New Research on VBP: Disease Severity and Unmet Need in the UK

Posted on 24 April 2012 by OHE News Editor

Koonal Shah

The UK Department of Health’s value based pricing (VBP) Consultation Document proposes a process whereby higher prices would be granted to medicines that tackle diseases that produce the greatest burdens of illness – i.e. those diseases that are most severe or are associated with the greatest unmet need. This suggests combining severity of disease and unmet need into a single metric. A literature review reveals that this approach has not been studied adequately (or perhaps at all) to date, either in the UK or elsewhere.

The Department of Health’s Policy Research Unit in Economic Evaluation of Health and Care Interventions (EEPRU) was asked by the Department to conduct an empirical study of society’s resource allocation preferences to obtain weights for burden of illness, therapeutic improvement and end-of-life. The objective would be to apply these, under the coming VBP system, to assessments of both new technologies and displaced activities.

The EEPRU study defines burden of illness as distance from “normal” health; the measure combines health status with the effects of existing standard therapy on both length and quality of life. The value of existing therapy, then, is in its contribution to the degree of burden. Not considered explicitly in the EEPRU study are issues raised by the definition of unmet need implied in the VBP Consultation Document – i.e. that “unmet need” means that no treatment is available at all.

Data collection for the EEPRU study is being conducted online, using discrete choice experiments to elicit preferences. Stakeholders have expressed concern about the limited scope of the EEPRU study in that it does not examine whether people have preferences about the availability of alternative treatments.

To address some of these issues, OHE currently is performing a small study, funded by an unrestricted research grant from the ABPI. Based on interviews with members of the general public, it is intended to develop a more nuanced understanding of the extent of societal support for basing health care resource priorities on disease severity and unmet need.

The OHE survey will be administered in face-to-face interviews conducted by trained interviewers with experience in conducting health care preference studies. Questions will be designed to identify respondents’ levels of support for policies that give greater weight to treatments that address disease severity and unmet medical need than to those that do not. The research also will address whether, controlling for disease severity, unmet need per se affects societal preferences regarding priorities for treatment. In this study, respondents also will be asked probing follow-up questions intended to elicit qualitative information about the thinking behind their choices.

This study will provide important, preliminary information about how disease severity and unmet need should be measured and how best to capture societal preferences. The main points we expect the research to address include the following:

Whether members of the public would support a policy that uses combined disease severity and unmet need as a criterion for priority setting
What societal preferences about disease severity and unmet need can be observed
Whether preferences regarding unmet need depend at least in part on disease severity
The likely reasons for the preferences observed
The strength of the preferences observed

The OHE study, then, will both complement the EEPRU study by exploring additional possible attributes and provide additional evidence about whether preferences regarding unmet need depend on disease severity. It can help define what further research is essential to produce valid measures.

The OHE research team for the project is Koonal Shah and Nancy Devlin. Results are anticipated in summer 2012 and will be published as an OHE Research Paper.

Comparing Variants of Lead and Lag Time TTO

Posted on 1 February 2011 by OHE News Editor

As reported in an earlier post, OHE was awarded a Policy Research Programme grant by the Department of Health that focuses on three aspects of health status indexes. The second of these is a study on Time Trade Off (TTO) methodology, focusing on Lead and Lag Time TTO (LT-TTO). TTO is crucial because it helps translate patients’ EQ-5D data into values that can underpin health care allocation and access decisions. The National Institute of Health and Clinical Excellence (NICE), for example, uses TTO values in assessing new technologies.

The objective of this research was to develop a better understanding of the characteristics of the data generated by LT-TTO, improve data collection tools, and provide information for selecting the particular variant of LT-TTO to be used in subsequent research.

Now available as OHE Research Paper 10/02, the results of this research already are having an important impact. Research to pilot the use of the methods reported in our paper now is underway in four countries. An additional four countries will use our results as the basis for further methodological research. These studies, coordinated by the EuroQol Group, will lay the foundations for future EQ-5D-5L value sets studies.

Background

The estimate of Quality Adjusted Life Years (QALYs) a patient gains from treatment requires that the length of life gained be adjusted by its quality – i.e., the perceived value of life to the patient experiencing a particular health state. These values (weights) are anchored on a scale where 1 is full health and 0 is dead. Health states perceived to be worse than dead have values of less than 0.

The ‘Time Trade Off’ method is widely used to obtain these values, but it presents some important problems. In particular, the method cannot adequately handle very poor health states that people may consider to be so bad they are ‘worse than being dead’. In such cases, the TTO must switch to a different questioning process to capture value, creating problems for the comparability and interpretation of values less than zero. In previous research, LT-TTO proved capable of producing weights for states both better and worse than dead.

Aims

The aims of this research were (1) to investigate the values generated from LT-TTO using different combinations of the length of time the individual experiences full health and a particular health state; the order of these states also was varied (Lead v. Lag Time TTO), (2) to gauge whether values generated from these methods concur with participants’ views as to whether the states are better or worse than dead, and (3) to explore a range of methods for handling the preferences of those whose distaste for very poor health states is so great that they are willing ‘use up’ all their lead time to avoid them.

Methods

A sample of 200 members of the general public valued five health states, using two of four variants of the LT-TTO: a lead time of 10 years followed by a health state duration of 20 years; a lead time of 5 years followed by a health state duration of 1 year; a lead time of 5 years followed by a duration of 10 years; and a duration of 5 years of a health state followed by with a lag time of 10 years. Participants also responded to a range of supplementary tasks and other questions.

Results

Values are influenced by the length of the lead time relative to the health state duration. Longer lead times enable somewhat more preferences to be captured, but appear to exert a framing effect on values. Lag time TTO results in both a greater willingness to trade off for mild states of poor health and trading off less time for severe states. Of those who valued the worst health state as less than 0, 70% also expressed the view that this state was worse than dead.

Conclusions

LT-TTO confers an important advantage over TTO by providing a single method capable of generating values greater and less than 0 that seem broadly in keeping with participants’ stated views about those states being better or worse than dead. However, values are sensitive both to the length of time in full health relative to the duration of the state to be valued and to the order in which these occur (lead vs. lag time). For those who use up their lead time, we show that additional ways of eliciting these preferences (via additional questioning) are feasible, as is modelling those values (via survival analysis). A small (<5%) group of participants remain, however, whose preferences are so ‘extreme’ that they cannot be captured by any approach.

Download Devlin, N et al. (2010) A comparison of alternative variants of the Lead and Lag Time TTO. Research Paper 10/02. London: Office of Health Economics

OHE Awarded DH Grant for EQ-5D Research

Posted on 13 April 2010 by OHE News Editor

The OHE has been awarded a £325,000 Policy Research Programme grant by the Department of Health. The fifteen-month project focuses on a new health status index – the 5 level (5L) EQ-5D — that will capture smaller changes in health related quality of life than does the current 3 level (3L) instrument. The EQ-5D is arguably the most important patient-reported outcomes measure (PROM) currently in use. In England, for example, it underpins technology appraisals submitted to NICE and is used by the PROMs programme to assess the quality of care provided in different settings.

The research for this grant consists of three sets of studies. The first will map the 5L to 3L values to produce an interim set of measures applicable while international research resolves important methodological issues with the 5L approach. The EuroQol Group has similar research underway in Scotland, Poland and The Netherlands. In England, 1,000 patients will be involved who have one of four diagnoses: rheumatoid arthritis, depression, multiple sclerosis or a recent history of myocardial infarction.

The second study will focus on improving Time Trade Off (TTO) methodology, focusing on Lead Time TTO (LT-TTO). The objective is to develop a better understanding of the characteristics of the data generated by LT-TTO, improve data collection tools, and provide information for selecting the particular variant of LT-TTO to be used in subsequent research. TTO helps translate EQ-5D indexes into values that can underpin health care allocation and access decisions.

The third study builds on the second, with the aim of investigating alternatives for addressing technical issues presented by the increase from 243 states under 3L to 3,125 under 5L. Specifically, a hybrid approach using LT-TTO and discrete choice (DC) methods will be tested. This study is part of a wider four-country study, involving the Netherlands, Italy and Canada.

The research programme will yield both an interim value set for the EQ-5D-5L, and methodological improvements in approaches to valuation that can be used to produce new national value sets for use in economic evaluation.

Investigators on the grant include: Prof Nancy Devlin, OHE; Dr Andrew Lloyd, Oxford Outcomes Ltd; Dr Aki Tsuchiya, University of Sheffield; Mr Koonal Shah, OHE. Please contact Nancy Devlin for additional information.

Official project title: An interim EQ-5D-5L value set for England and development of EQ-5D-5L valuation methods