Objective: To increase gender diversity among the physician consulting staff (PCS) at a major medical center. Design: Because the proportion of female PCS at academic medical centers in the United States has not increased commensurately with increases in the proportion of female graduates from American medical schools, a modeling and graphing technique was developed to analyze this problem and recommend solutions for one large academic medical center. Material and Methods: Personnel data, by gender and year from 1980 through 1994, were collected for all PCS at Mayo Clinic Rochester (MCR). These data were compared with similar data from other US academic medical centers and were used to develop models to predict the proportion of female PCS at MCR yearly until 2005, assuming various hiring and resignation patterns. Novel techniques were developed to illustrate and compare the models. Model-based predictions were compared with national projections, and a realistic target proportion of female PCS was defined on the basis of assumptions about the proportion of female graduates from medical school and internship programs during the next 10 years as well as probable hiring, retention, and resignation rates at MCR. To identify issues critical to recruitment, retention, and professional growth of female PCS at MCR, we used factor analysis to assess responses to a confidential questionnaire sent to all female faculty members. Results: In 1994 and 1995, the proportion of female PCS was 25% at US academic medical centers but only 15% at MCR, and the rate at which this proportion increased from 1980 through 1994 at MCR was also lower than the national rate. Model-based predictions demonstrated that gradually (1.5% per year) increasing the female percentage of new recruits from 26% in 1995 to 40% in 2005 would achieve the targeted 25% female PCS in 13 years. Questionnaire responses from 119 (68%) of the 175 female PCS at MCR identified 6 important recommendations for recruitment and retention of female PCS: survey resignees and candidates who decline positions; appoint more qualified women to policy-making committees; require sensitivity and diversity training for all staff (especially leaders); develop explicit, gender-sensitive criteria for selecting department and division chairs; compare Mayo gender and diversity data with national data at the department or division level; and develop mechanisms for mentoring junior female staff members. Conclusion: We developed useful methods for analyzing the PCS gender distribution, defined feasible hiring strategies, and identified specific recommendations to enhance the professional experience of female PCS. These methods can provide a model for other institutions seeking to optimize gender diversity among their staff.
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