ABSTRACT #9

Medical Statistics For Resident Physicians

Mantej Sehmbhi, Nadeem Bilani, Nirupama Krishnamurthi, Georgina Osorio

PURPOSE AND GOALS: Data analysis techniques, from basic statistical tests to advanced models, are essential tools for academic medicine. The interpretation of results from these analyses are also important for all clinicians in order to truly understand the evidence behind clinical decisions. We aimed to develop a medical statistics curriculum, which will augment the existing evidence-based medicine curriculum, to equip the physicians of the future with the skills to analyze and interpret data independently.

METHODS: The educational program will take the format of asynchronous learning. A curriculum covering data handling, cleaning, analysis and interpretation has been designed. Brief (5-10 minute) videos will be created to address the educational objectives for each curriculum domain. Each video will be complemented by an exercise worksheet allowing the learner to practice the techniques discussed in the videos. The educational program will be delivered in SPSS, SAS and R, allowing each learner to trial each of these three statistical languages/programs to determine which they are most comfortable using.

EVALUATION PLAN: A pre-intervention survey establishing learners’ understanding of statistical tests and level of proficiency in using statistical languages/software to perform their own analysis will be distributed. Following delivery of the curriculum, a post-intervention survey taken at 6 months following delivery will be distributed. Responses from the pre- and post-intervention surveys will be compared. As the program becomes established, a pre- and post- intervention assessment may also be incorporated.

SUMMARY OF RESULTS: The program is still in development. Results from a needs assessment reflect the unmet needs for medical statistics/data science teaching during residency training. Of 38 residents who completed the needs assessment survey, 32% reported difficulties completing a research project because of an inability to complete data analysis. There was a range of abilities in performing basic statistical tests: on a scale of 1 (no ability) to 5 (mastery), 29% of respondents reported 1/5 and 2/5 ability, 21% reported 3/5 ability, and 18% reported 4/5 ability. Approximately 90% of respondents scored their ability to perform more complex analyses (e.g. generalized linear models and survival analysis) as 3 or less. Respondents were broadly split regarding which statistical software/languages they would prefer the program to be delivered in, with R, SPSS and SAS being popular requests.

REFLECTIVE CRITIQUE: The program will address a significant need for practical teaching in medical statistics and data science for resident physicians. The asynchronous format will allow time-pressured residents to complete the program at their own pace, within the constraints of busy clinical schedules. Measuring the impact of the program presents challenges, particularly given the long gap between the acquisition of independent analysis skills and ‘hard’ end- points, such as successful publication or presentation of work at conferences.