Using routinely collected electronic health record data for health research

Module Aims:

This module aims to provide students with an overview of the use of routinely collected electronic health record data for health research. Students will be introduced to various sources of data, including electronic health records from primary care, secondary care and social care, data derived from Apps, the Internet and wearable devices, as well as data collected through disease registries and routine surveys. A number of statistical methods and techniques used to analyse electronic health records will be discussed through examples. Students will also be introduced to common data of each of the above-mentioned fields, such as Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES), so as to know the content of these datasets, the main challenges identified in research, and the pros and cons of their use. They will also be introduced to the reporting of studies using electronic health records and will gain experience in effective critical appraisal and evaluation of the quality of published work based on this data. Practical sessions using electronic health data will capture exercises in primary care, health economics and social care and will be used to apply the knowledge obtained by lectures onto example datasets.
 

Module Learning Outcomes:

By the end of the module students should be able to:
1. Be familiar with sources of electronic health records: records collected routinely from primary, secondary and social care settings, as well as from wearable devices, the Internet and Apps.
2. Understand the strengths and limitations of these data in health research
3. Be aware of key ethical issues pertaining to use of these data
4. Understand key elements of study design in relation to routinely collected electronic health records in health research
5. Be able to apply appropriate statistical methods for the analysis of these data in health research
6. Understand key methodological issues relevant to these data in health research (e.g. missing data, clinical coding, record linkage)
7. Be able to use and combine data from various sources and settings for research practice

 

Pre-requisites:

Principles of Epidemiology, Principles of Biostatistics, Applied Data Analysis

 

Teaching Strategy:

The course will be delivered using a combination of lectures, discussions around example research papers, and practical data analysis sessions. The latter will employ example data and will be performed in R.

Assessment:

Written exercises will be used to assess the level of knowledge acquired by this module. The assessment will be in line with the objectives of the module, and it will be a mix of practical and theoretical questions discussed during the module. The assessment will be submitted one week after the end of the module.

Module Length: 4 days