Equity and efficiency preferences of health policy makers in China--a stated preference analysis

Unravelling Elements of Value of Healthcare and Assessing their Importance Using Evidence from Two Discrete-Choice Experiments in England

BACKGROUND

Health systems are moving towards value-based care, implementing new care models that allegedly aim beyond patient outcomes. Therefore, a policy and academic debate is underway regarding the definition of value in healthcare, the inclusion of costs in value metrics, and the importance of each value element. This study aimed to define healthcare value elements and assess their relative importance (RI) to the public in England.

METHOD

Using data from 26 semi-structured interviews and a literature review, and applying decision-theory axioms, we selected a comprehensive and applicable set of value-based elements. Their RI was determined using two discrete choice experiments (DCEs) based on Bayesian D-efficient DCE designs, with one DCE incorporating healthcare costs expressed as income tax rise. Respondent preferences were analysed using mixed logit models.

RESULTS

Six value elements were identified: additional life-years, health-related quality of life, patient experience, target population size, equity, and cost. The DCE surveys were completed by 402 participants. All utility coefficients had the expected signs and were statistically significant (p < 0.05). Additional life-years (25.3%; 95% confidence interval [CI] 22.5-28.6%) and patient experience (25.2%; 95% CI 21.6-28.9%) received the highest RI, followed by target population size (22.4%; 95% CI 19.1-25.6%) and quality of life (17.6%; 95% CI 15.0-20.3%). Equity had the lowest RI (9.6%; 95% CI 6.4-12.1%), decreasing by 8.8 percentage points with cost inclusion. A similar reduction was observed in the RI of quality of life when cost was included.

CONCLUSION

The public prioritizes value elements not captured by conventional metrics, such as quality-adjusted life-years. Although cost inclusion did not alter the preference ranking, its inclusion in the value metric warrants careful consideration.

Does the Healthy China 2030 Policy Improve People's Health? Empirical Evidence Based on the Difference-in-Differences Approach

Background

The Healthy China 2030 (HC2030) policy is currently recognized as China's most significant and influential national health policy. However, despite its implementation in 2016, the policy's impact has yet to be comprehensively evaluated, particularly in relation to its effectiveness in enhancing population health and promoting public health equity.

Methods

We utilized the Difference-in-Differences (DiD) method to evaluate the impact of the HC2030. Our analysis utilized a panel dataset derived from five longitudinal surveys conducted by the China Family Panel Studies (CFPS).

Results

The implementation of HC2030 has improved the overall health status of residents, particularly in urban areas and the western and eastern regions. Mechanistic analysis has further unveiled that the policy's beneficial impact on health outcomes is attributed to a rise in physical activity frequency and the betterment of mental health. Additionally, female, married, and medically insured individuals have demonstrated a significant positive impact of the policy on their health outcomes.

Conclusion

Although the HC2030 appears to have effectively improved overall population health, it needs to promote equity in public health adequately. The study suggests adjustments are needed to address the unequal distribution of health outcomes between urban and rural areas and among different regions.

Public preferences in healthcare resource allocation: A discrete choice experiment in South Korea

OBJECTIVES

This study aimed to explore the public view on priority-setting criteria for healthcare resource allocation. Specifically, it investigates how the value of a quality-adjusted life year (QALY) varies depending on patient characteristics.

METHODS

A discrete choice experiment was conducted using an online sample of the general South Korean population. Respondents were presented with two competing treatment scenarios. The attributes of the scenarios were age at disease onset, life expectancy without treatment, life-years gain with treatment, health-related quality of life (HRQoL) without treatment, and HRQoL gains with treatment. Two hundred choice sets were generated and randomly allocated into 20 blocks. A conditional logit model was used to estimate the factors affecting the respondents' choices.

RESULTS

A total of 3,482 respondents completed the survey. The larger the QALY gain, the more likely it was that the scenario would be chosen but with a diminishing marginal value. Respondents prioritized 40-year-old patients over 5-year-olds and 5-year-olds over 70-year-olds and prioritized baseline HRQoL of 40% and 60% over 20%. Patients at the end of life were not preferred to those with a longer life expectancy.

CONCLUSION

Overall, respondents preferred health-maximizing options without explicit consideration for end-of-life patients or those with poor health. In addition, they revealed a kinked preference for patient age, prioritizing middle-aged patients over children and older people.

Priority setting in the German healthcare system: results from a discrete choice experiment

Worldwide, social healthcare systems must face the challenges of a growing scarcity of resources and of its inevitable distributional effects. Explicit criteria are needed to define the boundaries of public reimbursement decisions. As Germany stands at the beginning of such a discussion, more formalised priority setting procedures seem in order. Recent research identified multi-criteria decision analysis (MCDA) as a promising approach to inform and to guide decision-making in healthcare systems. In that regard, this paper aims to analyse the relative weight assigned to various criteria in setting priority interventions in Germany. A discrete choice experiment (DCE) was employed in 2015 to elicit equity and efficiency preferences of 263 decision makers, through six attributes. The experiment allowed us to rate different policy interventions based on their features in a composite league table (CLT). As number of potential beneficiaries, severity of disease, individual health benefits and cost-effectiveness are the most relevant criteria for German decision makers within the sample population, the results display an overall higher preference towards efficiency criteria. Specific high priority interventions are mental disorders and cardiovascular diseases.

Eliciting Trade-Offs Between Equity and Efficiency: A Methodological Scoping Review

OBJECTIVES

To identify differences in the approaches and results of studies that elicit equity-efficiency trade-offs that can inform equity-informative cost-effectiveness analysis for healthcare resource allocation.

METHODS

We searched Ovid (Medline), EconLit, and Scopus prior to June 25, 2021. Inclusion criteria were: (1) peer-reviewed or (2) gray literature; (3) published in English; (4) survey-based; (5) parameterized a social welfare function to quantify inequality aversion or (6) elicited a trade-off in equity and efficiency characteristics of health interventions. Exclusion criteria were: (1) studies that did not conduct a trade-off or (2) theoretical studies. We abstracted details on study methods, results, and limitations. Studies were grouped by following approach: (1) social welfare function or (2) preference ranking and distributional weighting. We described findings separately for each approach category.

RESULTS

Seventy-seven papers were included, 28 parameterized social welfare functions and 49 were classified as preference ranking and distributional weighting. Study methods were heterogeneous. Studies were conducted across 29 countries. Sample sizes and composition, survey methods and question framing varied. Preferences for equity were mixed. Across both approach categories: 39 studies were classified as clear evidence of inequality aversion; 33 found mixed evidence; and 4 had no evidence of aversion. Evidence of between and within-study heterogeneity was found. Preferences for equity may differ by gender, profession, political ideology, income, and education.

CONCLUSIONS

Substantial variability in study methods limit the direct comparability of findings and their use in equity-informed cost-effectiveness analysis. Future researches using representative samples that explore within and between country heterogeneity is needed.

Current Practices for Accounting for Preference Heterogeneity in Health-Related Discrete Choice Experiments: A Systematic Review

BACKGROUND

Accounting for preference heterogeneity is a growing analytical practice in health-related discrete choice experiments (DCEs). As heterogeneity may be examined from different stakeholder perspectives with different methods, identifying the breadth of these methodological approaches and understanding the differences are major steps to provide guidance on good research practices.

OBJECTIVES

Our objective was to systematically summarize current practices that account for preference heterogeneity based on the published DCEs related to healthcare.

METHODS

This systematic review is part of the project led by the Professional Society for Health Economics and Outcomes Research (ISPOR) health preference research special interest group. The systematic review conducted systematic searches on the PubMed, OVID, and Web of Science databases, as well as on two recently published reviews, to identify articles. The review included health-related DCE articles published between 1 January 2000 and 30 March 2020. All the included articles also presented evidence on preference heterogeneity analysis based on either explained or unexplained factors or both.

RESULTS

Overall, 342 of the 2202 (16%) articles met the inclusion/exclusion criteria for extraction. The trend showed that analyses of preference heterogeneity increased substantially after 2010 and that such analyses mainly examined heterogeneity due to observable or unobservable factors in individual characteristics. Heterogeneity through observable differences (i.e., explained heterogeneity) is identified among 131 (40%) of the 342 articles and included one or more interactions between an attribute variable and an observable characteristic of the respondent. To capture unobserved heterogeneity (i.e., unexplained heterogeneity), the studies largely estimated either a mixed logit (n = 205, 60%) or a latent-class logit (n = 112, 32.7%) model. Few studies (n = 38, 11%) explored scale heterogeneity or heteroskedasticity.

CONCLUSIONS

Providing preference heterogeneity evidence in health-related DCEs has been found as an increasingly used practice among researchers. In recent studies, controlling for unexplained preference heterogeneity has been seen as a common practice rather than explained ones (e.g., interactions), yet a lack of providing methodological details has been observed in many studies that might impact the quality of analysis. As heterogeneity can be assessed from different stakeholder perspectives with different methods, researchers should become more technically pronounced to increase confidence in the results and improve the ability of decision makers to act on the preference evidence.

Balancing Equity and Efficiency in the Allocation of Health Resources-Where Is the Middle Ground?

The notion of equity in health service delivery has been embodied in several of the Global Sustainable Development Goals (SDGs), especially the aspiration for universal health coverage (UHC). At the same time, escalating healthcare costs amidst dwindling resources continue to ignite discussions on the efficiency aspect of healthcare delivery at both operational and system levels. Therefore, health planners and managers have had to grapple with balancing the two, given limited resources and sophisticated population health needs. Undoubtedly, the concepts of equity and efficiency have overarching importance in healthcare. While efficiency dictates an 'economical' use of the limited healthcare resources, equity advocates their fair and ethical use. Some have leaned on this to argue that one has to be forgone in search of the other. In search of a 'middle ground', this paper explores the conceptual underpinnings of equity and efficiency in the context of healthcare resource allocation with some empirical examples from high-income and low- and middle-income settings. We conclude by arguing that equity and efficiency are, and ought to be, treated as complementary rather than conflicting considerations in distributing health resources. Each could be pursued without necessarily compromising the other-what matters is an explicit criterion of what will be 'equitable' in ensuring efficient allocation of resources, and on the other hand, what options will be considered more 'efficient' when equity objectives are pursued. Thus, equity can be achieved in an efficient way, while efficiency can drive the attainment of equity.

Impact of Education, Medical Services, and Living Conditions on Health: Evidence from China Health and Nutrition Survey

Education, medical services, and living conditions can influence individual health and health literacy. We used the 2015 China Health and Nutrition Survey data to analyze the impact of education, medical services, and living conditions on individual health by extending the Grossman model. As a result, using the instrumental variable (read, write, and draw) two-stage least square method, we found that education, medical services, and living conditions have a positive impact on individual health, both physical health and psychological health. Among them, medical services have the largest influence, followed by living conditions and education. In addition, the results are robust. However, individual characteristics, family income, and working status also affect individual health. Moreover, we observed heterogeneity in age, sex, and residence in the impact of education, medical services, and living conditions on individual health. In particular, the health of the rural elderly and elderly women is more sensitive to education, the medical services of middle-aged women and young men have a greater impact on their health, and the living conditions of the rural elderly and youth have a greater impact on their health. All the findings are helpful for optimizing the path of the Healthy China program.

Examining Equity Effects of Health Interventions in Cost-Effectiveness Analysis: A Systematic Review

OBJECTIVE

This systematic review aims to catalogue and describe published applications of equity-informative cost-effectiveness analysis (CEAs).

METHODS

Following PRISMA guidelines, we searched Medline for English-language, peer-reviewed CEAs published on or before August 2019. We included CEAs that evaluated 2 or more alternatives; explicitly mentioned equity as a consideration or decision-making principle; and applied an equity-informative CEA method to analyze or examine at least 1 equity criterion in an applied CEA. We extracted data on selected characteristics and analyzed reporting quality using the CHEERS checklist.

RESULTS

Fifty-four articles identified through a search and bibliography reviews met the inclusion criteria. All articles were published on or after 2010, with 80% published after 2015. Most studies evaluated primary prevention interventions in disease areas such as cancer, infectious diseases, and cardiovascular disease. Equity impact analysis alone was the most common equity-informative CEA (56%), followed by equity impact analysis with financial protection effects (30%). At least 11 different equity criteria have been used in equity-informative CEAs; socioeconomic status and race/ethnicity were used most frequently. Seventy-eight percent of studies reported finding "greater value" in an intervention after examining its distributional effects.

CONCLUSION

The number of equity-informative CEAs is increasing, and the wide range of equity criteria, diseases, interventions, settings, and populations represented suggests that broad application of these methods is feasible but will require further refinement. Inclusion of equity into CEAs may shift the value of evaluated interventions and can provide crucial additional information for decision makers.

Attitudes of patients and surgeons towards sham surgery trials: a protocol for a scoping review of attributes to inform a discrete choice experiment

INTRODUCTION

In order to properly evaluate the efficacy of orthopaedic procedures, rigorous, randomised controlled sham surgery trial designs are necessary. However, randomised controlled trials (RCTs) for surgery involving a placebo are ethically debated and difficult to conduct with many failing to reach their desired sample size and power. A review of the literature on barriers and enablers to recruitment, and patient and surgeon attitudes and preferences towards sham surgery trials, will help to determine the characteristics necessary for successful recruitment.

METHODS AND ANALYSIS

This review will scope the diverse literature surrounding sham surgery trials with the aim of informing a discrete choice experiment to empirically test patient and surgeon preferences for different sham surgery trial designs. The scoping review will be conducted in accordance with the methodological framework described in Arksey and O'Malley (2005) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols extension for Scoping Reviews. The review will be informed by a systematic search of Medline, Embase, PsycInfo, CINAHL and EconLit databases (from database inception to 21 June 2019), a Google Scholar search, and hand searching of reference lists of relevant studies or reviews. Studies or opinion pieces that involve patient, surgeon or trial characteristics, which influence the decision to participate in a trial, will be included. Study selection will be carried out independently by two authors with discrepancies resolved by consensus among three authors. Data will be charted using a standardised form, and results tabulated and narratively summarised with reference to the research questions of the review.

ETHICS AND DISSEMINATION

The findings from this review will inform the design of a discrete choice experiment around willingness to participate in surgical trials, the outcomes of which can inform decision and cost-effectiveness models of sham surgery RCTs. The qualitative information from this review will also inform patient-centred outcomes research. The review will be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

CRD42019133296.

The Impact of Public Health Expenditure on Health Outcomes in South Africa

Health holds an important position in maintaining economic development since it is both a prerequisite for and an outcome of economic development. This means that health contributes greatly to the attainment of sustainable development and health outcomes. The importance of health is demonstrated in the Millennium Development Goals (MDGs) where three of the eight goals are aimed at improving health outcomes. Despite progress made by other middle-income countries in achieving health-related MDGs, South Africa is still worse off in respect of health outcomes and experiences a challenge in attaining positive outcomes for these goals. This study’s main focus was to identify the association between public health expenditure and health outcomes in South Africa’s nine provinces from 2002 to 2016. The study implemented fixed effects and a random effects panel data estimation technique to control for time effects and individual provincial heterogeneity. This was followed by employing the Hausman specification test to identify the fixed effects model as the appropriate estimator for the study. The study also employed the seemingly unrelated regression (SUR) model and the least squares dummy variable (LSDV) model to examine the impact of public health expenditure on each province separately. The findings elucidated that the relationship between public health expenditure and health outcomes in South Africa varied across provinces depending on provincial management and infrastructure availability.

Criteria Used for Priority-Setting for Public Health Resource Allocation in Low- and Middle-Income Countries: A Systematic Review

OBJECTIVES

This systematic review aimed to identify criteria being used for priority setting for resource allocation decisions in low- and middle-income countries (LMICs). Furthermore, the included studies were analyzed from a policy perspective to understand priority setting processes in these countries.

METHODS

Searches were carried out in PubMed, Embase, Econlit, and Cochrane databases, supplemented with pre-identified Web sites and bibliographic searches of relevant papers. Quality appraisal of included studies was undertaken. The review protocol is registered in International Prospective Register of Systematic Reviews PROSPERO CRD42017068371.

RESULTS

Of 16,412 records screened by title and abstract, 112 papers were identified for full text screening and 44 studies were included in the final analysis. At an overall level, cost-effectiveness 52 percent (n = 22) and health benefits 45 percent (n = 19) were the most cited criteria used for priority setting for public health resource allocation. Inter-region (LMICs) and between various approaches (like health technology assessment, multi-criteria decision analysis (MCDA), accountability for reasonableness (AFR) variations among criteria were also noted. Our review found that MCDA approach was more frequently used in upper middle-income countries and AFR in lower-income countries for priority setting in health. Policy makers were the most frequently consulted stakeholders in all regions.

CONCLUSIONS AND RECOMMENDATIONS

Priority-setting criteria for health resource allocation decisions in LMICs largely comprised of cost-effectiveness and health benefits criteria at overall level. Other criteria like legal and regulatory framework conducive for implementation, fairness/ethics, and political considerations were infrequently reported and should be considered.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps

Background

The health area is one of the most affected systems on the perspective of decision-making with multiobjectives, thus becoming prone to errors in the final solution, however, multicriteria decision analysis (MDCA) appears as an aid tool for this process decision-making. Therefore,the present study aims to analyze and synthesize articles found in the literature, involing MCDA in health care, evaluating general issues and methodological aspects, structuring them in a single work.

Methods

Surveys in the bibliographic databases SCOPUS and PUBMED indicated 1852 documents on the subject, however after a careful verificatios, 66 studies were selected to be analyzed completely. The data extracted from the included articles were organized into a spreadsheet for the preparation of analysis, and the technique used was descriptive statistics.

Results

It was possible to identify a growth trend in the application of the MCDA in the health area, but no dominance was identified in relation to the authors of the publication and the periodicals where they are published, but some countries stood out in terms of the number of published researches, such as: Canada and Turkey. In defining the decision problem, and in defining criteria, the “literature” presented the greatest demand for those who wish to structure their decision problem. Finally, it was verified by the analysis of the problem, that the MCDA to solve the problems of ranking has comprehensive application and that there is a greater incidence in the use of the AHP and Logic methods Fuzzy.

Conclusion

With this, it is possible to observe, through the data of this review, that more than the multicriteria methods, the multicriteria decision model has been highlighted, also in the health area. In addition, the study can guide new applications and techniques using MCDA in the health care.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review

BACKGROUND

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood.

OBJECTIVE

We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications.

METHODS

We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist.

RESULTS

We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010.

CONCLUSIONS

LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Decision Making and Priority Setting: The Evolving Path Towards Universal Health Coverage

Health technology assessment (HTA) is widely viewed as an essential component in good universal health coverage (UHC) decision-making in any country. Various HTA tools and metrics have been developed and refined over the years, including systematic literature reviews (Cochrane), economic modelling, and cost-effectiveness ratios and acceptability curves. However, while the cost-effectiveness ratio is faithfully reported in most full economic evaluations, it is viewed by many as an insufficient basis for reimbursement decisions. Emotional debates about the reimbursement of cancer drugs, orphan drugs, and end-of-life treatments have revealed fundamental disagreements about what should and should not be considered in reimbursement decisions. Part of this disagreement seems related to the equity-efficiency tradeoff, which reflects fundamental differences in priorities. All in all, it is clear that countries aiming to improve UHC policies will have to go beyond the capacity building needed to utilize the available HTA toolbox. Multi-criteria decision analysis (MCDA) offers a more comprehensive tool for reimbursement decisions where different weights of different factors/attributes can give policymakers important insights to consider. Sooner or later, every country will have to develop their own way to carefully combine the results of those tools with their own priorities. In the end, all policymaking is based on a mix of facts and values.

Application of discrete choice experiments to enhance stakeholder engagement as a strategy for advancing implementation: a systematic review

Background

One of the key strategies to successful implementation of effective health-related interventions is targeting improvements in stakeholder engagement. The discrete choice experiment (DCE) is a stated preference technique for eliciting individual preferences over hypothetical alternative scenarios that is increasingly being used in health-related applications. DCEs are a dynamic approach to systematically measure health preferences which can be applied in enhancing stakeholder engagement. However, a knowledge gap exists in characterizing the extent to which DCEs are used in implementation science.

Methods

We conducted a systematic literature search (up to December 2016) of the English literature to identify and describe the use of DCEs in engaging stakeholders as an implementation strategy. We searched the following electronic databases: MEDLINE, Econlit, PsychINFO, and the CINAHL using mesh terms. Studies were categorized according to application type, stakeholder(s), healthcare setting, and implementation outcome.

Results

Seventy-five publications were selected for analysis in this systematic review. Studies were categorized by application type: (1) characterizing demand for therapies and treatment technologies (n = 32), (2) comparing implementation strategies (n = 22), (3) incentivizing workforce participation (n = 11), and (4) prioritizing interventions (n = 10). Stakeholders included providers (n = 27), patients (n = 25), caregivers (n = 5), and administrators (n = 2). The remaining studies (n = 16) engaged multiple stakeholders (i.e., combination of patients, caregivers, providers, and/or administrators). The following implementation outcomes were discussed: acceptability (n = 75), appropriateness (n = 34), adoption (n = 19), feasibility (n = 16), and fidelity (n = 3).

Conclusions

The number of DCE studies engaging stakeholders as an implementation strategy has been increasing over the past decade. As DCEs are more widely used as a healthcare assessment tool, there is a wide range of applications for them in stakeholder engagement. The DCE approach could serve as a tool for engaging stakeholders in implementation science.

Electronic supplementary material

The online version of this article (10.1186/s13012-017-0675-8) contains supplementary material, which is available to authorized users.

Efficiency and equity considerations in the preferences of health policy-makers in Israel

Background

There is a traditional tension in public policy between the maximization of welfare from given resources (efficiency) and considerations related to the distribution of welfare among the population and to social justice (equity). The aim of this paper is to measure the relative weights of the efficiency- and equity-enhancing criteria in the preferences of health policy-makers in Israel, and to compare the Israeli results with those of other countries.

Methods

We used the criteria of efficiency and equity which were adopted in a previous international study, adapted to Israel. The equity criteria, as defined in the international study, are: severity of the disease, age (young vs. elderly), and the extent to which the poor are subsidized. Efficiency is represented by the criteria: the potential number of beneficiaries, the extent of the health benefits to the patient, and the results of economic assessments (cost per QALY gained). We contacted 147 policy-makers, 65 of whom completed the survey (a response rate of 44%). Using Discrete Choice Experiment (DCE) methodology by 1000Minds software, we estimated the relative weights of these seven criteria, and predicted the desirability of technologies characterized by profiles of the criteria.

Results

The overall weight attached to the four efficiency criteria was 46% and that of the three equity criteria was 54%. The most important criteria were “financing of the technology is required so that the poor will be able to receive it” and the level of individual benefit. “The technology is intended to be used by the elderly” criterion appeared as the least important, taking the seventh place. Policy-makers who had experience as members of the Basket Committee appear to prefer efficiency criteria more than those who had never participated in the Basket Committee deliberations. While the efficiency consideration gained preference in most countries studied, Israel is unique in its balance between the weights attached to equity and efficiency considerations by health policy-makers.

Discussion

The study explored the trade-off between efficiency and equity considerations in the preferences of health policy-makers in Israel. The way these declarative preferences have been expressed in actual policy decisions remains to be explored.