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Published on: February 13, 2020
Clinical decision-making and dispensing performance in pharmacy students and its relationship to executive function
Greg Scutt1, Sian Williams1, Vivian Auyeung2
1Medicines Optimisation Research and Enterprise Group, School of Applied Sciences, University of Brighton, UK.
Background:
When providing pharmaceutical care, the pharmacist relies upon a clinical decision-making process that involves information gathering, clinical reasoning, and clinical judgment. Typically, pharmacists have to identify, retain and recall numerous pieces of key information arranged spatially in medical records and prescriptions or verbally from colleagues when making decisions. Executive function, including spatial working memory and verbal reasoning, along with other cognitive domains, will likely contribute to the elements that comprise this process.
Objective:
To establish the predictive utility of markers of executive function and implicit memory on clinical decision-making and dispensing performance in pharmacy students.
Methods:
MPharm students from two sites completed a battery of cognitive tasks designed to measure elements of executive and other cognitive functions (e.g., verbal working memory (VWM), visuospatial working memory (VSWM), and implicit memory (IM)). Performance on 2 clinical case studies was used to assess clinical decision-making ability (n = 16), and a prescription screening and dispensing assessment was used to assess dispensing accuracy (n = 32). A statistical model was built to establish whether executive and other cognitive functions markers can predict clinical decision-making and dispensing performance.
Results:
Performance in VSWM test and IM tests were found to explain approximately 63% of the deviance in clinical decision-making ability (null residual deviance = 49.4, deviance explained by variables = 31.0; Matrix Model p < 0.01, Dot-clearing test p < 0.01). Performance is the VSWM, and VWM tests explained approximately 30% of the deviance in the dispensing task (null residual deviance = 7596.7, deviance explained by variables = 2099.3; Matrix Model*Baddeley Reasoning Model, p < 0.05).
Conclusion:
The results suggest that specific cognitive domains contribute to the clinical decision-making process. This adds to a growing body of literature that highlights the importance of person-specific factors in predicting clinical competence.
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