Reliability of clinical impact grading by healthcare professionals of common prescribing error and optimisation cases in critical care patients. (31st January 2017) - Bourne, Richard S.; Shulman, Rob; Tomlin, Mark; Borthwick, Mark; Berry, Will; Mills, Gary H.
Abstract: Objective: To identify between and within profession-rater reliability of clinical impact grading for common critical care prescribing error and optimisation cases. To identify representative clinical impact grades for each individual case. Design: Electronic questionnaire. Setting: 5 UK NHS Trusts. Participants: 30 Critical care healthcare professionals (doctors, pharmacists and nurses). Intervention: Participants graded severity of clinical impact (5-point categorical scale) of 50 error and 55 optimisation cases. Main Outcome Measures: Case between and within profession-rater reliability and modal clinical impact grading. Methods: Between and within profession rater reliability analysis used linear mixed model and intraclass correlation, respectively. Results: The majority of error and optimisation cases (both 76%) had a modal clinical severity grade of moderate or higher. Error cases: doctors graded clinical impact significantly lower than pharmacists (−0.25; P < 0.001) and nurses (−0.53; P < 0.001), with nurses significantly higher than pharmacists (0.28; P < 0.001). Optimisation cases: doctors graded clinical impact significantly lower than nurses and pharmacists (−0.39 and −0.5; P < 0.001, respectively). Within profession reliability grading was excellent for pharmacists (0.88 and 0.89; P < 0.001) and doctors (0.79 and 0.83; P < 0.001) but only fair to good for nurses (0.43 and 0.74; P < 0.001), for optimisation and error cases, respectively. Conclusions: Representative clinical impact grades for over 100 common prescribing error and optimisation cases are reported for potential clinical practice and research application. The between professional variability highlights the importance of multidisciplinary perspectives in assessment of medication error and optimisation cases in clinical practice and research.