What Statistics Do GPs Really Need To Know?
Thursday 01 July 2010, 1400-1700
Postgraduate Statistics Centre, Lecture Theatre (A54)
This meeting of The Royal Statistical Society Primary Health Care Study Group, will focus on the statistics needs of general practitioners.
Three talks will be followed by discussion in groups. All are welcome, no pre-registration is necessary.
Mark Shapley (Primary Care Sciences, Keele University & G.P.)
There has been very little published research on the statistical wants and needs of non-academic and academic general practitioners. Medical statisticians have a well recognised role in research design and analysis but should they have a greater role in general practitioner education and clinical practice, and an even greater role in primary care research? The talk will meander through the speaker's 20 year experience as a practising general practitioner and university academic.
Jenny Freeman (School of Health and Related Research, University of Sheffield)
Key to any educational development work is the question of what learners need to know. It is easy for statistical educators to feel they know what students need to know, but it is also clear that when teaching non-statisticians, these non-specialists, who will be expected to use statistics after graduation, will have a view on what they need to know. We surveyed both current medical students and practicing doctors about what they would like to know and how it should be delivered. This informed a new curriculum covering the topics found to be most important and lead to the development of a new mode of delivery, based around the problem-based learning model. The understanding produced provides valuable knowledge for both medical education and other disciplines where understanding statistics is essential.
Nigel Mathers (Academic Unit of Primary Care Medicine, University of Sheffield)
What do GPs need to know about statistics? The four statistical areas which help GPs to improve their clinical practice are: Predictive values (Bayes theorem), Regression to the mean, Dichotomous and continuous variables, Geoffrey Rose population strategy. These four areas will be discussed.