Promoting faculty professionalism: a case-based approach.

INTRODUCTION: Professionalism is a key attribute for health professionals. Yet, it is unknown how much faculty development is directed toward skills and behaviours of faculty professionalism. Faculty professionalism includes boundaries in teacher-student relationships, self-reflection, assuring one's own fitness for duty, and maintaining confidentiality when appropriate. METHODS: For five years, we have incorporated faculty professionalism as a routine agenda item for the monthly Physician Assistant Programme faculty meetings, allowing faculty members to introduce issues they are comfortable sharing or have questions about. We also have case discussions of faculty professionalism within faculty meetings every three months. RESULTS: Faculty professionalism is important in the daily work lives of faculty members and including this as part of routine agendas verifies its importance. A faculty survey showed that a majority look forward to the quarterly faculty professionalism case discussions. These have included attempted influence in the admissions process, student/faculty social boundaries, civic professionalism, students requesting medical advice, and self-disclosure. CONCLUSION: A preventive approach works better than a reactionary approach to faculty missteps in professionalism. Routine discussion of faculty professionalism normalizes the topic and is helpful to both new and experienced faculty members. We recommend incorporation of faculty professionalism as a regular agenda item in faculty meetings.

Knowledge-based IMRT treatment planning for prostate cancer.

PURPOSE: To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan. METHODS: A database of 100 prostate IMRT treatment plans was assembled into an information-theoretic system. An algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases were each matched with the most similar case from the database of prior clinically approved plans. Treatment parameters from the matched case were used to develop new treatment plans. A comparison of the differences in the dose-volume histograms between the new and the original treatment plans were analyzed. RESULTS: On average, the new knowledge-based plan is capable of achieving very comparable planning target volume coverage as the original plan, to within 2% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum and dose to the bladder are also comparable to the original plan. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are 1.8% +/- 8.5%, -2.5% +/- 13.9%, and -13.9% +/- 23.6%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -5.9% +/- 10.8%, -12.2% +/- 14.6%, and -24.9% +/- 21.2%, respectively. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan. CONCLUSIONS: The authors demonstrate a knowledge-based approach of using prior clinically approved treatment plans to generate clinically acceptable treatment plans of high quality. This semiautomated approach has the potential to improve the efficiency of the treatment planning process while ensuring that high quality plans are developed.