Defining a Core Data Set for the Economic Evaluation of Precision Oncology.

OBJECTIVES: Precision oncology is generating vast amounts of multiomic data to improve human health and accelerate research. Existing clinical study designs and attendant data are unable to provide comparative evidence for economic evaluations. This lack of evidence can cause inconsistent and inappropriate reimbursement. Our study defines a core data set to facilitate economic evaluations of precision oncology. METHODS: We conducted a literature review of economic evaluations of next-generation sequencing technologies, a common application of precision oncology, published between 2005 and 2018 and indexed in PubMed (MEDLINE). Based on this review, we developed a preliminary core data set for informal expert feedback. We then used a modified-Delphi approach with individuals involved in implementation and evaluation of precision medicine, including 2 survey rounds followed by a final voting conference to refine the data set. RESULTS: Two authors determined that variation in published data elements was reached after abstraction of 20 economic evaluations. Expert consultation refined the data set to 83 unique data elements, and a multidisciplinary sample of 46 experts participated in the modified-Delphi process. A total of 68 elements (81%) were selected as required, spanning demographics and clinical characteristics, genomic data, cancer treatment, health and quality of life outcomes, and resource use. CONCLUSIONS: Cost-effectiveness analyses will fail to reflect the real-world impacts of precision oncology without data to accurately characterize patient care trajectories and outcomes. Data collection in accordance with the proposed core data set will promote standardization and enable the generation of decision-grade evidence to inform reimbursement.

Economic evaluation of meningococcal vaccines: considerations for the future.

In 2018, a panel of health economics and meningococcal disease experts convened to review methodologies, frameworks, and decision-making processes for economic evaluations of vaccines, with a focus on evaluation of vaccines targeting invasive meningococcal disease (IMD). The panel discussed vaccine evaluation methods across countries; IMD prevention benefits that are well quantified using current methods, not well quantified, or missing in current cost-effectiveness methodologies; and development of recommendations for future evaluation methods. Consensus was reached on a number of points and further consideration was deemed necessary for some topics. Experts agreed that the unpredictability of IMD complicates an accurate evaluation of meningococcal vaccine benefits and that vaccine cost-effectiveness evaluations should encompass indirect benefits, both for meningococcal vaccines and vaccines in general. In addition, the panel agreed that transparency in the vaccine decision-making process is beneficial and should be implemented when possible. Further discussion is required to ascertain: how enhancing consistency of frameworks for evaluating outcomes of vaccine introduction can be improved; reviews of existing tools used to capture quality of life; how indirect costs are considered within models; and whether and how the weighting of quality-adjusted life-years (QALY), application of QALY adjustment factors, or use of altered cost-effectiveness thresholds should be used in the economic evaluation of vaccines.

Differential item functioning in quality of life measurement: An analysis using anchoring vignettes.

Systematic differences in the ways that people use and interpret response categories (differential item functioning, DIF) can introduce bias when using self-assessments to compare health or quality of life across heterogeneous groups. This paper reports on an exploratory analysis involving the use of anchoring vignettes to identify DIF in a commonly used measure for assessing health-related quality of life - namely the EQ-5D. Using data from a bespoke (i.e. custom) survey that recruited a representative sample of 4300 respondents from the general Australian population in 2014 and 2015, we find that the assumptions of response consistency (RC) and vignette equivalence (VE) hold in a sub-sample of respondents aged 55-65 years (n = 914), which demonstrates that vignettes can appropriately identify DIF in EQ-5D reporting for this age group. We find that the EQ-5D is indeed subject to DIF, and that failure to account for DIF can lead to conclusions that are misleading when using the instrument to compare health or quality of life across heterogeneous groups. We also provide several important insights in terms of the identifying assumptions of RC and VE. We conclude that the implications of DIF could be of considerable importance, not only for outcomes research, but for funding decisions in healthcare more broadly given the strong reliance on patient-reported outcome measures in economic evaluations for health technology assessment.

Response-Scale Heterogeneity in the EQ-5D.

This paper discusses two types of response-scale heterogeneity, which may impact upon the EQ-5D. Response-scale heterogeneity in reporting occurs when individuals systematically differ in their use of response scales when responding to self-assessments. This type of heterogeneity is widely observed in relation to other self-assessed measures but is often overlooked with regard to the EQ-5D. Analogous to this, preference elicitation involving the EQ-5D could be subject to a similar type of heterogeneity, where variations across respondents may occur in the interpretations of the levels (response categories) being valued. This response-scale heterogeneity in preference elicitation may differ from variations in preferences for health states, which have been observed in the literature. This paper explores what these forms of response-scale heterogeneity may mean for the EQ-5D and the potential implications for researchers who rely on the instrument as a measure of health and quality of life. We identify situations where they are likely to be problematic and present potential avenues for overcoming these issues. Copyright © 2016 John Wiley & Sons, Ltd.

Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L.

PURPOSE: It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L. METHODS: A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs. RESULTS: Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar. CONCLUSIONS: When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably.

The Hospitalization Costs of Diabetes and Hypertension Complications in Zimbabwe: Estimations and Correlations.

Objective. Treating complications associated with diabetes and hypertension imposes significant costs on health care systems. This study estimated the hospitalization costs for inpatients in a public hospital in Zimbabwe. Methods. The study was retrospective and utilized secondary data from medical records. Total hospitalization costs were estimated using generalized linear models. Results. The median cost and interquartile range (IQR) for patients with diabetes, $994 (385-1553) mean $1319 (95% CI: 981-1657), was higher than patients with hypertension, $759 (494-1147) mean $914 (95% CI: 825-1003). Female patients aged below 65 years with diabetes had the highest estimated mean costs ($1467 (95% CI: 1177-1828)). Wound care had the highest estimated mean cost of all procedures, $2884 (95% CI: 2004-4149) for patients with diabetes and $2239 (95% CI: 1589-3156) for patients with hypertension. Age below 65 years, medical procedures (amputation, wound care, dialysis, and physiotherapy), the presence of two or more comorbidities, and being prescribed two or more drugs were associated with significantly higher hospitalization costs. Conclusion. Our estimated costs could be used to evaluate and improve current inpatient treatment and management of patients with diabetes and hypertension and determine the most cost-effective interventions to prevent complications and comorbidities.

Retrospective analysis of cancer survival across South-Western Victoria in Australia.

OBJECTIVE: This paper aims to describe cancer survival and examine association between survival and socio-demographic characteristics across Barwon South-Western region (BSWR) in Victoria, Australia. DESIGN: This study is based on the retrospective cohort database of patients accessing oncology services across BSWR. SETTING: Six rural and three urban hospital settings across the BSWR. PARTICIPANTS: The participants were patients who were diagnosed with cancer in 2009. MAIN OUTCOME MEASURES: Overall survival (OS) of participants was the main outcome measure. RESULTS: Total of 1778 eligible patients had four-year OS for all cancers combined of 59.7% (95% CI, 57.4-62.0). Improved OS was observed for patients in the upper socio-economic tertile (64.2%; 95% CI, 60.9-67.5) compared to the middle (59.3%; 95% CI, 55.5-63.1) and lowest tertiles (49.6%; 95% CI, 44.2-54.9) (P < 0.01). On multivariate analyses, higher socio-economic status remained a significant predictor of OS adjusting for gender, remoteness and age (HR [hazard ratio] 0.81; 95% CI 0.74-0.89; P < 0.01). Remoteness was significantly associated with improved OS after adjusting for age, gender and socio-economic status (HR 0.86; 95% CI, 0.77-0.97; P = 0.01). Older age ≥70 years compared to <70 years conferred inferior OS (HR 3.08; 95% CI, 2.64-3.59; P < 0.01). CONCLUSIONS: Our study confirmed improved survival outcomes for patients of higher socio-economic status and younger age. Future research to explain the unexpected survival benefit in patients who lived in more remote areas should examine factors including the correlation between geographical residence and eventual treatment facility as well as compare the BSWR care model to other regions' approaches.

Realising the Value of Linked Data to Health Economic Analyses of Cancer Care: A Case Study of Cancer 2015.

There is a growing appetite for large complex databases that integrate a range of personal, socio-demographic, health, genetic and financial information on individuals. It has been argued that 'Big Data' will provide the necessary catalyst to advance both biomedical research and health economics and outcomes research. However, it is important that we do not succumb to being data rich but information poor. This paper discusses the benefits and challenges of building Big Data, analysing Big Data and making appropriate inferences in order to advance cancer care, using Cancer 2015 (a prospective, longitudinal, genomic cohort study in Victoria, Australia) as a case study. Cancer 2015 has been linked to State and Commonwealth reimbursement databases that have known limitations. This partly reflects the funding arrangements in Australia, a country with both public and private provision, including public funding of private healthcare, and partly the legislative frameworks that govern data linkage. Additionally, linkage is not without time delays and, as such, achieving a contemporaneous database is challenging. Despite these limitations, there is clear value in using linked data and creating Big Data. This paper describes the linked Cancer 2015 dataset, discusses estimation issues given the nature of the data and presents panel regression results that allow us to make possible inferences regarding which patient, disease, genomic and treatment characteristics explain variation in health expenditure.

Burden attributable to Cardiometabolic Diseases in Zimbabwe: a retrospective cross-sectional study of national mortality data.

BACKGROUND: Cardiometabolic diseases (CMDs) are an important cause of mortality worldwide and the burden associated with them is increasing in Sub-Saharan Africa. The tracking of mortality helps support evidence based health policy and priority setting. Given the growing prevalence of non-communicable diseases in Zimbabwe, a study was designed to determine the mortality attributable to CMDs in Zimbabwe. METHODS: The study design was a retrospective cross-sectional analysis of national mortality from 1996 to 2007, collated by the Ministry of Health and Child Welfare in Zimbabwe. We employed generalized additive models to flexibly estimate the trend of the CMD mortality and a logistic regression model was used to find significant factors (cause of death according to the death certificate) of the CMD mortality and predict CMD mortality to 2040. RESULTS: CMDs accounted for 8.13% (95% CI: 8.08% - 8.18%) of all deaths during 1996 to 2007 (p = 0.005). During the study period CMD mortality rate increased by 29.4% (95% CI: 19.9% - 41.1%). The association between gender and CMD mortality indicated female mortality was higher for diabetes (p < 0.001), hypertensive disease (p < 0.001), CVD (p < 0.001) and pulmonary disease (p < 0.001), while male mortality was higher for ischaemic (p = 0.010) and urinary diseases (p < 0.001). There was no gender difference for endocrine disease (p = 0.893). Overall, females have 1.65% higher mortality than males (p < 0.001). CMD mortality is predicted to increase from 9.6 (95% CI: 8.0% - 11.1%) in 2015 to 13.7% (95% CI: 10.2% - 17.2%) in 2040 for males, and from 11.6% (95% CI: 10.2% - 12.9%) in 2015 to 16.2% (95% CI: 13.1% - 19.3%) in 2040 in females. CONCLUSION: The findings of this study indicate a growing prevalence of CMDs and related mortality in Zimbabwe. Health policy decisions and cost-effective preventive strategies to reduce the burden of CMDs are urgently required.

Cancer 2015: a longitudinal whole-of-system study of genomic cancer medicine.

Genomic cancer medicine promises revolutionary change in oncology. The impacts of 'personalized medicine', based upon a molecular classification of cancer and linked to targeted therapies, will extend from individual patient outcomes to the health economy at large. To address the 'whole-of-system' impact of genomic cancer medicine, we have established a prospective cohort of patients with newly diagnosed cancer in the state of Victoria, Australia, about whom we have collected a broad range of clinical, demographic, molecular, and patient-reported data, as well as data on health resource utilization. Our goal is to create a model for investigating public investment in genomic medicine that maximizes the cost:benefit ratio for the Australian community at large.

Operationalising the capability approach as an outcome measure in public health: The development of the OCAP-18.

There is growing interest in operationalising the capability approach to measure quality of life. This paper reports the results of a research project undertaken in 2007 that sought to reduce and refine a longer survey in order to provide a summary measure of wellbeing and capability in the realm of public health. The reduction and refinement of the questionnaire took place across a number of stages, using both qualitative (five focus group discussions and 17 in-depth interviews) and quantitative (secondary data analysis, N = 1048 and primary data collection using postal surveys and interviews, N = 45) approaches. The questionnaire was reduced from its original 60+ questions to 24 questions (including demographic questions). Each of Nussbaum's ten Central Human Capabilities are measured using one (or more) of the 18 specific capability items which are included in the questionnaire (referred to as the OCAP-18). Analysis of the questionnaire responses (N = 198) found that respondents differed with respect to the levels of capabilities they reported, and that these capabilities appear to be sensitive to one's gender, age, income and deprivation decile. An index of capability, estimated by assuming equal weight for each capability question, found that the average level of capability amongst respondents was 12.44 (range 3-17.75). This index was found to be highly correlated with a measure of health (EQ-5D) and wellbeing (global QoL), although some differences were apparent. This project operationalised the capability approach to produce an instrument to measure the effectiveness (and cost effectiveness) of public health interventions; the resulting OCAP-18 appears to be responsive and measure something supplementary to health and wellbeing, thus offers a promising addition to the current suite of outcome measures that are available.

Choice of Outcome Measure in an Economic Evaluation: A Potential Role for the Capability Approach.

The last decade has seen a renewed interest in Sen's capability approach; health economists have been instrumental in leading much of this work. One particular stream of research is the application of the approach to outcome measurement. To date, there have been a dozen attempts (some combined) to operationalise the approach, and produce an outcome measure that offers a broader evaluative space than health-related quality-of-life measures. Applications have so far been confined to public health, physical, mental health and social care interventions, but the capability approach could be of benefit to evaluations of pharmacotherapies and other technologies. This paper provides an introduction to the capability approach, reviews the measures that are available for use in an economic evaluation, including their current applications, and then concludes with a discussion of a number of issues that require further consideration before the approach is adopted more widely to inform resource allocation decisions.

A protocol for a discrete choice experiment: understanding preferences of patients with cancer towards their cancer care across metropolitan and rural regions in Australia.

INTRODUCTION: Medical decision-making in oncology is a complicated process and to date there are few studies examining how patients with cancer make choices with respect to different features of their care. It is also unknown whether patient choices vary by geographical location and how location could account for observed rural and metropolitan cancer differences. This paper describes an ongoing study that aims to (1) examine patient and healthcare-related factors that influence choices of patients with cancer; (2) measure and quantify preferences of patients with cancer towards cancer care using a discrete choice experiment (DCE) and (3) explore preference heterogeneity between metropolitan and rural locations. METHODS AND ANALYSIS: A DCE is being conducted to understand how patients with cancer choose between two clinical scenarios accounting for different patient and healthcare-related factors (and levels). Preliminary qualitative research was undertaken to guide the development of an appropriate DCE design including characteristics that are important and relevant to patients with cancer. A fractional factorial design using the D-efficiency criteria was used to estimate interactions among attributes. Multinomial logistic regression will be used for the primary DCE analysis and to control for sociodemographic and clinical characteristics. ETHICS AND DISSEMINATION: The Barwon Health Human Research Ethics Committee approved the study. Findings from the study will be presented in national/international conferences and peer-reviewed journals. Our results will form the basis of a feasibility study to inform the development of a larger scale study into preferences of patients with cancer and their association with cancer outcomes.

An exploration of parents' preferences for foot care in juvenile idiopathic arthritis: a possible role for the discrete choice experiment.

BACKGROUND: An increased awareness of patients' and parents' care preferences regarding foot care is desirable from a clinical perspective as such information may be utilised to optimise care delivery. The aim of this study was to examine parents' preferences for, and valuations of foot care and foot-related outcomes in juvenile idiopathic arthritis (JIA). METHODS: A discrete choice experiment (DCE) incorporating willingness-to-pay (WTP) questions was conducted by surveying 42 parents of children with JIA who were enrolled in a randomised-controlled trial of multidisciplinary foot care at a single UK paediatric rheumatology outpatients department. Attributes explored were: levels of pain; mobility; ability to perform activities of daily living (ADL); waiting time; referral route; and footwear. The DCE was administered at trial baseline. DCE data were analysed using a multinomial-logit-regression model to estimate preferences and relative importance of attributes of foot care. A stated-preference WTP question was presented to estimate parents' monetary valuation of health and service improvements. RESULTS: Every attribute in the DCE was statistically significant (p < 0.01) except that of cost (p = 0.118), suggesting that all attributes, except cost, have an impact on parents' preferences for foot care for their child. The magnitudes of the coefficients indicate that the strength of preference for each attribute was (in descending order): improved ability to perform ADL, reductions in foot pain, improved mobility, improved ability to wear desired footwear, multidisciplinary foot care route, and reduced waiting time. Parents' estimated mean annual WTP for a multidisciplinary foot care service was £1,119.05. CONCLUSIONS: In terms of foot care service provision for children with JIA, parents appear to prefer improvements in health outcomes over non-health outcomes and service process attributes. Cost was relatively less important than other attributes suggesting that it does not appear to impact on parents' preferences.

Anchoring vignettes for health comparisons: an analysis of response consistency.

PURPOSE: Self-rated health (SRH) is widely used to measure and compare the health status of different groups of individuals. However, SRH can suffer from heterogeneity in reporting styles, making health comparisons problematic. Anchoring vignettes is a promising technique for improving inter-group comparisons of SRH. A key identifying assumption of the approach is response consistency-that respondents rate themselves using the same underlying response scale that they rate the vignettes. Despite growing research into response consistency, it remains unclear how respondents rate vignettes and why respondents may not assess vignettes and themselves consistently. METHOD: Vignettes for the EQ-5D-5L were developed and included in an online survey. In-depth interviews were conducted with participants following survey completion. Response consistency was examined through qualitative analysis of the interview responses and quantitative coding of participants' thought processes. RESULTS: Our analysis showed that anchoring vignettes for the EQ-5D-5L is feasible, but that response consistency may not hold for some participants. Respondents are more likely to rate their own health and vignettes in the same way if presented with overall health state vignettes than single health dimension vignettes, and if they imagined themselves in the health state of the hypothetical individual. CONCLUSION: This research highlights opportunities to improve the design of anchoring vignettes in order to enhance response consistency. It additionally provides new evidence on the feasibility of employing anchoring vignettes for the EQ-5D-5L, which is promising for future work to address reporting heterogeneity in the EQ-5D-5L.