Just a reminder.
> Operational Research Society
> Health and Social Services study group meeting*
> ------
> HOSPITAL EPISODE STATISTICS
> ------
> Date: TUESDAY 25 May 2004, 17:00-18:30
> Venue: 9-18 Euston Centre, University of Westminster, Room 3.02
> http://www.streetmap.co.uk/streetmap.dll?G2M?X=529153&Y=182435&A=Y&Z=1
>
> Talk 1: The Hospital Episodes Statistics data warehouse: what
can
> it do?
> By: Sheila Dixon, Head of Output, Hospital Episodes
> Statistics, Department of Health, UK
>
> Abstract:
> The Hospital Episodes Statistics (HES) database contains records of all
> admitted patient care in NHS Trusts in England. With over 12 million
> records per year, the database has information on patients (e.g. age, sex,
> residence), their pathway through hospital (e.g. elective or emergency,
> dates in and out) and some clinical data (diagnoses and operations). This
> provides a resource for a number of central and local purposes, such as
> defining activity, investigating trends, monitoring performance and
managing
> resources. Traditionally reported at national, Trust or health
organisation
> level, HES is also developing analysis at consultant level. This session
> will look at what HES comprises, how it can be used and a selection of
> examples of the analysis it offers.
>
> Talk 2: Leveraging HES data to support health care modelling:
A
> data warehouse approach
> By: Dr Christos Vasilakis, University of Westminster, UK
>
> Abstract:
> Data warehousing and On-Line Analytical Processing (OLAP) tools have
become
> the standard for analytical applications in the business world as they are
> characterised by powerful data browsing capabilities. However, developing
> such information systems in the health care domain poses some interesting
> challenges. It is due to the particular analytical requirements of health
> decision makers and the unique characteristics of health care data. This
> talk gives an introduction to data warehousing and OLAP concepts, and a
> description of a pertinent prototype application that is built around
> Hospital Episode Statistics data. The prototype primarily supports the
> analysis of bed occupancy and patient length of stay data, both seen as
> critical to the development of decision models of patient flow.
>
> * For more information contact Dr Thierry Chaussalet, Health and Social
Care
> Modelling Group (HSCMG), Cavendish School of Computer Science (CSCS),
> Department of Mathematics, 9-18 Euston Centre, London; Tel: 020 7911 5000
> ext 4310; Email: [log in to unmask]
> -----------
> Dr. T.J. Chaussalet
> Reader, CSCS, Dept of Mathematics
> University of Westminster
> 9-18 Euston Centre
> London NW1 3ET, UK
> Tel: +44(0)207 911 5000 ext 4310
> Fax: +44(0)207 915 5438
> Email: [log in to unmask]
> -----------
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