Recommended Methods for the Collection of Health State Utility Value Evidence in Clinical Studies

The Impact of Hypoglycemia on Productivity Loss and Utility in Type 2 Diabetes Patients Treated with Insulin in Real-World Canadian Practice: Protocol for a Prospective Study (Preprint)

Background

Type 2 diabetes mellitus (T2DM) imposes a substantial burden owing to its increasing prevalence and life-threatening complications. In patients who do not achieve glycemic targets with oral antidiabetic drugs, the initiation of insulin is recommended. However, a serious concern regarding insulin is drug-induced hypoglycemia. Hypoglycemia is known to affect quality of life and the use of health care resources. However, health economics and outcomes research (HEOR) data for economic modelling are limited, particularly regarding utility values and productivity losses.

Objective

This real-world prospective study aims to assess the impact of hypoglycemia on productivity and utility in insulin-treated adults with T2DM from Ontario and Quebec, Canada.

Methods

This noninterventional, multicenter, 3-month prospective study will recruit patients from 4 medical clinics and 2 endocrinology or diabetes clinics. Patients will be identified using appointment lists and enrolled through consecutive sampling during routinely scheduled consultations. To be eligible, patients must be aged ≥18 years, diagnosed with T2DM, and treated with insulin. Utility and productivity will be measured using the EQ-5D-5L questionnaire and Institute for Medical Technology Assessment Productivity Cost Questionnaire, respectively. Questionnaires will be completed 4, 8, and 12 weeks after recruitment. Generalized estimating equation models will be used to investigate productivity losses and utility decrements associated with incident hypoglycemic events while controlling for individual patient characteristics. A total of 500 patients will be enrolled to ensure the precision of HEOR estimates.

Results

This study is designed to fill a gap in the Canadian evidence on the impact of hypoglycemia on HEOR outcomes. More specifically, it will generate productivity and utility inputs for the economic modeling of T2DM.

Conclusions

Insulin therapy is expensive, and hypoglycemia is a significant component of economic evaluation. Robust HEOR data may help health technology assessment agencies in future reimbursement decision-making.

International Registered Report Identifier (IRRID)

PRR1-10.2196/35461

Vignette-Based Utilities: Usefulness, Limitations, and Methodological Recommendations

Health technology assessment agencies often prefer that utilities used to calculate quality-adjusted life years in cost-utility analyses (CUAs) are derived using standardized methods, such as generic preference-based measures completed by patients in clinical trials. However, there are situations when no standardized approach is feasible or appropriate for a specific medical condition or treatment that must be represented in a CUA. When this occurs, vignette-based methods are often used to estimate utilities. A vignette (sometimes called a "scenario," "health state description," "health state vignette," or "health state") is a description of a health state that is valued in a preference elicitation task to obtain a utility estimate. This method is sometimes the only feasible way to estimate utilities representing a concept that is important for a CUA. Consequently, vignette-based studies continue to be conducted and published, with the resulting utilities used in economic models to inform decision making about healthcare resource allocation. Despite the potential impact of vignette-based utilities on medical decision making, there is no published guidance or review of this methodology. This article provides recommendations for researchers, health technology assessment reviewers, and policymakers who may be deciding whether to use vignette-based methods, designing a vignette study, using vignette-based utilities in a CUA, or evaluating a CUA that includes vignette-based utilities. Recommendations are provided on: (A) when to use vignette-based utilities, (B) methods for developing vignettes, (C) valuing vignettes, (D) use of vignette-based utilities in models, and (E) limitations of vignette methods.

The estimation of health state utility values in rare diseases: overview of existing techniques

There are several techniques for estimating health state utility values, each of which presents pros and cons in the context of rare diseases (RDs). Direct approaches (e.g. standard gamble and time trade-off) may be too demanding for patients with RDs, since most of them affect young children or cause cognitive impairment. The alternatives are using "vignettes" that describe hypothetical health states for the general public, which may not reflect the heterogeneous manifestations of RDs, or multi-attribute utility instruments (i.e. indirect techniques), such as EQ-5D, which may be less sensitive in capturing the specificities of RDs. The "rule of rescue" approach is a promising alternative in RDs, since it prioritizes identifiable patients with life-threatening or disabling conditions. However, it raises measurement challenges and ethical issues. Furthermore, the literature reports on relevant implications of choosing a technique over others for health technology assessment, which should be considered in relation to individual RDs.

The Use of Health State Utility Values in Decision Models

Methodological issues of how to use health state utility values (HSUVs) in decision models arise frequently, including the most appropriate evidence to use as the baseline (e.g. the baseline HSUVs associated with avoiding a particular health condition or event), how to capture changes due to adverse events and how to appropriately capture uncertainty in progressive conditions where the expected change in quality of life is likely to be monotonically decreasing over time. As preference-based measures provide different values when collected from the same patient, it is important to ensure that all HSUVs used within a single model are obtained from the same instrument where ever possible. When people enter the model without the condition of interest (e.g. primary prevention of cardiovascular disease, screening or vaccination programmes), appropriate age- and gender-adjusted HSUVs from people without the particular condition should be used as the baseline. General population norms may be used as a proxy if the exact condition-specific evidence is not available. Individual discrete health states should be used for serious adverse reactions to treatment and the corresponding HSUVs sourced as normal. Care should be taken to avoid double counting when capturing the effects for both less severe adverse reactions (e.g. itchy skin rash or dry cough) and more severe adverse events (e.g. fatigue in oncology). Transparency in reporting standards for both the justification of the evidence used and any 'adjustments' is important to increase readers' confidence that the evidence used is the most appropriate available.

International Regulations and Recommendations for Utility Data for Health Technology Assessment

Recommendations and guidelines for the collection, generation, source and usage of utility data for health technology assessment (HTA) vary across different countries, with no international consensus. Many international agencies generate their own guidelines providing details on their preferred methods for HTA submissions, and there is variability in both what they recommend and the clarity and amount of detail provided in their guidelines. This article provides an overview of international regulations and recommendations for utility data in HTA for a selection of key HTA countries: Australia, Canada, France, Germany, the Netherlands, Spain (Catalonia), Sweden and the UK (England/Wales and Scotland). International guidelines are typically clear and detailed for the selection of countries assessed regarding the source description of health states (e.g. generic preference-based measure) and who should provide preference weights for these health states (e.g. general population for own country). Many guidelines specify the use of off-the-shelf generic preference-based measures, and some further specify a measure, such as EQ-5D. However, international guidelines are either unclear or lack detailed guidance regarding the collection (e.g. patients report own health), source (e.g. clinical trial) and usage (e.g. adjusting for comorbidities) of utility values. It is argued that there is a need for transparent and detailed international guidelines on utility data recommendations to provide decision makers with the best possible evidence. Where this is not possible it is recommended that best practice should be used to inform the collection, source and usage of utility values in HTA.