BACKGROUND: Modern approaches to clinical evaluation emphasize the value of learner-driven feedback models, where trainees are encouraged to take an active role in the initiation of the evaluation process. In an effort to empower medical students to request evaluations on performance, our medical school developed a web-based application for mobile devices that prompts learners to solicit feedback electronically following a clinical encounter. In 2016, mandatory implementation of this application resulted in a transition from an educator-driven feedback model to a learner-driven feedback model. We aimed to investigate the impact of this innovative system on both the quality and quantity of feedback provided to medical students on their anesthesiology elective. METHODS: We retrospectively analyzed medical students' feedback data from the sequential academic years prior to and after the implementation of our learner-driven feedback application. Quantitative analysis was performed to compare the frequency of evaluations requested and completed. Free-text commentary was analyzed using conventional qualitative content analysis. Comments were categorized by quality and representative themes based upon Accreditation Council for Graduate Medical Education Core Competency domains. RESULTS: A total of 297 evaluations for 72 students were analyzed. Students in the learner-driven model requested feedback more frequently than the previously educator-driven system (13.4 vs 8.9 requests per student, P < .0001). Additionally, a greater proportion of assessments were completed by evaluators when solicited from the learner-driven model (42% vs 34%, P = .0265). The quality of comments solicited from the learner-driven model were of higher quality when addressing students' strengths (71% vs 30%, P < .00001) and of lower quality when addressing areas of improvement (73% vs 59%, P = .0378). Comments from the learner-driven model were more likely to address Patient Care (48% vs 24%, P < .00001) and less likely to address Interpersonal and Clinical Communication (17% vs 28%, P = .0037) compared to the educator-driven model. CONCLUSIONS: A learner-driven feedback model was successful in improving the quantity of both requested and completed evaluations for students. The quality of feedback was also improved when addressing students' strengths.
BACKGROUND: Modern approaches to clinical evaluation emphasize the value of learner-driven feedback models, where trainees are encouraged to take an active role in the initiation of the evaluation process. In an effort to empower medical students to request evaluations on performance, our medical school developed a web-based application for mobile devices that prompts learners to solicit feedback electronically following a clinical encounter. In 2016, mandatory implementation of this application resulted in a transition from an educator-driven feedback model to a learner-driven feedback model. We aimed to investigate the impact of this innovative system on both the quality and quantity of feedback provided to medical students on their anesthesiology elective. METHODS: We retrospectively analyzed medical students' feedback data from the sequential academic years prior to and after the implementation of our learner-driven feedback application. Quantitative analysis was performed to compare the frequency of evaluations requested and completed. Free-text commentary was analyzed using conventional qualitative content analysis. Comments were categorized by quality and representative themes based upon Accreditation Council for Graduate Medical Education Core Competency domains. RESULTS: A total of 297 evaluations for 72 students were analyzed. Students in the learner-driven model requested feedback more frequently than the previously educator-driven system (13.4 vs 8.9 requests per student, P < .0001). Additionally, a greater proportion of assessments were completed by evaluators when solicited from the learner-driven model (42% vs 34%, P = .0265). The quality of comments solicited from the learner-driven model were of higher quality when addressing students' strengths (71% vs 30%, P < .00001) and of lower quality when addressing areas of improvement (73% vs 59%, P = .0378). Comments from the learner-driven model were more likely to address Patient Care (48% vs 24%, P < .00001) and less likely to address Interpersonal and Clinical Communication (17% vs 28%, P = .0037) compared to the educator-driven model. CONCLUSIONS: A learner-driven feedback model was successful in improving the quantity of both requested and completed evaluations for students. The quality of feedback was also improved when addressing students' strengths.
Authors: David A Rogers; Margaret L Boehler; Cathy J Schwind; Andreas H Meier; Jarrod C H Wall; Michael J Brenner Journal: Am J Surg Date: 2011-11-08 Impact factor: 2.565
Authors: Pedro Tanaka; Sylvia Bereknyei Merrell; Kim Walker; Jennifer Zocca; Lena Scotto; Alyssa L Bogetz; Alex Macario Journal: Anesth Analg Date: 2017-02 Impact factor: 5.108
Authors: Paul A Harris; Robert Taylor; Brenda L Minor; Veida Elliott; Michelle Fernandez; Lindsay O'Neal; Laura McLeod; Giovanni Delacqua; Francesco Delacqua; Jacqueline Kirby; Stephany N Duda Journal: J Biomed Inform Date: 2019-05-09 Impact factor: 6.317