Evidence Based Health Care (Medical Statistics) MSc
Course Overview - Evidence Based Health Care (Medical Statistics) MSc
The information provided on this page was correct at the time of publication (November 2025). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.
The MSc in Evidence-Based Health Care (Medical Statistics) is a part-time taught course for health professionals, focusing on statistical methods, clinical trials, meta-analysis, and big data to support evidence-based decision-making.
The course is designed for doctors, nurses, pharmacists, midwives and othe...
<strong>The information provided on this page was correct at the time of publication (November 2025). For complete and up-to-date information about this course, please visit the relevant University of Oxford course page via www.graduate.ox.ac.uk/ucas.</strong> <br/><br/>The MSc in Evidence-Based Health Care (Medical Statistics) is a part-time taught course for health professionals, focusing on statistical methods, clinical trials, meta-analysis, and big data to support evidence-based decision-making.<br/><br/>The course is designed for doctors, nurses, pharmacists, midwives and other healthcare professionals, seeking to consolidate their understanding and ability in medical statistics. Core modules introduce the students to methods for observational and clinical trials research. Optional modules offer the students skills in growth areas such as systematic review, meta-analysis, and big data epidemiology, or specialist areas such as statistical computing, diagnosis and screening research and others.<br/><br/>The course aims to give students high competence in the concepts, methods, terminology and interpretation of medical statistics; and hence, enhance their ability to carry out their own research and to interpret published evidence.<br/><br/>Students should gain:<br/><br/><br/>- competence in execution and interpretation of core statistical techniques used by medical statisticians, particularly those used in multivariable analyses: multiple linear regression, logistic regression, and survival modelling, statistical analysis plans and statistical reporting<br/><br/><br/>- competence in execution and interpretation of core statistical techniques used by medical statisticians in clinical trials<br/><br/><br/>- competence in execution and interpretation of four other areas, selected by the student from the following options: clinical prediction rules; meta-analysis; systematic reviews or complex reviews; big data epidemiology; statistical computing; diagnosis and screening; study design and research methods<br/><br/><br/>- hands-on experience, supervised by a senior member of our medical statistics team, of the analysis or meta-analysis of healthcare data, in order to address a question in evidence-based health care.<br/><br/><br/>Compared to the main EBHC course, MSc in Evidence-Based Health Care, this will suit those with basic statistical understanding who now seek deeper understanding on a broader base of statistical methods.<br/><br/>The MSc is a joint course offered between the Nuffield Department of Primary Care Health Sciences and the Department for Continuing Education. The course works in collaboration with the renowned Centre for Evidence-Based Medicine in Oxford.<br/><br/>This course has teachers and contributors who are internationally recognised leaders in the field of evidence-based practice and teaching. The flexible structure of the course has been devised to fit with the structure of specialist training and to accommodate student choice.<br/><br/>Teaching is tailored to non-statisticians and delivered by an experienced team of tutors from University of Oxford who bridge the disciplines of medical statistics and evidence-based healthcare.
Course Information
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Course Details
Information
Study Mode
Part-time
Duration
3 Years
Start Date
10/2026
Campus
University of Oxford
Application Details
Varied
Application deadline
Provider Details
Codes/info
Course Code
Unknown
Institution Code
O33
Points of Entry
Unknown
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