Minster View

Statistical Methods in Economic Evaluation for HTA - Foundations/Advanced 

It is envisaged that participants interested in attending these courses are people currently undertaking, reviewing or commissioning analyses of health economics and outcomes research (HEOR) data, within the pharmaceutical and medical device industries, consultancy, academia or the health service.

Foundations course

‌Overview

This is a two-day foundations course designed for those wishing to develop an introductory understanding of the fundamental statistical concepts used in economic evaluation for Health Technology Assessment (HTA). The course includes a mixture of taught modules and practical exercises, where participants will learn the relevant statistical concepts and their estimation using the statistical software package Stata®. Although Stata® will be used as a vehicle to demonstrate a variety of statistical concepts in HTA, no prior knowledge of Stata® is required to be able to complete these practical exercises. 

Teaching methods‌

 Courses comp lab

The course includes a mixture of presentations from members of the Faculty, together with computer-based exercises using Stata®. The course will take place in a computer laboratory within the University of York campus and each participant will have access to a PC with the latest version of the Stata® software installed. Stata® code (do-files) required to complete the exercises will be provided and all exercises will be supported by Faculty and a group of tutors. Participants are expected to have a basic familiarity with the concepts of cost-effectiveness analysis for Health Technology Assessment (HTA) decisions. 

Objectives 

By the end of the course, participants will be able to: 

  • understand the key statistical concepts used in economic evaluation for HTA;
  • appreciate how to use existing evidence to derive statistical parameters, relevant to economic evaluation;
  • produce descriptive statistics, tabulation and correlations from patient-level data using Stata® to (i) derive basic inputs for health economics models and (ii) report the results of trial-based cost-effectiveness analyses; 
  • understand good practice in the reporting of cost-effectiveness results to decision makers and recognise the analytical issues involved when dealing with individual patient-level data;
  • appreciate the potential for using a regression approach to derive parameter estimates to populate a cost-effectiveness model while controlling for patient characteristics. 

Outline programme

Please note that the exact programme is subject to change although the material covered will remain largely the same. 

Day One (10am start)

  • Introduction and Policy Context
  • Introduction to Stata® (Lecture and Practical)
  • Foundations in Statistics for Economic Evaluation (Lecture and Practical) - key quantities and how they are derived
  • Exploiting Available Evidence (Lecture and Practical)
  • Evening Social Event 

Day Two

  • Analytical Approaches involving Patient-Level Data (Lecture and Practical)
  • Multivariable Regression for Economic Evaluation (Lecture and Practical)
  • Advanced Statistical Issues – this lecture looks at a series of case studies to make participants aware of statistical issues beyond the scope of the foundations course
  • Course Ends (5pm)

Fees

VAT is not payable. Transferring between courses is not possible.  Registration fees are payable in advance of the workshop dates and are fully inclusive of:  

  • Tuition
  • Lunch
  • One Course Dinner event per Course
  • Course materials
  • Do not include accommodation
2019 Public/academic sectorCommercial sector
Foundations Course  £760.00  £1200.00 



Advanced course

Overview

This is a three-day advanced course focused on the use of statistical methods for the analysis for of individual patient-level cost, effects (e.g. survival and health-related quality of life) and other type of data used in cost-effectiveness analysis for HTA. It is intended for people who wish to learn how to apply (and interpret the results of) more advanced techniques for the analysis of data collected alongside both experimental (e.g. RCTs) and observational (sometimes referred to as “real-world”) studies, where the objective is to estimate within-study quantities (e.g. differential mean costs) or to derive key input parameters to populate economic evaluation models for HTA. The course includes a mixture of taught modules and practical exercises. 

Teaching methods

Practical exercises will be conducted in Stata® to help participants appreciate how the methods described during the lectures can be used in real life. Some prior knowledge of Stata® is recommended to be able to maximise the learning opportunity offered by the practical exercises. The course will take place in a computer laboratory within the University of York campus and each participant will have access to a PC the latest version of the Stata® software installed. Stata® codes (do-files) required to complete the exercises will be provided and all exercises will be supported by Faculty and a group of tutors. 

Objectives

By the end of the course, participants will be able to:

  • understand the advantages of using more advanced statistical methods to analyse individual-patient level cost-effectiveness data for HTA;
  • use Stata® to apply robust statistical methods for the analysis of different kinds of HEOR data relevant to HTA (e.g. survival, health-related quality of life and costs);
  • gain insight into how to interpret (and critically assess) the output of these analyses and to use this to derive parameters of interest in a cost-effectiveness model (e.g. probabilities, health state utility values, costs);
  • appreciate what methods can be used to analyse data obtained from non-randomised studies and how to apply these in cost-effectiveness analysis;
  • assess their study results, report and present the output of such analyses to policy makers.

Outline programme

Please note that the exact programme is subject to change although the material covered will remain largely the same.

This course uses a simulated, but realistic, patient-level dataset to illustrate the key concepts, which are like building blocks introduced with increasing sophistication. Ultimately the course aims to show students how to analyse these kinds of data to estimate within-study quantities (e.g. differential mean costs) or to derive key input parameters to populate a cost-effectiveness model to inform HTA decisions.

Three-day course

Day one - (9.00am start)

  • Economic evaluation for decision-making: policy context;
  • Economic evaluation for decision-making: methodological context
  • Introduction to the analysis of experimental (i.e. RCT) and observational data to estimate treatment effects;
  • Statistical methods for the analysis of binary and time-to-event outcomes;
  • Evening social event: drinks reception

Day two 

  • Statistical analysis of generic health-related quality of life (HRQoL) data and how to derive health-states utility values
  • Developing and applying mapping algorithms to predict EQ-5D from other HRQoL instruments
  • Advanced statistical methods for the analysis of cost data and how to quantify health-state costs
  • Evening social event: dinner

Day three

  • Analysis of observational data to estimate treatment effects, beyond propensity score methods;
  • Advanced methods for the analysis of time-to-event data, to derive probability estimates in realistic settings
  • Summary and key messages
  • Course Ends (approx. 4pm)

Fees

VAT is not payable. Transferring between courses is not possible.  Registration fees are payable in advance of the workshop dates and are fully inclusive of:  

  • Tuition
  • Lunch
  • One Course Dinner event per Course
  • Course materials
  • Do not include accommodation
 2019Public/academic sectorCommercial sector
Advanced Course  £1150.00 £1800.00 

Faculty

Faculty

In addition to the presenters below, tutors from CHE will be involved in all exercises to ensure that there will be sufficient support to maximise participants’ learning experience.

Susan Griffin

Susan is a Senior Research Fellow based in the team for Economic Evaluation and Health Technology Assessment. Her research interests include the use of decision-analytic models in cost-effectiveness analysis, value of information analysis and the application of methods for economic evaluation in the field of public health. Susan has worked on economic evaluations in the fields of cardiovascular disease, HIV/AIDS, cancer and mental health.

Noemi Kreif

Noemi joined the Centre in 2016 as a Research Fellow in Global Health Economics.  She holds a PhD (2013) from the London School of Hygiene and Tropical Medicine. Her PhD and post-doctoral (Medical Research Council Early Career Fellowship) work focussed on advancing statistical methods for economic evaluation that uses observational data, resulting in publications in leading health economics and statistics journals, such as Health Economics, Statistical Methods in Medical Research and American Journal of Epidemiology. Her current work is centred on econometric evaluations of health policies in low and middle-income countries, with a continued interest in applying advanced causal inference and machine learning tools. 

James Lomas

James joined the Team for Economic Evaluation and Health Technology Assessment (TEEHTA) in October 2014. Prior to this he was a PhD student affiliated with the Health, Econometrics and Data Group. holds a BA in Economics from the University of Cambridge and an MSc in Health Economics from the University of York, and has worked at the OECD and the Department of Health (UK) on summer placements. In 2016, Andrew Jones, James Lomas and Nigel Rice were awarded the inaugural Willard G. Manning Memorial Award for the Best Research in Health Econometrics by the American Society of Health Economists.

Andrea Manca (course leader)

Andrea is Professor of Health Economics based in the Team for Economic Evaluation and Health Technology Assessment. His research interests include the application of statistical methods for the analysis of cost-effectiveness and health outcomes data, as well as the use of evidence synthesis techniques in economic evaluation to support health care decision making. Andrea has worked in economic evaluations of health technologies in several clinical areas. 

Mark Sculpher

Mark is Professor of Health Economics and leads the Team for Economic Evaluation and Health Technology Assessment. He has worked on numerous applied economic evaluations including interventions in heart disease, cancer, HIV and respiratory disease. His methodological interests are handling uncertainty and decision analytical modelling.

Beth Woods

Beth is a Senior Research Fellow in the Team for Economic Evaluation and Health Technology Assessment. Prior to joining CHE Beth was a Director in the Health Economics team at Oxford Outcomes, a private consulting firm, where she specialised in applied economic evaluation from 2006-2013. During this time Beth contributed to numerous submissions to the National Institute for Health and Care Excellence (NICE) and other national HTA agencies.

Registration

Registration

Before you register on these workshops please ensure you have secured the appropriate funding from your organisation, and (if applicable) that you allow yourself plenty of time to apply for any visas you may require to enter the UK, as you may experience some delay in getting these processed.

Please register via Credit/Debit card for instant payment and a guaranteed secured place on your chosen course (please note the University of York does not accept American Express cards) University of York online payment store 

If you or your organisation cannot pay by credit/debit card please email the Spring Course Coordinator on che-statmeth@york.ac.uk

  • Please note that we will submit invoices by post or email invoices to an address of your choice but we will not sign up to portals due to the way the University is structured and due to limited resources we have in our office.
  • We regret that we cannot reserve or hold workshop places in advance of booking or payment.

Fees

VAT is not payable. Transferring between courses is not possible.  Registration fees are payable in advance of the workshop dates and are fully inclusive of:  

  • Tuition
  • Lunch
  • One Course Dinner event per Course
  • Course materials 
  • Do not include accommodation 
 2019Public/academic sectorCommercial sector
Foundations Course

£760.00

£1200.00

Advanced Course  £1150.00 £1800.00

Places on all workshops are available to book right up until the Friday before the course runs, although it is advisable to book early to avoid disappointment.

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-statmeth@york.ac.ukCancellations 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

You are responsible for arranging your own accommodation.  Unfortunately, campus accommodation is not available over the Easter break.  Some rooms may become available - the University Conference Office can provide updated information.  There are many hotels and guest houses locally (Fulford and Heslington are the closest areas) and some of these hotels can be viewed on the following web-sites:

http://www.expedia.co.uk/Fulford-Hotels.d602274.Travel-Guide-Hotels

http://www.visityork.org/

Who to contact

Course dates

  • Foundations Course 
    18th & 19th March 2019
  • Advanced Course
    20th - 22nd March 2019

CHE Short Courses in Health Economics brochure 2018 (PDF  , 1,355kb)