Advanced Analysis of Linked Health Data

Advanced Analysis of Linked Health Data is an intensive course of five days in duration, designed to instruct participants in the theory and practice of analysis of large sets of linked health data at an intermediate to advanced level. Advanced principles of health care epidemiology are combined with hands-on practical exercises in the implementation of computing solutions.

Application is now open for the course 3 April - 7 April 2017.

The modular structure of the unit provides students with a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding technological computing solutions. Students use fictitious but realistic linked data files in the hands-on exercises. One-on-one coaching and instruction is available in the computing laboratory session each afternoon on how to problem-solve complex research scenarios covered by the hands-on exercises.

Course Outline

The course caters to users of SPSS, SAS or Stata with course materials and exercises covering all three statistical software packages. Advanced principles of health and social epidemiology are combined with hands-on practical exercises in the implementation of computing solutions for managing and analysing a range of complex linked data sets.

Professor David Preen provides students with a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding technological computing solutions. Students use multiple fictitious but realistically modelled linked data files in the hands-on exercises. The course will also include a series of guest presentations throughout the five days. Professors Preen, along with additional lab demonstrators, will be available in the computing laboratory session each afternoon and conduct one-on-one coaching for those who need assistance.

Who Should Attend

This course is ideal for health and social care researchers, social scientists, clinical practitioners and health care managers who wish to build on their pre-existing theoretical knowledge and skills in the analysis of linked health data.

Learning Objectives

The course practice data sets provide health and social researchers with the opportunity to build on their pre-existing theoretical knowledge and skills in the analysis of linked data by exploring a number of advanced topics.

Upon completion the participant will:

  • have consolidated their grasp of foundation concepts of epidemiology and linked data analysis;

  • possess an advanced understanding of methods for the conceptualisation and construction of valid measures and effect measures of health and social services utilisation and outcomes based on complex, multi-sourced linked data sets;

  • understand complex longitudinal research designs and how to implement them using large multi-sourced linked data sets;

  • understand advanced ‘modern epidemiology’ theoretical principles including case-distribution study designs and how to practically implement them using large multi-sourced linked data sets;

  • have skills in the analysis of linked hospital morbidity, mortality, institutional, pharmaceutical and primary care data; and

  • be able to write computing syntax to prepare complex linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators and produce results from advanced statistical procedures.

Course Prerequisites

The course assumes that participants have completed Introductory Analysis of Linked Health Data or have equivalent knowledge arising from hands-on experience in the analysis of linked files with multiple and variable numbers of records per individual. The computing component of the unit assumes a facile competence in the preparation of computing syntax for either SPSS, SAS or Stata and familiarity with the statistical analysis of linked data files at an introductory to intermediate level.

It is recommend that participants who have not previously completed an introductory course in epidemiology, familiarise themselves with the basic principles and terms used in that discipline. A working knowledge of statistical concepts, including regression models, used in data analysis in the medical and social sciences is also assumed.

Course Credits

The Advanced Analysis of Linked Health Data Course is part of the MSc Health Data Science module (PMIM602) which carries 20 Masters Level Credits and these are awarded on completion of a successful assignment. 

However, students who wish to attend for Continuing Professional Development (CPD) purposes only, will omit the assessment and be given a Certificate of Attendance.

Course Fees

Commercial: £1800.00 per delegate

Non-commercial: £1500.00 per delegate

Full-time PhD student unwaged: £750.00 per delegate

(International students please enquire for further details of course fees)

Fees include course materials.

Application

Applications are now open for the course 3 April - 7 April 2017.

To apply please click here.

Please note that application forms received after the closing date will incur a £50 late booking fee.

 

The training courses are delivered in collaboration with

     The Centre for Health Services Research at

The University of Western Australia

Contact Us

Course Enquiries:
Athanasios Anastasiou
Course Lecturer, Health Data Science

Marketing Enquiries:
Stephanie Lee

Data Science Building, Swansea University Medical School, Singleton Park, SWANSEA SA2 8PP, Wales, UK

+44 (0)1792 606292