Second Meeting of the Routine Data Section
Category: Routine data
A group has been formed to address the issues encountered by NIHR statisticians working on complex, routine datasets. We aim to provide a networking group for statistical researchers involved in the analysis of either established databases or routine data that has not been pre-processed.
Agenda
10.30-11.00 Registration and coffee
11.00 Introduction and welcome to the NIHR Statistics Group and the Routine Data Section (Routine Data Group Committee)
All the following talks are running with the format of 20 mins for a talk plus 10 mins for discussion.
11.10-11.40 GP consultations and code lists
John Edwards Arthritis Research UK Primary Care Centre, Keele University
Content: I aim to illustrate how an appointment with a GP turns into to coded information in the electronic health records.
Objectives:
- to map the range of processes involved in converting a consultation to a record, including the level of training they primary care clinicians are given, and the difficulties faced.
- give some real examples that illustrate how it works in practice, with different kinds of patients/conditions.
12.00-13.00 Primary care consultation databases
CPRD
Dan Dedman CPRD, MHRA (Slides)
Content: I will give a brief introduction on CPRD data, data access, and ISAC applications. I will talk some examples of common problems and issues in the ISAC applications. In addition, I will talk about challenges when requesting CPRD linkage data.
Daniel Prieto (Slides)
Content: I will give a brief introduction on the approach and strategy of the European Health Data & Evidence Network.
Objectives: From this, attendees will not only have an idea of primary care consultation databases for research, but also know process of obtaining data from two different data providers.
13.00-13.45 Lunch and networking
13.45-14.45 Experiences of coding/working with primary care consultation data
Antonella Delmestri CSM, NDORMS, University of Oxford (Slides)
Content: I will show the advantages of automation in big clinical data management, curation and extraction by using a DataBase Management System (e.g. MySQL) and a programming language (e.g. Python).
Rosa Parisi University of Manchester (Slides)
Content: I will demonstrate how a R package could manipulate and analyse electronic health record data (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0171784#sec015). During this session, you will find out how to use the package rEHR in order to extract ready-for analysis dataset, including creating a longitudinal cohort or perform matching. It could be centrally by a Data Manager, or with the use of existing programming package.
14.45-15.00 Coffee
15.00-15.30 Handling Missing data in the primary care consultation database
Irene Petersen University College London (Slides)
Content: I will discuss the scale of missing data in the primary care consultation database, and discuss typical approaches to handle missing data. I will also introduce the two-fold approach for multiple imputation for longitudinal electronic health record data.
Additional reference on missing data and multiple imputation and recording of primary care electronic health records in electronic health records.
Objectives: From this, attendees will have ideas of handling missing data in the primary care consultation data.
15.30-16.00 Jessica Harris, University of Bristol (Slides)
Content: I will present a CPRD/HES linked study and go through how I have used various codelists, to define exposures and outcomes.
16.00-16.30 breakout sessions
16.30 Close of meeting, followed by an optional social networking