacists use forward reasoning to detect adverse drug events (ADEs), but often lack sufficient information. Developing better alerting systems can improve ADE detection and patient safety.
Area of Science:
- Pharmacology
- Health Informatics
- Clinical Pharmacy
Background:
- Manual chart review for adverse drug event (ADE) detection is effective but costly.
- Expert systems can improve efficiency and reduce costs by mimicking human decision-making.
- This study investigates pharmacist decision-making for ADE detection as a foundational step.
Purpose of the Study:
- To explore pharmacist decision-making processes in adverse drug event detection.
- To identify information signals and unmet information needs during ADE detection.
- To inform the development of expert systems for improved ADE detection.
Main Methods:
- Think-aloud procedures were employed with pharmacists reviewing ADE case scenarios.
- Verbal protocols were qualitatively analyzed to extract decision-making strategies and information needs.
- Inter-reviewer agreement for classifying ADE information signals was assessed using Cohen's kappa.
Main Results:
- 110 information signals were extracted; 73% were interpreted from the scenario, and 53% were relevant for ADE detection.
- Excellent inter-reviewer reliability was achieved in classifying signals.
- Fifty information signals related to unmet information needs were identified and themed.
Conclusions:
- Pharmacists utilize forward reasoning for hypothesis validation in ADE detection.
- Frequent unmet information needs were identified, highlighting areas for system improvement.
- Developing targeted alerting systems can enhance pharmacists' ability to reduce preventable ADEs and improve patient safety.
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