Big Data Epidemiology

Overview

Design, conduct and interpret epidemiological studies in large routine healthcare databases

This module introduces the particular challenges and opportunities of epidemiology in large routine health care databases, such as the Clinical Practice Research Datalink.  Lectures and practical sessions will cover protocols and approvals, data management and longitudinal analysis, and interpretation of findings.  Students will explore and analyse data using Stata software.  Special topics include sample size considerations in very large databases, a view from the protocol reviewers’ perspective and an introduction to specialist study designs. Participants will apply their new knowledge and skills to a large database research project and produce a study protocol.

Tutors include Professor Richard Stevens, Chair of one of the CPRD's Research and Data Governance (RDG) Expert Review Committees (ERC) and member of the Central Advisory Committee (CAC), and Professor Clare Bankhead, Head of the Nuffield Department of Primary Care Health Sciences CPRD Group, who host the University’s access to CPRD.   Module coordinators Dr Emily McFadden and Dr Margaret Smith both have extensive experience in the use of routine healthcare data for research.  Emily is a Department Lecturer and senior statistical epidemiologist within the Centre for Evidence-Based Medicine, Chair of one of the CPRD's Expert Review Committees and a member of the Central Advisory Committee.  Margaret is a senior statistician and epidemiologist within Oxford’s CPRD research group.  Both are members of (different!) CPRD RDG Expert Review Committees.

The last date for receipt of complete applications is 5pm Friday 20th December 2024. Regrettably, late applications cannot be accepted.

Aims of the module

This module aims to provide competence in the design, execution and interpretation of analyses of large databases of routinely collected data, such as the Clinical Practice Research Datalink (CPRD).

Previous statistical experience including the following is a pre-requisite for this module:

  • Statistical concepts – p-values, confidence intervals, standard error
  • Multivariate linear, logistic and Cox regression
  • Competence in statistical software including Stata

Applicants must provide information on their statistical experience in the personal statement section of the application form. Students who have taken the module Essential Medical Statistics will meet these requirements.

Key learning outcomes:

  • Gain knowledge of examples of large routine healthcare databases in the UK that are available for epidemiological research.
  • Understand the types of epidemiological questions and study designs where routinely collected data may be of use.
  • Understand and gain experience, using Stata software, of key practical components involved in designing research in a database, with focus on the CPRD:
    - Identify different populations for analysis and understand which are appropriate to address specific research questions
    - Identify recorded demographic, clinical history and prescribing data and understand their potential limitations
    - Gain specific skills in Stata for data extraction and analysis
     
  • Gain familiarity of potential data linkages, and their advantages and disadvantages.  Gain awareness of data security issues.
     
  • Understand relevant methodological issues and possible solutions in routinely collected healthcare data, including: measurement error, missing data, addressing confounding, multiple testing and sample size calculations.
  • Gain awareness of specialist design and analytical methods relevant to routinely collected data.
  • Understand the strengths and weaknesses of routinely collected data and use this knowledge to interpret and critically appraise study findings.
  • Gain the ability to plan a research protocol to answer questions in evidence based healthcare using routinely collected data.

Programme details

This module is run over an eight week cycle where the first week is spent working on introductory activities using a Virtual Learning Environment, the second week is a full week of online teaching (this takes place on the dates advertised), there are then four Post-Oxford activities (delivered through the VLE) which are designed to help you write your assignment. You then have a week of personal study and you will be required to submit your assignment electronically the following week (usually on a Tuesday at 14:00 UK Local Time).

Fees

Description Costs
Short Course in Health Sciences £3175.00
Students enrolled on MSc in Evidence-Based Health Care £2570.00

Funding

Details of funding opportunities, including grants, bursaries, loans, scholarships and benefit information are available on our financial assistance page.

Discounts

If you are an employee of the University of Oxford and have a valid University staff card you may be eligible to receive a 10% discount on the full stand-alone fee. To take advantage of this offer please submit a scan/photocopy of your staff card along with your application. Your card should be valid for a further six months after attending the course.

Tutors

Dr Emily McFadden

Module Coordinator

Dr Emily McFadden is a Departmental Lecturer and Senior Statistical Epidemiologist at the Nuffield Dept of Primary Care Health Sciences, University of Oxford.

Dr Margaret Smith

Deputy Module Coordinaor

Dr Margaret Smith is a Senior Statistician and Epidemiologist at the Nuffield Dept of Primary Care Health Sciences, University of Oxford, and the Deputy Course Director of the MSc in EBHC (Medical Statistics).

Assessment methods

Assessment will be based on submission of a written assignment which should not exceed 4,000 words.

Academic Credit

Applicants may take this course for academic credit. The University of Oxford Department for Continuing Education offers Credit Accumulation and Transfer Scheme (CATS) points for this course. Participants attending at least 80% of the taught course and successfully completing assessed assignments are eligible to earn credit equivalent to 20 CATS points which may be counted towards a postgraduate qualification.

Applicants can choose not to take the course for academic credit and will therefore not be eligible to undertake the academic assignment offered to students taking the course for credit. Applicants cannot receive CATS (Credit Accumulation and Transfer Scheme) points or equivalence. Credit cannot be attributed retrospectively. CATS accreditation is required if you wish for the course to count towards a further qualification in the future.

A Certificate of Completion is issued at the end of the course.

Applicants registered to attend ‘not for credit’ who subsequently wish to register for academic credit and complete the assignment are required to submit additional information, which must be received one calendar month in advance of the course start date. Please contact us for more details.

Please contact cpdhealth@conted.ox.ac.uk if you have any questions.

Application

This course requires you to complete the application form and to attach a copy of your CV. If you are applying to take this course for academic credit you will also be required to provide a reference. Please note that if you are not applying to take the course for academic credit then you do not need to submit a reference.

Please ensure you read the guidance notes which appear when you click on the symbols as you progress through the application form, as any errors resulting from failure to do so may delay your application.

Selection criteria

Admissions Criteria:
To apply for the course you should:

  • Show evidence of your previous statistical knowledge
  • Be a graduate or have successfully completed a professional training course
  • Have professional work experience in the health service or a health-related field
  • Be able to combine intensive classroom learning with the application of the principles and practices of evidence-based health care within the work place
  • Have a good working knowledge of email, internet, word processing and Windows applications (for communications with course members, course team and administration)
  • Show evidence of the ability to commit time to study and an employer's commitment to make time available to study, complete course work and attend course and university events and modules.
  • Be able to demonstrate English Language proficiency at the University’s higher level

IT requirements

Please ensure that you have access to a computer that meets the specifications detailed on our technical support page.