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Analysing Patient-Level Data using Hospital Episode Statistics (HES), to be held at the University of York, UK, 6-8 December 2016.
 
This intensive workshop introduces participants to HES (hospital episode statistics) data and how to handle and manipulate these very large patient-level data sets using computer software. Understanding and interpreting the data is a key first step for using these data in economic evaluation or evaluating health care policy and practice. Participants will engage in lectures and problem-solving exercises, analysing the information in highly interactive sessions. Data manipulation and statistical analysis will be taught and demonstrated using Stata.
 
This workshop is offered to people in the academic, public and commercial sectors.  It is useful for analysts who wish to harness the power of HES non-randomised episode level patient data to shed further light on such things as patient costs and pathways, re-admissions and outcomes and provider performance.  The workshop is suitable for individuals working in NHS hospitals, commissioning organisations, NHS England, Monitor, and the Department of Health, pharmaceutical companies or consultancy companies and for health care researchers and PhD students.  Overseas participants may find the tuition helpful for their own country, but note that the course is heavily oriented towards understanding HES data for England.
 
The workshop fee is 900GBP for the public sector; 1,400GBP for the commercial sector. This includes all tuition, course materials, lunches, the welcome and drinks reception, the workshop dinner and refreshments, but does not include accommodation. 
 
Online registration is now open; further information and registration is at: 
http://www.york.ac.uk/che/courses/patient-data/
Subsidised places are available for full-time PhD students, and applications are invited by completing the form at: 
http://www.york.ac.uk/che/courses/patient-data/registrationstudent/
 
Contact: Gillian Robinson, Workshop Administrator, at:
[log in para visualizar];  tel: +44 (0)1904 321436.