Introduction to Hospital Episode Statistics
|Organised by||NCRM, University of Southampton|
|Presenter||Dr Pia Hardelid|
|Date||03/10/2019 – 04/10/2019|
|Venue||Building 39, University of Southampton, Highfield, Hants|
|Map||View in Google Maps (SO17 1BJ)|
Training and Capacity Building Co-ordinator
National Centre for Research Methods
|Description||This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data.
The course covers:
By the end of the course participants will:
• understand how and why HES data are collected
• become aware of the strength and weaknesses of using HES data for research
This course is aimed at researchers and analysts at any level working in universities, local authorities, civil service, the NHS, private sector or third sector organisations.
Previous experience of programming in Stata, R or SAS will therefore be helpful, but Stata code and instructions will be provided to all participants. There are no pre-requisites for the lectures.
|Level||Entry (no or almost no prior knowledge)|
|Cost||The fee per teaching day is:
• £30 per day for UK/EU registered students
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Full refund is available two weeks prior to the course, NO refunds are available after this date
|Website and registration|
|Keywords||Longitudinal Data Analysis, Hospital Episode Statistics , Hospital Data , Administrative Data , Routine Data , Data Management , Health Data Science|
|Related publications and presentations||Longitudinal Data Analysis|