Advancing interprofessional education through the use of high fidelity human patient simulators

Background: Modern medical care increasingly requires coordinated teamwork and communication between healthcare professionals of different disciplines. Unfortunately, healthcare professional students are rarely afforded the opportunity to learn effective methods of interprofessional (IP) communication and teamwork strategies during their education. The question of how to best incorporate IP interactions in the curricula of the schools of health professions remains unanswered.Objective: We aim to solve the lack of IP education in the pharmacy curricula through the use of high fidelity simulation (HFS) to allow teams of medical, pharmacy, nursing, physician assistant, and social work students to work together in a controlled environment to solve cases of complex medical and social issues.Methods: Once weekly for a 4-week time period, students worked together to complete complex simulation scenarios in small IP teams consisting of pharmacy, medical, nursing, social work, and physician assistant students. Student perception of the use of HFS was evaluated by a survey given at the conclusion of the HFS sessions. Team communication was evaluated through the use of Communication and Teamwork Skills (CATS) Assessment by 2 independent evaluators external to the project.Results: The CATS scores improved from the HFS sessions 1 to 2 (p = 0.01), 2 to 3 (p = 0.035), and overall from 1 to 4 (p = 0.001). The inter-rater reliability between evaluators was high (0.85, 95% CI 0.71, 0.99). Students perceived the HFS improved: their ability to communicate with other professionals (median =4); confidence in patient care in an IP team (median=4). It also stimulated student interest in IP work (median=4.5), and was an efficient use of student time (median=4.5)Conclusion: The use of HFS improved student teamwork and communication and was an accepted teaching modality. This method of exposing students of the health sciences to IP care should be incorporated throughout the curricula

Validation of a transparent decision model to rate drug interactions

BACKGROUND: Multiple databases provide ratings of drug-drug interactions. The ratings are often based on different criteria and lack background information on the decision making process. User acceptance of rating systems could be improved by providing a transparent decision path for each category. METHODS: We rated 200 randomly selected potential drug-drug interactions by a transparent decision model developed by our team. The cases were generated from ward round observations and physicians' queries from an outpatient setting. We compared our ratings to those assigned by a senior clinical pharmacologist and by a standard interaction database, and thus validated the model. RESULTS: The decision model rated consistently with the standard database and the pharmacologist in 94 and 156 cases, respectively. In two cases the model decision required correction. Following removal of systematic model construction differences, the DM was fully consistent with other rating systems. CONCLUSION: The decision model reproducibly rates interactions and elucidates systematic differences. We propose to supply validated decision paths alongside the interaction rating to improve comprehensibility and to enable physicians to interpret the ratings in a clinical context