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Analysing Patient-Level Data using Hospital Episode Statistics (HES)

Overview

Overview 

Going through the paper inpatient and outpatient exercises was very useful.

Previous participant

Hospital episode statistics (HES) contains details of all admissions to NHS hospitals and all NHS outpatient appointments in England and is a main data source for a wide range of healthcare analyses for the NHS, government and many other organisations and individuals. There is also an increasing role for this observational dataset in providing evidence-based parameters which are not collectable in trials for the economic evaluation of new technologies. Admitted patient care data is available from 1989 onwards, with more than 18 million new inpatient records with over 350 data items per record added each year. Outpatient attendance data has been collected since 2003, with more than 90 million new records added each year. Recent HES data also includes Patient Reported Outcome Measures (PROMs) for a limited number of conditions.

However because of the size and complexity of HES, it is one of the most challenging and difficult datasets to get to grips with: complex coding of data items, data provided at a level which is not immediately amenable to analysis, missing data, duplicates, costing episodes via HRGs and other data issues mean that the analyst has significant upfront investment costs in learning to come to terms with the data before being able to produce meaningful analyses that are free from common errors.

I really liked the fact that the course gave a really good insight into HES (HES is amazingly complicated!)

Previous participant

Taught by academics with extensive experience in using HES for a wide range of outputs, this intensive workshop introduces participants to HES data and how to handle, manipulate and begin to analyse these very large datasets using computer software. Participants will engage in problem-solving exercises, analysing the information in highly interactive sessions. At the end of the course, the participants should understand the complex nature of the HES datasets, understand the importance of approaching HES with a disciplined programming structure and have the tools required to manipulate and re-code data from the raw form to that required for analysis. 

Objectives

This course includes instruction on how to:

  • understand, manage and manipulate the data
  • construct and analyse key variables such as waiting times or length of stay
  • analyse individual patient records defined as Finished Consultant, Episodes, Provider Spells and Continuous Inpatient Spells
  • monitor emergency readmissions
  • aggregate data by Healthcare Resource Group or providers/commissioners
  • cost data by HRG and reference costs
  • evaluate Patient Reported Outcome Measures (PROMS) 
  • use the data for benchmarking and policy evaluation

The tutors have worked extensively with HES data and will guide participants through the potential pitfalls using case studies, practical examples and problem-solving exercises.

Prerequisites

This workshop is offered to people working in the public sector, academia and the private sector. It is suitable for analysts who wish to harness the power of 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 and the Department of Health, pharmaceutical companies or consultancy companies and for health care researchers and PhD students. Overseas applicants may also find the tuition can be applied to similar scenarios in their own country, but must be aware that the tuition and exercises relate directly to HES data which is created for, and used in, England.

Participants should have some knowledge of introductory statistics and familiarity with computer software such as Excel, Access, SPSS, SAS or Stata.

We shall be using Stata during the workshop, the reason being that the data manipulation and analyses we shall be performing require a powerful statistical package. More information about Stata is available here http://www.stata.com/why-use-stata/. On the registration form, indicate if you will attend the Stata introduction session. 

Course dates

Course dates

  • To be announced

Programme

Course programme

Day 1:   

  • 09:10 - 09:30 Registration
  • 09:30 - 12:45 Introduction to computer software: Stata. (Optional: indicate attendance (or not) on the online registration form)
  • 12:35 - 12:45 only: Registration for those not attending optional Stata session
  • Introduction to HES datasets. HES inpatient records: episodes, provider spells, and continuous inpatient spells. Examining an example HES extract. Linkage to other datasets
  • Obtaining HES data; data manipulation: inpatient data and missing values
  • Welcome and drinks reception

Day 2:

  • Data Manipulation (contd). Dealing with dates and identifying duplicate records. Data quality and errors in HES
  • Linking patient episodes. Constructing continuous inpatient spells
  • Using HES to measure hospital performance
  • Analysing Patient Reported Outcome Measures (PROMs)
  • Workshop dinner in York's city centre

Day 3:

  • Introduction to Healthcare Resource Groups (HRGs)
  • The HRG Grouper
  • Using HES in applied research
  • 15:45 End of workshop

Presenters

Presenters

The senior tutors for this course will be Chris Bojke and Andrew Street

Further tutors will be Research Fellows in the Centre for Health Economics. 

 

Registration

Registration

Further information and registration will be available after the dates are announced for the next workshop.

Cancellations and alterations

A full refund of course fees (less 10% administrative charge) will be made for cancellations received in writing at least one month prior to the workshop. Substitutes can be made but please email new delegate's details when known to che-apd@york.ac.uk. Cancellations made less than one month prior to the workshops are non-refundable/non-changeable.

In the unlikely event that, due to unforeseen circumstances, the course has to be cancelled by the University of York, our liability is limited to refund of workshop fees. We recommend delegates have adequate insurance cover to claim any travel or personal expenses.

Accommodation

Once registered, the course administrator will give further information about accommodation available on campus and in York in your registration confirmation. The cost of accommodation is additional to the course fee. There are a large number of hotels and guest houses in York.

Who to contact

Course dates

  • To be announced