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Structured clinical reflection in acute toxicology: bridging guidelines and bedside decision-making
Nusret Uysal1, Aravindan Veiraiah2, Berna Terzioglu Bebitoglu1
1Department of Medical Pharmacology, Marmara University School of Medicine, Başıbüyük, Başıbüyük Yolu No: 9 D:2, 34854 Maltepe, Istanbul, Turkey.
Postgraduate Medical Journal
|July 17, 2026
Summary
Structured clinical reflection enhances acute toxicology decision-making by clarifying reasoning and promoting balanced judgments in uncertain situations. This approach aids in the appropriate application of guidelines for managing poisoning cases effectively.
Area of Science:
- Medical Toxicology
- Clinical Reasoning
- Medical Education
Background:
- Acute poisoning presents frequent emergency department challenges with diagnostic and therapeutic uncertainty.
- Evidence-based guidelines and decision-support tools offer a framework but require clinical interpretation.
- Clinical judgment is crucial for managing poisoning cases effectively.
Purpose of the Study:
- To explore the application of structured clinical reflection in acute toxicology.
- To examine the interaction of guideline-based knowledge with clinical judgment.
- To identify factors influencing decision-making in poisoning management.
Main Methods:
- A four-week clinical toxicology observership at the National Poisons Information Service.
- Application of Gibbs' reflective cycle framework to selected clinical encounters.
- Purposive case selection to illustrate key toxicology decision-making domains.
Main Results:
- Structured reflection facilitated examination of clinical reasoning processes in toxicology.
- Identified interplay between guidelines, physiological assessment, ethics, and cognitive factors.
- Highlighted importance of proportional decision-making and avoiding cognitive biases.
Conclusions:
- Structured clinical reflection makes implicit reasoning explicit in acute toxicology.
- The process supports balanced decision-making and appropriate guideline use.
- Enhances deliberate and proportionate decision-making under uncertainty.
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