Introduction to ECHILD: Linked data from health, education and children’s social care

Description:

This short course is designed to give participants a practical introduction to ECHILD (Educational and Child Health Insights from Linked Data). ECHILD is a collection of linked, longitudinal administrative datasets covering health, education and children’s social care. More information about the ECHILD, and resources for researchers and the public can be found on the ECHILD website. 

The course is aimed at both analysts intending to use ECHILD and researchers who want to understand more about how the data can be used for policy relevant research. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice.   

Day 1 will provide information on the strengths and limitations of the different component datasets of ECHILD, through case studies of the National Pupil Database, Hospital Episode Statistics, Maternity Services Data, Mental Health Services Data, and the Community Services Dataset. Interactive lectures / tutorials will teach participants how to design a research study to answer a specific research question in ECHILD, focusing on the power and complexity of working with linked datasets. We will also discuss how to extract ECHILD data from SQL tables on the ONS Secure Research Service platform and provide an overview of access arrangements. 

Day 2 will focus on a series of practical sessions (in Stata and R) allowing participants to progress through an exemplar research study using ECHILD, covering phenotyping, developing cohorts, and analysing ECHILD cohort data. 

The current course builds on our previous in person and online training courses with the inclusion of some updated information reflecting newer developments of ECHILD. ECHILD users who have previously attended this training course and have an interest in learning about emerging ECHILD research and newly available data are encouraged to attend the next ECHILD User Day, which is available for anyone with an interest in ECHILD.

The course covers: 

• Overview of the component datasets of ECHILD, with reference to case studies 

• Accessing the data on the ONS SRS 

• Strengths and limitations of ECHILD 

• Development of electronic cohorts in ECHILD 

• Phenotyping in ECHILD 

• Analysing ECHILD data 

By the end of the course participants will: 

• Understand what data are available in ECHILD 
• Know how to access ECHILD data 
• Understand the strengths and limitations of ECHILD 
• Know how to developing electronic cohorts in ECHILD 

The course is aimed at academic or government analysts and researchers who would like to know more about ECHILD and how ECHILD could be used in their own research, or who would like to know how it is currently being used to generate policy-relevant research. 

This is an intermediate level course that requires some prior knowledge of epidemiological research methods and statistical analysis, and familiarity with R or Stata.

ECHILD users who have previously attended this training course and have an interest in learning about emerging ECHILD research and newly available data are encouraged to attend the next ECHILD User Day, which is open to anyone with an interest in ECHILD.

Although there is no preparatory reading is required, although participants are encouraged to familiarise themselves with the data resources for researchers available on the ECHILD website.

Participants should have a basic understanding of epidemiological research methods and statistical analysis. They should be comfortable in using R or Stata. Experience using administrative data is not required but would be an advantage.

Programme

Day 1: 

• Introduction 
• Case Studies using each component dataset 
• Developing cohorts in ECHILD 
• Getting started with ECHILD data 
• ECHILD best practice and user community

Day 2: 

• Developing e-cohorts Part 1 
• Phenotyping to define exposures, outcomes and covariates 
• Developing e-cohorts Part 2 
• Analysing cohort data 
• Developing e-cohorts Part 3 
• Leveraging longitudinal administrative data for policy evaluation and population research

This is an in-person course and will take place at Friend's House (Elizabeth Fry Suite) on 28-29 September from 09:30-17:00.

Cost:

The fee per teaching day is:

• £60 per day for students registered at any University.
• £150 per day for staff at academic institutions, Research Councils researchers, public sector staff and staff at registered charity organisations and recognised research institutions.
• £350 per day for all other participants

All fees include event materials and morning and afternoon refreshments. Fees do not include travel and accommodation costs.

In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date.

If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of its cancellation of a course, including but not limited to any travel or accommodation costs.

The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:

Register for this course

Region:

Greater London

Keywords:

Data Quality and Data Management , Quality in Quantitative Research, Quantitative Data Handling and Data Analysis, Longitudinal Data Analysis, Quantitative Software, R, Stata, Use of Administrative Data Sources, Longitudinal Research, Interdisciplinary and Multidisciplinary Research

Related publications and presentations from our eprints archive:

Data Quality and Data Management
Quality in Quantitative Research
Quantitative Data Handling and Data Analysis
Longitudinal Data Analysis
Quantitative Software
R
Stata

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