Tracking family medicine graduates. Where do they go, what services do they provide and whom do they see?

<p>Abstract</p> <p>Background</p> <p>There are continued concerns over an adequate supply of family physicians (FPs) practicing in Canada. While most resource planning has focused on intake into postgraduate education, less information is available on what postgraduate medical training yields. We therefore undertook a study of Family Medicine (FM) graduates from the University of Toronto (U of T) to determine the type of information for physician resource planning that may come from tracking FM graduates using health administrative data. This study compared three cohorts of FM graduates over a 10 year period of time and it also compared FM graduates to all Ontario practicing FPs in 2005/06. The objectives for tracking the three cohorts of FM graduates were to: 1) describe where FM graduates practice in the province 2) examine the impact of a policy introduced to influence the distribution of new FM graduates in the province 3) describe the services provided by FM graduates and 4) compare workload measures. The objectives for the comparison of FM graduates to all practicing FPs in 2005/06 were to: 1) describe the patient population served by FM graduates, 2) compare workload of FM graduates to all practicing FPs.</p> <p>Methods</p> <p>The study cohort consisted of all U of T FM postgraduate trainees who started and completed their training between 1993 and 2003. This study was a descriptive record linkage study whereby postgraduate information for FM graduates was linked to provincial health administrative data. Comprehensiveness of care indicators and workload measures based on administrative data where determined for the study cohort.</p> <p>Results</p> <p>From 1993 to 2003 there were 857 University of Toronto FM graduates. While the majority of U of T FM graduates practice in Toronto or the surrounding Greater Toronto Area, there are FM graduates from U of T practicing in every region in Ontario, Canada. The proportion of FM graduates undertaking further emergency training had doubled from 3.6% to 7.8%. From 1993 to 2003, a higher proportion of the most recent FM graduates did hospital visits, emergency room care and a lower proportion undertook home visits. Male FM graduates appear to have had higher workloads compared with female FM graduates, though the difference between them was decreasing over time. A 1997 policy initiative to discount fees paid to new FPs practicing in areas deemed over supplied did result in a decrease in the proportion of FM graduates practicing in metropolitan areas.</p> <p>Conclusions</p> <p>We were able to profile the practices of FM graduates using existing and routinely collected population-based health administrative data. Further work tracking FM graduates could be helpful for physician resource forecasting and in examining the impact of policies on family medicine practice.</p

The devil is in the details: trends in avoidable hospitalization rates by geography in British Columbia, 1990–2000

BACKGROUND: Researchers and policy makers have focussed on the development of indicators to help monitor the success of regionalization, primary care reform and other health sector restructuring initiatives. Certain indicators are useful in examining issues of equity in service provision, especially among older populations, regardless of where they live. AHRs are used as an indicator of primary care system efficiency and thus reveal information about access to general practitioners. The purpose of this paper is to examine trends in avoidable hospitalization rates (AHRs) during a period of time characterized by several waves of health sector restructuring and regionalization in British Columbia. AHRs are examined in relation to non-avoidable and total hospitalization rates as well as by urban and rural geography across the province. METHODS: Analyses draw on linked administrative health data from the province of British Columbia for 1990 through 2000 for the population aged 50 and over. Joinpoint regression analyses and t-tests are used to detect and describe trends in the data. RESULTS: Generally speaking, non-avoidable hospitalizations constitute the vast majority of hospitalizations in a given year (i.e. around 95%) with AHRs constituting the remaining 5% of hospitalizations. Comparing rural areas and urban areas reveals that standardized rates of avoidable, non-avoidable and total hospitalizations are consistently higher in rural areas. Joinpoint regression results show significantly decreasing trends overall; lines are parallel in the case of avoidable hospitalizations, and lines are diverging for non-avoidable and total hospitalizations, with the gap between rural and urban areas being wider at the end of the time interval than at the beginning. CONCLUSION: These data suggest that access to effective primary care in rural communities remains problematic in BC given that rural areas did not make any gains in AHRs relative to urban areas under recent health sector restructuring initiatives. It remains important to continue to monitor the discrepancy between them as a reflection of inequity in service provision. In addition, it is important to consider alternative explanations for the observed trends paying particular attention to the needs of rural and urban populations and the factors influencing local service provision

Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model

BACKGROUND: E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. METHODS: We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. RESULTS: Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. CONCLUSION: This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings