Using Patient Preferences in Health Technology Assessment: Evaluating Quality-Adjusted Survival Equivalents (QASE) for the Quantification of Non-health Benefits.

Interest in using patient preference (PP) data alongside traditional economic models in health technology assessment (HTA) is growing, including using PP data to quantify non-health benefits. However, this is limited by a lack of standardised methods. In this article, we describe a method for using discrete choice experiment (DCE) data to estimate the value of non-health benefits in terms of quality-adjusted survival equivalence (QASE), which is consistent with the concept of value prevalent among HTA agencies. We describe how PP data can be used to estimate QASE, assess the ability to test the face-validity of QASE estimates of changes in mode of administration calculated from five published DCE oncology studies and review the methodological and normative considerations associated with using QASE to support HTA. We conclude that QASE may have some methodological advantages over alternative methods, but this requires DCEs to estimate second-order effects between length and quality of life. In addition, empirical work has yet to be undertaken to substantiate this advantage and demonstrate the validity of QASE. Further work is also required to align QASE with normative objectives of HTA agencies. Estimating QASE would also have implications for the conduct of DCEs, including standardising and defining more clear attribute definitions.

Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms.

It is important that patient-reported outcome (PRO) measures used to assess cancer therapies adequately capture the benefits and risks experienced by patients, particularly when adverse event profiles differ across therapies. This study explores the case for augmenting preference-based utility measures to capture the impact of cancer treatment-related symptoms. Additional cancer treatment-related items could be specific (e.g., rash) or global. While specific items are easier to describe and understand, their use may miss rarer symptoms and those that are currently unknown but will arise from future medical advancements. The appropriate number of additional items, the independence of those items, and their impact on the psychometric properties of the core instrument require consideration. Alternatively, a global item could encompass all potential treatment-related symptoms, of any treatments for any disease. However, such an item may not be well understood by general public respondents in valuation exercises. Further challenges include the decision about whether to generate de novo value sets for the modified instrument or to map to existing tariffs. The fluctuating and transient nature of treatment-related symptoms may be inconsistent with the methods used in conventional valuation exercises. Fluctuating symptoms could be missed by sub-optimal measure administration timing. The addition of items also poses double-counting risks. In summary, the addition of treatment-related symptom items could increase the sensitivity of existing utility measures to capture known and unknown treatment effects in oncology, while retaining the core domains. However, more research is needed to investigate the challenges, particularly regarding valuation.

Using EQ-5D Data to Measure Hospital Performance: Are General Population Values Distorting Patients' Choices?

Background. The English National Health Service publishes hospital performance indicators based on average postoperative EQ-5D index scores after hip replacement surgery to inform prospective patients' choices of hospital. Unidimensional index scores are derived from multidimensional health-related quality-of-life data using preference weights estimated from a sample of the UK general population. This raises normative concerns if general population preferences differ from those of the patients who are to be informed. This study explores how the source of valuation affects hospital performance estimates. Methods. Four different value sets reflecting source of valuation (general population v. patients), valuation technique (visual analog scale [VAS] v. time tradeoff [TTO]), and experience with health states (currently experienced vs. experimentally estimated) were used to derive and compare performance estimates for 243 hospitals. Two value sets were newly estimated from EQ-5D-3L data on 122,921 hip replacement patients and 3381 members of the UK general public. Changes in hospital ranking (nationally) and performance outlier status (nationally; among patients' 5 closest hospitals) were compared across valuations. Results. National rankings were stable under different valuations (rank correlations >0.92). Twenty-three (9.5%) hospitals changed outlier status when using patient VAS valuations instead of general population TTO valuations, the current approach. Outlier status also changed substantially at the local level. This was explained mostly by the valuation technique, not the source of valuations or experience with the health states. Limitations. No patient TTO valuations were available. The effect of value set characteristics could be established only through indirect comparisons. Conclusion. Different value sets may lead to prospective patients choosing different hospitals. Normative concerns about the use of general population valuations are not supported by empirical evidence based on VAS valuations.

Government and charity funding of cancer research: public preferences and choices.

BACKGROUND: It is unclear how the public would respond to changes in government decisions about how much to spend on medical research in total and specifically on major disease areas such as cancer. Our aim was to elicit the views of the general public in the United Kingdom about how a change in government spending on cancer research might affect their willingness to donate, or to hypothecate a portion of their income tax payments, to cancer research charities. METHODS: A web-based stated preference survey was conducted in 2013. Respondents considered hypothetical scenarios regarding changes in the levels of government funding for medical research. In each scenario, respondents were asked to imagine that they could allocate £100 of the income tax they paid this year to one or more medical research charities. They were asked how they wished to allocate the £100 between cancer research charities and medical research charities concerned with diseases other than cancer. After having been given the opportunity to allocate £100 in this way, respondents were then asked if they would want to reduce or increase any personal out-of-pocket donations that they already make to cancer research and non-cancer medical research charities. Descriptive analyses and random effects modelling were used to examine patterns in the response data. RESULTS: The general tendency of respondents was to act to offset hypothetical changes in government spending. When asked to imagine that the government had reduced (or increased) its spending on cancer research, the general tendency of respondents was to state that they would give a larger (or smaller) allocation of their income tax to cancer research charities, and to increase (or reduce) their personal out-of-pocket donations to cancer research charities. However, most respondents' preferred allocation splits and changes in personal donations did not vary much from scenario to scenario. Many of the differences between scenarios were small and non-significant. CONCLUSIONS: The public's decisions about how much to donate to cancer research or other medical research charities are not greatly affected by (hypothetical) changes to government plans about the amount of public funding of cancer or other medical research.

Using patient-reported outcome measures to estimate cost-effectiveness of hip replacements in English hospitals.

OBJECTIVE: To estimate the average cost per quality adjusted life year (QALY) gained from hip surgery, and to examine the variation in that between hospitals. DESIGN: The transformation of patient-reported outcome measures (EQ-5D data) into QALYs, covering 25,463 NHS patient episodes between April 2009 and August 2010 from hospitals in England, using a model of future health change arising from a hip operation compared to a counterfactual of no operation. Hospital-level costs for hip procedures from the National Reference Costs data-set was used to calculate the hospitals' cost per QALY. SETTING: English hospitals treating NHS-funded patients undergoing hip replacement. PARTICIPANTS: NHS-funded patients undergoing primary hip replacement. MAIN OUTCOME MEASURE: Cost per QALY. RESULTS: Assuming some degradation in patients' health over the lifetime of the hip prosthesis, average health gain arising from a hip operation was 2.77 QALYs. For procedures paid for by the NHS but carried out in the independent sector the average gain was 2.97 QALYs. Average NHS hospital hip procedure costs were estimated to be £5844. The unweighted average cost per QALY for NHS hospitals was £2128. There were significant variations in cost per QALY between hospitals; most of this variation appears to be driven by variations in cost, not QALYs. CONCLUSIONS: Using the new patient-assessed health-related quality of life data combined with routine hospital-level cost data it is possible to estimate a procedure-based measure of efficiency for hospitals. The fact that variations in cost per QALY are strongly driven by variations in cost suggests that further work is needed to investigate the causes of cost variations per se--especially the quality of routine NHS cost data.

Using QALYs in cancer: a review of the methodological limitations.

The objective of this paper is to examine how well the QALY captures the health gains generated by cancer treatments, with particular focus on the methods for constructing QALYs preferred by the UK National Institute for Health and Clinical Excellence (NICE). Data were obtained using a keyword search of the MEDLINE database and a hand search of articles written by leading researchers in the subject area (with follow up of the references in these articles). Key arguments were discussed and developed at an oncology workshop in September 2009 at the Office of Health Economics. Three key issues emerged. First, the EQ-5D, NICE's preferred measure of health-related quality of life (QOL) in adults, has been found to be relatively insensitive to changes in health status of cancer patients. Second, the time trade-off, NICE's preferred technique for estimating the values of health states, involves making assumptions that are likely to be violated in end-of-life scenarios. Third, the practice of using valuations of members of the general population, as recommended by NICE, is problematic because such individuals typically display a misunderstanding of what it is really like for patients to live with cancer. Because of the way in which it is constructed, the QALY shows important limitations in terms of its ability to accurately capture the value of the health gains deemed important by cancer patients. A research agenda for addressing these limitations is proposed.