Seeing the NICE side of cost-effectiveness analysis: a qualitative investigation of the use of CEA in NICE technology appraisals

RCT-based Social Return on Investment (SROI) of a Home Exercise Program for People With Early Dementia Comparing In-Person and Blended Delivery Before and During the COVID-19 Pandemic

Regular exercise and community engagement may slow the rate of function loss for people with dementia. However, the evidence is uncertain regarding the cost-effectiveness and social return on investment (SROI) of home exercise with community referral for people with dementia. This study aimed to compare the social value generated from the in-person PrAISED program delivered before March 2020 with a blended PrAISED program delivered after March 2020. SROI methodology compared in-person and blended delivery formats of a home exercise program. Stakeholders were identified, a logic model was developed, outcomes were evidenced and valued, costs were calculated, and SROI ratios were estimated. Five relevant and material outcomes were identified: 3 outcomes for patient participants (fear of falling, health-related quality of life, and social connection); 1 outcome for carer participants (carer strain), and 1 outcome for the National Health Service (NHS) (health service resource use). Data were collected at baseline and at 12-month follow-up. The in-person PrAISED program generated SROI ratios ranging from £0.58 to £2.33 for every £1 invested. In-person PrAISED patient participants gained social value from improved health-related quality of life, social connection, and less fear of falling. In-person PrAISED carer participants acquired social value from less carer strain. The NHS gained benefit from less health care service resource use. However, the blended PrAISED program generated lower SROI ratios ranging from a negative ratio to £0.08:£1. Compared with the blended program, the PrAISED in-person program generated higher SROI ratios for people with early dementia. An in-person PrAISED intervention with community referral is likely to provide better value for money than a blended one with limited community referral, despite the greater costs of the former.Trial registration: ISRCTN Registry ISRCTN15320670.

The normative grounds for NICE decision-making: a narrative cross-disciplinary review of empirical studies

The National Institute for Health and Care Excellence (NICE) is the UK's primary health care priority-setter, responsible for advising the National Health Service on its adoption of health technologies. The normative basis for NICE's advice has long been the subject of public and academic interest, but the existing literature does not include any comprehensive summary of the factors observed to have substantively shaped NICE's recommendations. The current review addresses this gap by bringing together 29 studies that have explored NICE decision-making from different disciplinary perspectives, using a range of quantitative and qualitative methods. It finds that although cost-effectiveness has historically played a central role in NICE decision-making, 10 other factors (uncertainty, budget impact, clinical need, innovation, rarity, age, cause of disease, wider societal impacts, stakeholder influence and process factors) are also demonstrably influential and interact with one another in ways that are not well understood. The review also highlights an over-representation in the literature of appraisals conducted prior to 2009, according to methods that have since been superseded. It suggests that this may present a misleading view of the importance of allocative efficiency to NICE's current approach and illustrates the need for further up-to-date research into the normative grounds for NICE's decisions.

A Conceptual Framework for Life-Cycle Health Technology Assessment

OBJECTIVES

Health technology assessment (HTA) uses evidence appraisal and synthesis with economic evaluation to inform adoption decisions. Standard HTA processes sometimes struggle to (1) support decisions that involve significant uncertainty and (2) encourage continued generation of and adaptation to new evidence. We propose the life-cycle (LC)-HTA framework, addressing these challenges by providing additional tools to decision makers and improving outcomes for all stakeholders.

METHODS

Under the LC-HTA framework, HTA processes align to LC management. LC-HTA introduces changes in HTA methods to minimize analytic time while optimizing decision certainty. Where decision uncertainty exists, we recommend risk-based pricing and research-oriented managed access (ROMA). Contractual procurement agreements define the terms of reassessment and provide additional decision options to HTA agencies. LC-HTA extends value-of-information methods to inform ROMA agreements, leveraging routine, administrative data, and registries to reduce uncertainty.

RESULTS

LC-HTA enables the adoption of high-value high-risk innovations while improving health system sustainability through risk-sharing and reducing uncertainty. Responsiveness to evolving evidence is improved through contractually embedded decision rules to simplify reassessment. ROMA allows conditional adoption to obtain additional information, with confidence that the net value of that adoption decision is positive.

CONCLUSIONS

The LC-HTA framework improves outcomes for patients, sponsors, and payers. Patients benefit through earlier access to new technologies. Payers increase the value of the technologies they invest in and gain mechanisms to review investments. Sponsors benefit through greater certainty in outcomes related to their investment, swifter access to markets, and greater opportunities to demonstrate value.

Reference Case Methods for Expert Elicitation in Health Care Decision Making

BACKGROUND

The evidence used to inform health care decision making (HCDM) is typically uncertain. In these situations, the experience of experts is essential to help decision makers reach a decision. Structured expert elicitation (referred to as elicitation) is a quantitative process to capture experts' beliefs. There is heterogeneity in the existing elicitation methodology used in HCDM, and it is not clear if existing guidelines are appropriate for use in this context. In this article, we seek to establish reference case methods for elicitation to inform HCDM.

METHODS

We collated the methods available for elicitation using reviews and critique. In addition, we conducted controlled experiments to test the accuracy of alternative methods. We determined the suitability of the methods choices for use in HCDM according to a predefined set of principles for elicitation in HCDM, which we have also generated. We determined reference case methods for elicitation in HCDM for health technology assessment (HTA).

RESULTS

In almost all methods choices available for elicitation, we found a lack of empirical evidence supporting recommendations. Despite this, it is possible to define reference case methods for HTA. The reference methods include a focus on gathering experts with substantive knowledge of the quantities being elicited as opposed to those trained in probability and statistics, eliciting quantities that the expert might observe directly, and individual elicitation of beliefs, rather than solely consensus methods. It is likely that there are additional considerations for decision makers in health care outside of HTA.

CONCLUSIONS

The reference case developed here allows the use of different methods, depending on the decision-making setting. Further applied examples of elicitation methods would be useful. Experimental evidence comparing methods should be generated.

Developing a reference protocol for structured expert elicitation in health-care decision-making: a mixed-methods study

BACKGROUND

Many decisions in health care aim to maximise health, requiring judgements about interventions that may have higher health effects but potentially incur additional costs (cost-effectiveness framework). The evidence used to establish cost-effectiveness is typically uncertain and it is important that this uncertainty is characterised. In situations in which evidence is uncertain, the experience of experts is essential. The process by which the beliefs of experts can be formally collected in a quantitative manner is structured expert elicitation. There is heterogeneity in the existing methodology used in health-care decision-making. A number of guidelines are available for structured expert elicitation; however, it is not clear if any of these are appropriate for health-care decision-making.

OBJECTIVES

The overall aim was to establish a protocol for structured expert elicitation to inform health-care decision-making. The objectives are to (1) provide clarity on methods for collecting and using experts' judgements, (2) consider when alternative methodology may be required in particular contexts, (3) establish preferred approaches for elicitation on a range of parameters, (4) determine which elicitation methods allow experts to express uncertainty and (5) determine the usefulness of the reference protocol developed.

METHODS

A mixed-methods approach was used: systemic review, targeted searches, experimental work and narrative synthesis. A review of the existing guidelines for structured expert elicitation was conducted. This identified the approaches used in existing guidelines (the 'choices') and determined if dominant approaches exist. Targeted review searches were conducted for selection of experts, level of elicitation, fitting and aggregation, assessing accuracy of judgements and heuristics and biases. To sift through the available choices, a set of principles that underpin the use of structured expert elicitation in health-care decision-making was defined using evidence generated from the targeted searches, quantities to elicit experimental evidence and consideration of constraints in health-care decision-making. These principles, including fitness for purpose and reflecting individual expert uncertainty, were applied to the set of choices to establish a reference protocol. An applied evaluation of the developed reference protocol was also undertaken.

RESULTS

For many elements of structured expert elicitation, there was a lack of consistency across the existing guidelines. In almost all choices, there was a lack of empirical evidence supporting recommendations, and in some circumstances the principles are unable to provide sufficient justification for discounting particular choices. It is possible to define reference methods for health technology assessment. These include a focus on gathering experts with substantive skills, eliciting observable quantities and individual elicitation of beliefs. Additional considerations are required for decision-makers outside health technology assessment, for example at a local level, or for early technologies. Access to experts may be limited and in some circumstances group discussion may be needed to generate a distribution.

LIMITATIONS

The major limitation of the work conducted here lies not in the methods employed in the current work but in the evidence available from the wider literature relating to how appropriate particular methodological choices are.

CONCLUSIONS

The reference protocol is flexible in many choices. This may be a useful characteristic, as it is possible to apply this reference protocol across different settings. Further applied studies, which use the choices specified in this reference protocol, are required.

FUNDING

This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 37. See the NIHR Journals Library website for further project information. This work was also funded by the Medical Research Council (reference MR/N028511/1).

One-Way Sensitivity Analysis for Probabilistic Cost-Effectiveness Analysis: Conditional Expected Incremental Net Benefit

Although probabilistic analysis has become the accepted standard for decision analytic cost-effectiveness models, deterministic one-way sensitivity analysis continues to be used to meet the need of decision makers to understand the impact that changing the value taken by one specific parameter has on the results of the analysis. The value of a probabilistic form of one-way sensitivity analysis has been recognised, but the proposed methods are computationally intensive. Deterministic one-way sensitivity analysis provides decision makers with biased and incomplete information whereas, in contrast, probabilistic one-way sensitivity analysis (POSA) can overcome these limitations, an observation supported in this study by results obtained when these methods were applied to a previously published cost-effectiveness analysis to produce a conditional incremental expected net benefit curve. The application of POSA will provide decision makers with unbiased information on how the expected net benefit is affected by a parameter taking on a specific value and the probability that the specific value will be observed.

The Emerging Social Science Literature on Health Technology Assessment: A Narrative Review

BACKGROUND

Social scientists have paid increasing attention to health technology assessment (HTA). This paper provides an overview of existing social scientific literature on HTA, with a focus on sociology and political science and their subfields.

METHODS

Narrative review of key pieces in English.

RESULTS

Three broad themes recur in the emerging social science literature on HTA: the drivers of the establishment and concrete institutional designs of HTA bodies; the effects of institutionalized HTA on pricing and reimbursement systems and the broader society; and the social and political influences on HTA decisions.

CONCLUSION

Social scientists bring a focus on institutions and social actors involved in HTA, using primarily small-N research designs and qualitative methods. They provide valuable critical perspectives on HTA, at times challenging its otherwise unquestioned assumptions. However, they often leave aside questions important to the HTA practitioner community, including the role of culture and values. Closer collaboration could be beneficial to tackle new relevant questions pertaining to HTA.

Applying an Implementation Framework to the Use of Evidence from Economic Evaluations in Making Healthcare Decisions

BACKGROUND AND OBJECTIVE

There is a need for the application of theory in understanding the use of evidence from economic evaluations in healthcare decision making. The purpose of this study is to review the published literature on the use of evidence from economic evaluations for healthcare decision making and to map the findings to the Consolidated Framework for Implementation Research (CFIR).

METHODS

A systematic search strategy was used to identify studies investigating the factors that determine the use of evidence from economic evaluation in healthcare decision making. Barriers and facilitators identified in the included studies were mapped across the five CFIR domains, with the "intervention" referring to the use of economic evaluations in decision making. Gaps, inconsistencies and emergent relations were identified through the mapping process.

RESULTS

Fifty-three studies met eligibility criteria and were included in the review. The CFIR constructs associated with the Intervention Characteristics and those associated with the knowledge and beliefs of users of economic evaluations were widely cited in the identified barriers and facilitators. Other constructs from the CFIR had not been reported in the literature, such as 'organisational networks' and 'individual stage of change'. Most of the stages in the implementation process as described by the CFIR were reflected in the identified barriers and facilitators.

DISCUSSION

By categorising barriers and facilitators into domains, the CFIR provides a systematic approach to assess how these factors interact. Literature gaps in the literature regarding the use of economic evaluation in healthcare decision making were identified, specifically issues regarding organisational networks and the role of feedback.

CONCLUSIONS

Through mapping findings from studies of the use of evidence from economic evaluations in healthcare decision making, we present an implementation framework based on the CFIR for understanding the use of economic evaluations into practice.

Procedural justice and the individual participant in priority setting: Doctors' experiences

In this study we describe, synthesise, and discuss the experiences and views of doctors who participate as technical experts in health care priority setting, reflect on the ethical significance of the challenges to procedural and distributive justice they encounter, and propose an empirically derived practical approach to improving the fairness of the process. Between August 2015 and July 2016 we conducted semi-structured face-to-face interviews with 20 doctors in NSW, Australia, purposively selected on the basis of their participation in macroallocation. Participant selection, data collection, and analysis were carried out according to the principles of grounded moral analysis, an empirical bioethics methodology closely based on grounded theory. The doctors we interviewed attached ethical significance to a broad range of procedural concerns that militated both against the prospect of distributive justice and against their own wellbeing: unfair access to opportunities to participate in macroallocation, sexist behaviours and structures, rewards for rule-breakers, cynical and insincere practices, waste, duplication, and inefficiency, and being taken for granted. On the basis of our data, we hypothesise that the institutional conditions for macroallocation do not support the care of medical participants in deliberations. Evaluating our findings against the 'accountability for reasonableness' framework of Daniels and Sabin, we expose as incompatible with the conditions for procedural justice processes that treat participants in macroallocation unfairly or cause them to have moral unease about the justice of the enterprise. We suggest a supplementary procedure that positions commitment to the care and just treatment of participants as a foundation of any macroallocation procedure.

Methodological Issues in Economic Evaluations Submitted to the Pan-Canadian Oncology Drug Review (pCODR)

BACKGROUND

Public drug plans are faced with increasingly difficult funding decisions. In Canada, the pan-Canadian Oncology Drug Review (pCODR) makes funding recommendations to the provincial and territorial drug plans responsible for cancer drugs. Assessments of the economic models submitted by pharmaceutical manufacturers are publicly reported.

OBJECTIVES

The main objective of this research was to identify recurring methodological issues in economic models submitted to pCODR for funding reviews. The secondary objective was to explore whether there exists any observed relationships between reported methodological issues and funding recommendations made by pCODR's expert review committee.

METHODS

Publicly available Economic Guidance Reports from July 2011 (inception) until June 2014 for drug reviews with a final funding recommendation (N = 34) were independently examined by two authors. Major methodological issues from each review were abstracted and grouped into nine main categories. Each issue was also categorized based on perception of the reviewer's actions to manage it.

RESULTS

The most commonly reported issues involved costing (59% of reviews), time horizon (56%), and model structure (36%). Several types of issues were identified that usually could not be resolved, such as quality of clinical data or uncertainty with indirect comparisons. Issues with costing or choice of utility estimates could usually be addressed or explored by reviewers. No statistically significant relationship was found between any methodological issue and funding recommendations from the expert review committee.

CONCLUSIONS

The findings provide insights that can be used by parties who submit or review economic evidence for continuous improvement and consistency in economic modeling, reporting, and decision making.

The evolution of the cancer formulary review in Canada: Can centralization improve the use of economic evaluation?

Public reimbursement of drugs is a costly proposition for health care systems. Decisions to add drugs to the public formulary are often guided by review processes and committees. The evolution of the formulary review process in Canada's publicly funded health system is characterized by increased centralization and systematization. In the past, the review of evidence and recommendation was conducted at the regional level, but was replaced with the pan-Canadian Oncology Drug Review in 2011. We assess the extent to which centralization and systematization of the review process have responded to past challenges, focusing on the use of economic evaluation in the process. Past challenges with economic evaluation experienced by regionalized review committees were identified from literature and qualitative data collected in the province of Nova Scotia. We categorize these using a typology with a macro-, meso, and micro-level hierarchy, which provides a useful framework for understanding at which level change is required, and who has the authority to influence change. Using grounded theory methods, we identify approaches used by Nova Scotia past committee members to compensate for perceived shortcomings of the process. These include an undue reliance on other committee members, on the multidisciplinarity of the committee, and on past decisions. Using a policy analysis approach, we argue that centralization and systematization of the review process only partially address the shortcomings of the previous regionalized process. Lessons from Canada can inform policy discussions across all health systems, where similar challenges with the formulary review process have been identified. © 2016 The Authors. The International Journal of Health Planning and Management published by John Wiley & Sons Ltd.

Economic Evaluation in Ethiopian Healthcare Sector Decision Making: Perception, Practice and Barriers

BACKGROUND

Globally, economic evaluation (EE) is increasingly being considered as a critical tool for allocating scarce healthcare resources. However, such considerations are less documented in low-income countries, such as in Ethiopia. In particular, to date there has been no assessment conducted to evaluate the perception and practice of and barriers to health EE.

OBJECTIVE

This paper assesses the use and perceptions of EE in healthcare decision-making processes in Ethiopia.

METHODS

In-depth interview sessions with decision makers/healthcare managers and program coordinators across six regional health bureaus were conducted. A qualitative analysis approach was conducted on three thematic areas.

RESULTS

A total of 57 decision makers/healthcare managers were interviewed from all tiers of the health sector in Ethiopia, ranging from the Federal Ministry of Health down to the lower levels of the health facility pyramid. At the high-level healthcare decision-making tier, only 56 % of those interviewed showed a good understanding of EE when explaining in terms of cost and consequences of alternative courses of action and value for money. From the specific program perspective, 50 % of the prevention of mother-to-child transmission of HIV/AIDS program coordinators indicated the relevance of EE to program planning and decision making. These respondents reported a limited application of costing studies on the HIV/AIDS prevention and control program, which were most commonly used during annual planning and budgeting.

CONCLUSION

The study uncovered three important barriers to growth of EE in Ethiopia: a lack of awareness, a lack of expertise and skill, and the traditional decision-making culture.

The Role of Qualitative Research Methods in Discrete Choice Experiments

Background. The use of qualitative research (QR) methods is recommended as good practice in discrete choice experiments (DCEs). This study investigated the use and reporting of QR to inform the design and/or interpretation of healthcare-related DCEs and explored the perceived usefulness of such methods. Methods. DCEs were identified from a systematic search of the MEDLINE database. Studies were classified by the quantity of QR reported (none, basic, or extensive). Authors (n = 91) of papers reporting the use of QR were invited to complete an online survey eliciting their views about using the methods. Results. A total of 254 healthcare DCEs were included in the review; of these, 111 (44%) did not report using any qualitative methods; 114 (45%) reported “basic” information; and 29 (11%) reported or cited “extensive” use of qualitative methods. Studies reporting the use of qualitative methods used them to select attributes and/or levels (n = 95; 66%) and/or pilot the DCE survey (n = 26; 18%). Popular qualitative methods included focus groups (n = 63; 44%) and interviews (n = 109; 76%). Forty-four studies (31%) reported the analytical approach, with content (n = 10; 7%) and framework analysis (n = 5; 4%) most commonly reported. The survey identified that all responding authors (n = 50; 100%) found that qualitative methods added value to their DCE study, but many (n = 22; 44%) reported that journals were uninterested in the reporting of QR results. Conclusions. Despite recommendations that QR methods be used alongside DCEs, the use of QR methods is not consistently reported. The lack of reporting risks the inference that QR methods are of little use in DCE research, contradicting practitioners’ assessments. Explicit guidelines would enable more clarity and consistency in reporting, and journals should facilitate such reporting via online supplementary materials.

Methodological considerations in service use assessment for children and youth with mental health conditions; issues for economic evaluation

Economic evaluations are increasingly used in decision-making. Accurate measurement of service use is critical to economic evaluation. This qualitative study, based on expert interviews, aims to identify best approaches to service use measurement for child mental health conditions, and to identify problems in current methods. Results suggest considerable agreement on strengths (e.g., availability of accurate instruments to measure service use) and weaknesses, (e.g., lack of unit prices for services outside the health sector) or alternative approaches to service use measurement. Experts also identified some unresolved problems, for example the lack of uniform definitions for some mental health services.

The Role of Decision Models in Health Care Policy: A Case Study

BACKGROUND

In 2009, the Centers for Medicare and Medicaid Services (CMS) underwent a National Coverage Determination on computed tomography colonography (CTC) to screen for colorectal cancer. The Cancer Intervention & Surveillance Network developed decision models to inform this decision. The purpose of our study was to investigate the role of models in this decision.

METHODS

We performed a descriptive case study. We conducted semistructured telephone interviews with members of the CMS coverage and analysis group (CAG) and Medicare Coverage and Analysis Advisory Committee (MEDCAC) panelists. Informed by previously published literature, we developed a coding scheme to analyze interview transcripts, MEDCAC meeting transcripts, and the final CMS decision memo.

RESULTS

Four members of the CAG and 8 MEDCAC panelists were interviewed. The total number of codes across all study documents was 772. We found evidence that decision makers believed in the adequacy of models to inform decision making. In interview transcripts, the code Models Are Adequate to Inform was more frequent than the code Models Are Inadequate to Inform (47 times v. 5). Discussion of model conceptualization dominated the MEDCAC meeting (Model Conceptualization assigned 113 times) and was frequently discussed during interviews (Model Conceptualization assigned 84 times). We also found evidence that the models helped to focus the policy discussion. Across study documents, the codes Focus on Cost, Focus on Clinical-Health Impact, and Focus on Inadequacy of Evidence Base were assigned 99, 98, and 97 times, respectively.

CONCLUSIONS

Decision makers involved in the CTC decision believed in the adequacy of models to inform coverage decisions. The model played a role in focusing the CTC coverage policy discussion.

Using CART to Identify Thresholds and Hierarchies in the Determinants of Funding Decisions

There is much interest in understanding decision-making processes that determine funding outcomes for health interventions. We use classification and regression trees (CART) to identify cost-effectiveness thresholds and hierarchies in the determinants of funding decisions. The hierarchical structure of CART is suited to analyzing complex conditional and nonlinear relationships. Our analysis uncovered hierarchies where interventions were grouped according to their type and objective. Cost-effectiveness thresholds varied markedly depending on which group the intervention belonged to: lifestyle-type interventions with a prevention objective had an incremental cost-effectiveness threshold of $2356, suggesting that such interventions need to be close to cost saving or dominant to be funded. For lifestyle-type interventions with a treatment objective, the threshold was much higher at $37,024. Lower down the tree, intervention attributes such as the level of patient contribution and the eligibility for government reimbursement influenced the likelihood of funding within groups of similar interventions. Comparison between our CART models and previously published results demonstrated concurrence with standard regression techniques while providing additional insights regarding the role of the funding environment and the structure of decision-maker preferences.

Bridging the gap: exploring the barriers to using economic evidence in healthcare decision making and strategies for improving uptake

Evidence from economic evaluations is often not used to inform healthcare policy despite being well regarded by policy makers and physicians. This article employs the accessibility and acceptability framework to review the barriers to using evidence from economic evaluation in healthcare policy and the strategies used to overcome these barriers. Economic evaluations are often inaccessible to policymakers due to the absence of relevant economic evaluations, the time and cost required to conduct and interpret economic evaluations, and lack of expertise to evaluate quality and interpret results. Consistently reported factors that limit the translation of findings from economic evaluations into healthcare policy include poor quality of research informing economic evaluations, assumptions used in economic modelling, conflicts of interest, difficulties in transferring resources between sectors, negative attitudes to healthcare rationing, and the absence of equity considerations. Strategies to overcome these barriers have been suggested in the literature, including training, structured abstract databases, rapid evaluation, reporting checklists for journals, and considering factors other than cost effectiveness in economic evaluations, such as equity or budget impact. The factors that prevent or encourage decision makers to use evidence from economic evaluations have been identified, but the relative importance of these factors to decision makers is uncertain.

Use of cost-effectiveness data in priority setting decisions: experiences from the national guidelines for heart diseases in Sweden

BACKGROUND

The inclusion of cost-effectiveness data, as a basis for priority setting rankings, is a distinguishing feature in the formulation of the Swedish national guidelines. Guidelines are generated with the direct intent to influence health policy and support decisions about the efficient allocation of scarce healthcare resources. Certain medical conditions may be given higher priority rankings i.e. given more resources than others, depending on how serious the medical condition is. This study investigated how a decision-making group, the Priority Setting Group (PSG), used cost-effectiveness data in ranking priority setting decisions in the national guidelines for heart diseases.

METHODS

A qualitative case study methodology was used to explore the use of such data in ranking priority setting healthcare decisions. The study addressed availability of cost-effectiveness data, evidence understanding, interpretation difficulties, and the reliance on evidence. We were also interested in the explicit use of data in ranking decisions, especially in situations where economic arguments impacted the reasoning behind the decisions.

RESULTS

This study showed that cost-effectiveness data was an important and integrated part of the decision-making process. Involvement of a health economist and reliance on the data facilitated the use of cost-effectiveness data. Economic arguments were used both as a fine-tuning instrument and a counterweight for dichotomization. Cost-effectiveness data were used when the overall evidence base was weak and the decision-makers had trouble making decisions due to lack of clinical evidence and in times of uncertainty. Cost-effectiveness data were also used for decisions on the introduction of new expensive medical technologies.

CONCLUSION

Cost-effectiveness data matters in decision-making processes and the results of this study could be applicable to other jurisdictions where health economics is implemented in decision-making. This study contributes to knowledge on how cost-effectiveness data is used in actual decision-making, to ensure that the decisions are offered on equal terms and that patients receive medical care according their needs in order achieve maximum benefit.

Public funding of pharmaceuticals in The Netherlands: investigating the effect of evidence, process and context on CVZ decision-making

The College Voor Zorgverzekeringen (CVZ) provides guidance to the Dutch healthcare system on funding and use of new pharmaceutical technologies. This study examined the impact of evidence, process and context factors on CVZ decisions in 2004-2009. A data set of CVZ decisions pertaining to pharmaceutical technologies was created, including 29 variables extracted from published information. A three-category outcome variable was used, defined as the decision to 'recommend', 'restrict' or 'not recommend' a technology. Technologies included in list 1A/1B or on the expensive drug list were considered recommended; those included in list 2 or for which patient co-payment is required were considered restricted; technologies not included on any reimbursement list were classified as 'not recommended'. Using multinomial logistic regression, the relative contribution of explanatory variables on CVZ decisions was assessed. In all, 244 technology appraisals (256 technologies) were analysed, with 51%, of technologies recommended, 33% restricted and 16% not recommended by CVZ for funding. The multinomial model showed significant associations (p ≤ 0.10) between CVZ outcome and several variables, including: (1) use of an active comparator and demonstration of statistical superiority of the primary endpoint in clinical trials, (2) pharmaceutical budget impact associated with introduction of the technology, (3) therapeutic indication and (4) prevalence of the target population. Results confirm the value of a comprehensive and multivariate approach to understanding CVZ decision-making.

STAR—People-Powered Prioritization

The aim of cost effectiveness analysis (CEA) is to inform the allocation of scarce resources. CEA is routinely used in assessing the cost-effectiveness of specific health technologies by agencies such as the National Institute for Health and Clinical Excellence (NICE) in England and Wales. But there is extensive evidence that because of barriers of accessibility and acceptability, CEA has not been used by local health planners in their annual task of allocating fixed budgets to a wide range of types of health care. This paper argues that these planners can use Socio Technical Allocation of Resources (STAR) for that task. STAR builds on the principles of CEA and the practice of program budgeting and marginal analysis. STAR uses requisite models to assess the cost-effectiveness of all interventions considered for resource reallocation by explicitly applying the theory of health economics to evidence of scale, costs, and benefits, with deliberation facilitated through an interactive social process of engaging key stakeholders. In that social process, the stakeholders generate missing estimates of scale, costs, and benefits of the interventions; develop visual models of their relative cost-effectiveness; and interpret the results. We demonstrate the feasibility of STAR by showing how it was used by a local health planning agency of the English National Health Service, the Isle of Wight Primary Care Trust, to allocate a fixed budget in 2008 and 2009.

Health utility scores in Alzheimer's disease: differences based on calculation with American and Canadian preference weights

OBJECTIVE

Health utility scores quantify health-related quality-of-life (HRQOL) in Alzheimer's disease (AD). These scores are calculated by using preference weights derived from general population samples. We recruited persons with AD and their primary informal caregivers and examined differences in health utility scores calculated by using two sets of published preference weights.

METHODS

We recruited participants from nine clinics across Canada and administered the EuroQol five-dimensional (EQ-5D) questionnaire HRQOL instrument. We converted participants' EQ-5D questionnaire responses into two sets of health utility scores by using US and Canadian preference weights. We assessed agreement between sets by using the intraclass correlation coefficient. Bland-Altman plots depicted individual-level differences between sets.

RESULTS

For 216 persons with AD and their caregivers, mean health utility scores were higher when calculated with US instead of Canadian preference weights (P < 0.0001). The intraclass correlation coefficient (95% CI) was 0.79 (0.05-0.93) in the persons with AD group and 0.83 (0.30-0.94) in the caregiver group. Ninety-five percent of the individual differences in utility score fell between -0.16 and 0.03 for persons with AD and -0.15 and 0.05 for caregivers. Forty-three percent of these differences exceeded a minimum clinically important threshold of 0.074.

CONCLUSIONS

In AD studies, researchers should calculate health utility scores by using preference weights obtained in the general population of their country of interest. Using weights from other countries' populations could bias the utilities and adversely affect the results of economic evaluations of AD treatments.

Perspectives on econometric modelling to inform policy: a UK qualitative case study of minimum unit pricing of alcohol

Background: Novel policy interventions may lack evaluation-based evidence. Considerations to introduce minimum unit pricing (MUP) of alcohol in the UK were informed by econometric modelling (the ‘Sheffield model’). We aim to investigate policy stakeholders’ views of the utility of modelling studies for public health policy. Methods: In-depth qualitative interviews with 36 individuals involved in MUP policy debates (purposively sampled to include civil servants, politicians, academics, advocates and industry-related actors) were conducted and thematically analysed. Results: Interviewees felt familiar with modelling studies and often displayed detailed understandings of the Sheffield model. Despite this, many were uneasy about the extent to which the Sheffield model could be relied on for informing policymaking and preferred traditional evaluations. A tension was identified between this preference for post hoc evaluations and a desire for evidence derived from local data, with modelling seen to offer high external validity. MUP critics expressed concern that the Sheffield model did not adequately capture the ‘real life’ world of the alcohol market, which was conceptualized as a complex and, to some extent, inherently unpredictable system. Communication of modelling results was considered intrinsically difficult but presenting an appropriate picture of the uncertainties inherent in modelling was viewed as desirable. There was general enthusiasm for increased use of econometric modelling to inform future policymaking but an appreciation that such evidence should only form one input into the process. Conclusion: Modelling studies are valued by policymakers as they provide contextually relevant evidence for novel policies, but tensions exist with views of traditional evaluation-based evidence.

Decision maker perceptions of resource allocation processes in Canadian health care organizations: a national survey

BACKGROUND

Resource allocation is a key challenge for healthcare decision makers. While several case studies of organizational practice exist, there have been few large-scale cross-organization comparisons.

METHODS

Between January and April 2011, we conducted an on-line survey of senior decision makers within regional health authorities (and closely equivalent organizations) across all Canadian provinces and territories. We received returns from 92 individual managers, from 60 out of 89 organizations in total. The survey inquired about structures, process features, and behaviours related to organization-wide resource allocation decisions. We focus here on three main aspects: type of process, perceived fairness, and overall rating.

RESULTS

About one-half of respondents indicated that their organization used a formal process for resource allocation, while the others reported that political or historical factors were predominant. Seventy percent (70%) of respondents self-reported that their resource allocation process was fair and just over one-half assessed their process as 'good' or 'very good'. This paper explores these findings in greater detail and assesses them in context of the larger literature.

CONCLUSION

Data from this large-scale cross-jurisdictional survey helps to illustrate common challenges and areas of positive performance among Canada's health system leadership teams.

Link between process and appraisal in coverage decisions: an analysis with structural equation modeling

BACKGROUND

To achieve fair-coverage decision making, both material criteria and criteria of procedural justice have been proposed. The relationship between these is still unclear.

OBJECTIVE

To analyze hypotheses underlying the assumption that more assessment, transparency, and participation have a positive impact on the reasonableness of coverage decisions.

METHODS

We developed a structural equation model in which the process components were considered latent constructs and operationalized by a set of observable indicators. The dependent variable "reasonableness" was defined by the relevance of clinical, economic, and other ethical criteria in technology appraisal (as opposed to appraisal based on stakeholder lobbying). We conducted an Internet survey among conference participants familiar with coverage decisions of third-party payers in industrialized countries between 2006 and 2011. Partial least squares path modeling (PLS-PM) was used, which allows analyzing small sample sizes without distributional assumptions. Data on 97 coverage decisions from 15 countries and 40 experts were used for model estimation.

RESULTS

Stakeholder participation (regression coefficient [RC] =0.289; P = 0.005) and scientific rigor of assessment (RC = 0.485; P < 0.001) had a significant influence on the construct of reasonableness. The path from transparency to reasonableness was not significant (RC = 0.289; P = 0.358). For the reasonableness construct, a considerable share of the variance was explained (R (2) = 0.44). Biases from missing data and nesting effects were assessed through sensitivity analyses. Limitations. The results are limited by a small sample size and the overrepresentation of some decision makers.

CONCLUSIONS

Rigorous assessment and intense stakeholder participation appeared effective in promoting reasonable decision making, whereas the influence of transparency was not significant. A sound evidence base seems most important as the degree of scientific rigor of assessment had the strongest effect.

Decision making by NICE: examining the influences of evidence, process and context

The National Institute for Health and Clinical Excellence (NICE) provides guidance to the National Health Service (NHS) in England and Wales on funding and use of new technologies. This study examined the impact of evidence, process and context factors on NICE decisions in 2004–2009. A data set of NICE decisions pertaining to pharmaceutical technologies was created, including 32 variables extracted from published information. A three-category outcome variable was used, defined as the decision to ‘recommend’, ‘restrict’ or ‘not recommend’ a technology. With multinomial logistic regression, the relative contribution of explanatory variables on NICE decisions was assessed. A total of 65 technology appraisals (118 technologies) were analysed. Of the technologies, 27% were recommended, 58% were restricted and 14% were not recommended by NICE for NHS funding. The multinomial model showed significant associations (p ⩽ 0.10) between NICE outcome and four variables: (i) demonstration of statistical superiority of the primary endpoint in clinical trials by the appraised technology; (ii) the incremental cost-effectiveness ratio (ICER); (iii) the number of pharmaceuticals appraised within the same appraisal; and (iv) the appraisal year. Results confirm the value of a comprehensive and multivariate approach to understanding NICE decision making. New factors affecting NICE decision making were identified, including the effect of clinical superiority, and the effect of process and socio-economic factors.

Transparency vs. closed-door policy: do process characteristics have an impact on the outcomes of coverage decisions? A statistical analysis

The aim of this study was to analyze influences of process- and technology-related characteristics on the outcomes of coverage decisions. Using survey data on 77 decisions from 13 countries, we examined whether outcomes differ by 14 variables that describe components of decision-making processes and the technology. We analyzed the likelihood of committees covering a technology, i.e. positive (including partial coverage) vs. negative coverage decisions. We performed non-parametric univariate tests and binomial logistic regression with a stepwise variable selection procedure. We identified a negative association between a positive decision and whether the technology is a prescribed medicine (p=0.0097). Other significant influences on a positive decision outcome included one disease area (p=0.0311) and whether a technology was judged to be (cost-)effective (p<0.0001). The first estimation of the logistic regression yielded a quasi-complete separation for technologies that were clearly judged (cost-)effective. In uncertain decisions, a higher number of stakeholders involved in voting (odds ratio=2.52; p=0.03) increased the likelihood of a positive outcome. The results suggest that decisions followed the lines of evidence-based decision-making. Despite claims for transparent and participative decision-making, the phase of evidence generation seemed most critical as decision-makers usually adopted the assessment recommendations. We identified little impact of process configurations.

Factors relating to effectiveness data use in healthcare management

Purpose

The aim of this study is to produce information concerning factors which may hamper or promote the use of effectiveness data in secondary health care middle and upper management. Additionally, the study aims to acquire knowledge of the ways in which the managers would generate effectiveness data for use in their own work.

Design/methodology/approach

The study was conducted by interviewing department directors, chief medical officers and directors of nursing (n=38) in the surgical, medical and psychiatric divisions of the five largest hospital districts in Finland.

Findings

The use of effectiveness data in management was hampered by factors relating to research, managerial work and the organization. Factors relating to the production of effectiveness data, managerial behaviour and a universal demand for evidence‐based operations were considered conducive to the use of such information. Managers would cultivate the use of effectiveness data by improving its accessibility, usability and visibility.

Practical implications

The findings may help healthcare organizations in developing the use of effectiveness data in their decision‐making.

Originality/value

The paper addresses managers’ willingness to apply effectiveness data in decision‐making although the present quality, reliability and accessibility of effectiveness data do not meet the managers’ needs. The use of effectiveness data in management can be influenced by enhancing organizational patterns of action and supporting managerial decision‐making.

‘Innovation’ in health care coverage decisions: All talk and no substance?

There has been much discussion recently about ‘innovation’, or more precisely the lack of it, in pharmaceuticals and devices in health care. The concern has been expressed by national guideline bodies, such as the Common Drugs Review in Canada and the National Institute for Health& Clinical Excellence in the UK, applying strict cost-effectiveness criteria in their decision-making and, therefore, failing adequately to recognize the full benefits that come from innovation. In order to explore the legitimacy of such claims, we first define innovation, and second, explore the basis for assuming an independent and separable social value associated with innovation. We conclude that demands relating to innovation, such as relaxation of thresholds and premium prices for innovatory products, remain hollow until we have a compelling case on the demand side for a separable social value on ‘innovation’. We see no such case currently.

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes

Background

Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare.

Methods

Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM.

Results

After modification by dropping two indicators that showed poor measures in the measurement models’ quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of ‘transparency’, ‘participation’, ‘scientific rigour’ and ‘reasonableness’.

Conclusions

The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies.

Field testing of a multicriteria decision analysis (MCDA) framework for coverage of a screening test for cervical cancer in South Africa

BACKGROUND

Systematic and transparent approaches to priority setting are needed, particularly in low-resource settings, to produce decisions that are sound and acceptable to stakeholders. The EVIDEM framework brings together Health Technology Assessment (HTA) and multi-criteria decision analysis (MCDA) by proposing a comprehensive set of decision criteria together with standardized processes to support decisionmaking. The objective of the study was to field test the framework for decisionmaking on a screening test by a private health plan in South Africa.

METHODS

Liquid-based cytology (LBC) for cervical cancer screening was selected by the health plan for this field test. An HTA report structured by decision criterion (14 criteria organized in the MCDA matrix and 4 contextual criteria) was produced based on a literature review and input from the health plan. During workshop sessions, committee members 1) weighted each MCDA decision criterion to express their individual perspectives, and 2) to appraise LBC, assigned scores to each MCDA criterion on the basis of the by-criterion HTA report.Committee members then considered the potential impacts of four contextual criteria on the use of LBC in the context of their health plan. Feedback on the framework and process was collected through discussion and from a questionnaire.

RESULTS

For 9 of the MCDA matrix decision criteria, 89% or more of committee members thought they should always be considered in decisionmaking. Greatest weights were given to the criteria "Budget impact", "Cost-effectiveness" and "Completeness and consistency of reporting evidence". When appraising LBC for cervical cancer screening, the committee assigned the highest scores to "Relevance and validity of evidence" and "Disease severity". Combination of weights and scores yielded a mean MCDA value estimate of 46% (SD 7%) of the potential maximum value. Overall, the committee felt the framework brought greater clarity to the decisionmaking process and was easily adaptable to different types of health interventions.

CONCLUSIONS

The EVIDEM framework was easily adapted to evaluating a screening technology in South Africa, thereby broadening its applicability in healthcare decision making.

Systematic Review and Empirical Comparison of Contemporaneous EQ-5D and SF-6D Group Mean Scores

Background. Group mean estimates and their underlying distributions are the focus of assessment for cost and outcome variables in economic evaluation. Research focusing on the comparability of alternative preference-based measures of health-related quality of life has typically focused on analysis of individual-level data within specific clinical specialties or community-based samples. Purpose. To explore the relationship between group mean scores for the EQ-5D and SF-6D across the utility scoring range. Methods. Studies were identified via a systematic search of 13 online electronic databases, a review of reference lists of included papers, and hand searches of key journals. Studies were included if they reported contemporaneous mean EQ-5D and SF-6D health state scores. All (sub)group comparisons of group mean EQ-5D and SF-6D scores identifiable from text, tables, or figures were extracted from identified studies. A total of 921 group mean comparisons were extracted from 56 studies. The nature of the relationship between the paired scores was examined using ranked scatter graphs and analysis of agreement. Results. Systematic differences in group mean estimates were observed at both ends of the utility scale. At the lower (upper) end of the scale, the SF-6D (EQ-5D) provides higher mean utility estimates. Conclusions. These findings show that group mean EQ-5D and SF-6D scores are not directly comparable. This raises serious concerns about the cross-study comparability of economic evaluations that differ in the choice of preference-based measures, although the review focuses on 2 of the available instruments only. Further work is needed to address the practical implications of noninterchangeable utility estimates for cost-per-QALY estimates and decision making.

Bridging Health Technology Assessment (HTA) and Efficient Health Care Decision Making with Multicriteria Decision Analysis (MCDA)

Background. Health care decision making is complex and requires efficient and explicit processes to ensure transparency and consistency of factors considered. Objectives. To pilot an adaptable decision-making framework incorporating multicriteria decision analysis (MCDA) in health technology assessment (HTA) with a pan-Canadian group of policy and clinical decision makers and researchers appraising 10 medicines covering 6 therapeutic areas. Methods. An appraisal group was convened and participants were asked to express their individual perspectives, independently of the medicines, by assigning weights to each criterion of the MCDA core model: disease severity, size of population, current practice and unmet needs, intervention outcomes (efficacy, safety, patient reported), type of health benefit, economics, and quality of evidence. Participants then assigned performance scores for each medicine using available evidence synthesized in a “by-criterion” HTA report covering each of the MCDA CORE model criteria. MCDA estimates of perceived value were calculated by combining normalized weights and scores. Feedback on the approach was collected through structured discussion. Results. Relative weights on criteria varied widely, reflecting the diverse perspectives of participants. Scores for each criterion provided a performance measure, highlighting strengths and weaknesses of each medicine. MCDA estimates of perceived value ranged from 0.42 to 0.64 across medicines, providing comprehensive measures incorporating a large spectrum of criteria. Participants reported that the framework provided an efficient approach to systematic consideration in a pragmatic format of the multiple elements guiding decision, including criteria and values (MCDA core model) and evidence (HTA “by-criterion” report). Conclusions. This proof-of-concept study demonstrated the usefulness of incorporating MCDA in HTA to support transparent and systematic appraisal of health care interventions. Further research is needed to advance MCDA-based approaches to more effective healthcare decision making.

Pharmaceutical priority setting and the use of health economic evaluations: a systematic literature review

OBJECTIVES

To investigate which factors and criteria are used in priority setting of pharmaceuticals, in what contexts health economic evaluations are used, and barriers to the use of health economic evaluations at micro, meso, and macro health-care levels.

METHODS

The search for empirical articles was based on the MeSH index (Medical Substance Heading), including the search terms "economic evaluation," "cost-effectiveness analysis," "cost-utility analysis," "cost-benefit analysis," "pharmacoeconomic," AND "drug cost(s)," AND "eligibility determination," AND "decision-making," AND "rationing," AND formulary. The following databases were searched: PubMed, EconLit, Cochrane, Web of Science, CINAHL, and PsycINFO. More than 3100 studies were identified, 31 of which were included in this review.

RESULTS

The use of health economic evaluations at all three health-care levels was investigated in three countries (United States [US], United Kingdom [UK], and Sweden). Postal and telephone survey methods dominated (n = 17) followed by interviews (n = 13), document analysis (n = 10), and observations of group deliberations (n = 9). The cost-effectiveness criterion was most important at the macro level. A number of contextual uses of health economic evaluations were identified, including importantly the legitimizing of decisions, structuring the priority-setting process, and requesting additional budgets to finance expensive pharmaceuticals.

CONCLUSION

Factors that seem to support the increased use of health economic evaluations are well-developed frameworks for evaluations, the presence of health economic skills, and an explicit priority-setting process. Differences in how economic evaluations are used at macro, meso, and micro levels are attributed to differences in the preconditions at each level.

Fixing the game: are between-silo differences in funding arrangements handicapping some interventions and giving others a head-start?

Given resource scarcity, not all potentially beneficial health services can be funded. Choices are made, if not explicitly, implicitly as some health services are funded and others are not. But what are the primary influences on those choices? We sought to test whether funding decisions are linked to cost effectiveness and to quantify the influence of funding arrangements and community values arguments. We tested this via empirical analysis of 245 Australian health-care interventions for which cost-effectiveness estimates had been published. The likelihood of government funding was modelled as a function of cost effectiveness, patient/target group characteristics, intervention characteristics and publication characteristics, using multiple regression analysis. We found that higher cost effectiveness ratios were a significant predictor of funding rejection, but that cost effectiveness was not related to the level of funding. Intervention characteristics linked to funding and delivery arrangements and community values arguments were significant predictors of funding outcomes. Our analysis supports the hypothesis that funding and delivery arrangements influence both whether an intervention is funded and funding level; even after controlling for community values and cost effectiveness. It suggests that adopting partial priority setting processes without regard to opportunity cost can have the perverse effect of compounding allocative inefficiencies.

Qualitative methodologies in health-care priority setting research

Priority setting research in health economics has traditionally employed quantitative methodologies and been informed by post-positivist philosophical assumptions about the world and the nature of knowledge. These approaches have been rewarded with well-developed and validated tools. However, it is now commonly noted that there has been limited uptake of economic analysis into actual priority setting and resource allocation decisions made by health-care systems. There seem to be substantial organizational and political barriers. The authors argue in this paper that understanding and addressing these barriers will depend upon the application of qualitative research methodologies. Some efforts in this direction have been attempted; however these are theoretically under-developed and seldom rooted in any of the established qualitative research traditions. Two such approaches - narrative inquiry and discourse analysis - are highlighted here. These are illustrated with examples drawn from a real-world priority setting study. The examples demonstrate how such conceptually powerful qualitative traditions produce distinctive findings that offer unique insight into organizational contexts and decision-maker behavior. We argue that such investigations offer untapped benefits for the study of organizational priority setting and thus should be pursued more frequently by the health economics research community.

Has the time come for cost-effectiveness analysis in US health care?

Cost-effectiveness analysis (CEA) is a powerful analytic tool for assessing the value of health care interventions but it is a method used sparingly in the US. Despite its growing acceptance internationally and its endorsement in the academic literature, most policy analysts have assumed that US decision makers will resist using CEA to inform coverage decisions. This study sought to clarify the extent to which CEA is understood and accepted by US decision makers, including regulators, private and public insurers, and purchasers, and to identify their points of difficulty with its use. We conducted half-day workshops with a sample of six California-based health care organizations that spanned a range of public and private perspectives regarding coverage of health care services. Each workshop included an overview of CEA methods, a priority-setting exercise that asked participants (acting as ‘social decision makers’) to rank condition treatment pairs prior to and following provision of cost-effectiveness information; and a facilitated discussion of obstacles and opportunities for using CEA in their own organizations. Pre and post-questionnaires inquired as to obstacles toward implementing CEA, attitudes toward rationing, and views on the use of CEA in Medicare and in private insurance coverage decision-making. In post-workshop surveys major obstacles identified included: fears of litigation, concerns about the quality and accuracy of studies that were commercially sponsored, and failure of CEAs to address shorter horizon cost implications. Over 90% of participants felt that CEA should be used as an input to Medicare coverage decisions and 75% supported its use in such decisions by private insurance plans. Despite the wide acceptance of CEA, at the conclusion of the workshop, 40% of the sample remained uncomfortable with support of ‘rationing’ per se. We suggest that how cost-effectiveness analysis is framed will have important implications for its acceptability to US decision makers.

Effectiveness in political—administrative decision-making in specialized healthcare

Aim: To investigate the occurrence of the word ``effectiveness'' in the political—administrative decision-making minutes in specialized healthcare as presented to board and council meetings by top management teams. Methods: The occurrence and intended use of ``effectiveness'' were identified from all council and board meeting minutes (n = 190) of five Finnish university hospital districts in 2001 and 2006. Data were collected from the Internet pages of the hospital districts. For analysis, deductive content analysis combining qualitative and quantitative methodologies was used. Results: The word ``effectiveness'' occurred in the planning, organization and evaluation of service activities and in the definitions and justifications for the goal states of research and development work. Although objectives were justified by effectiveness, the occurrence and use of the term were not grounded on proven effectiveness but rather represented an ideal being pursued. Use of the word ``effectiveness'' increased from 2001 to 2006, particularly in the political—administrative decision-making of large hospital districts. This article gives useful information regarding the benefits of effectiveness in political—administrative decision-making. Conclusions: Healthcare is under pressure to increase effectiveness, which is manifested by rhetoric presentations of the term in the political—administrative decision-making in specialized healthcare. There is a need for focused collection and systematic follow-up of easily available effectiveness information in healthcare.

Cost-effectiveness of pioglitazone in type 2 diabetes patients with a history of macrovascular disease: a German perspective

BACKGROUND

The aim of this study was to project health-economic outcomes relevant to the German setting for the addition of pioglitazone to existing treatment regimens in patients with type 2 diabetes, evidence of macrovascular disease and at high risk of cardiovascular events.

METHODS

Event rates corresponding to macrovascular outcomes from the Prospective Pioglitazone Clinical Trial in Macrovascular Events (PROactive) study of pioglitazone were used with a modified version of the CORE Diabetes Model to simulate outcomes over a 35-year time horizon. Direct medical costs were accounted from a healthcare payer perspective in year 2005 values. Germany specific costs were applied for patient treatment, hospitalization and management. Both costs and clinical benefits were discounted at 5.0% per annum.

RESULTS

Over patient lifetimes pioglitazone treatment improved undiscounted life expectancy by 0.406 years and improved quality-adjusted life expectancy by 0.120 quality-adjusted life years (QALYs) compared to placebo. Direct medical costs (treatment plus complication costs) were marginally higher for pioglitazone treatment and calculation of the incremental cost-effectiveness ratio (ICER) produced a value of euro13,294 per QALY gained with the pioglitazone regimen versus placebo. Acceptability curve analysis showed that there was a 78.2% likelihood that pioglitazone would be considered cost-effective in Germany, using a "good value for money" threshold of euro50,000 per QALY gained. Sensitivity analyses showed that the results were most sensitive to changes in the simulation time horizon. After adjustment for the potential stabilization of pancreatic beta-cell function with pioglitazone treatment, the ICER was euro6,667 per QALY gained for pioglitazone versus placebo.

CONCLUSION

The findings of this modelling analysis indicated that, for patients with a history of macrovascular disease, addition of pioglitazone to existing therapy reduces the long-term cumulative incidence of diabetes-complications at a cost that would be considered to represent good value for money in the German setting.

Economic evaluation of the decisions of the Israeli Public Committee for updating the National List of Health Services in 2006/2007

OBJECTIVE

The Public Committee (PC), which decides on the inclusion and ranking of new technologies in the Israeli List of Health Services facing a given budget, does not explicitly consider the results of economic evaluations of the technologies discussed. The present article includes an ex post economic examination of the PC's 2006/2007 decisions.

METHODS

The cost per quality-adjusted life-year (QALY) (CPQ) values of the technologies approved and rejected were retrieved from national health technologies assessments and the professional literature.

RESULTS

CPQ values were found for 40 technologies out of the 52 that were approved by the PC, and for 26 out of 42 randomly sampled among those rejected. The technologies approved for inclusion produce QALYs in a cheaper way, in general, than those rejected. A CPQ of about 50,000 new Israeli shekels (NIS) (15,500 USDPPP [purchasing power parity adjusted U.S. dollars]) is identified as the best discriminating value between approved and rejected technologies. The agreement between the PC's ranking of the approved technologies and the ranking by CPQ is low, and the only significant determinant of the Committee's ranking is the number of patients expected to benefit from the technology.

CONCLUSIONS

Although not considering CPQ data explicitly, the PC tends, in fact, to approve technologies with relatively low CPQ. In ranking the approved technologies, however, the PC tries to maximize the number of persons expected to benefit from the additional budget even at the expense of possibly giving up cheaper QALYs. The size of the budget should be determined in accordance with an Israeli value of QALY and Israeli values of the CPQ of the technologies submitted for inclusion.

Self-reported healthcare decision-makers' attitudes towards economic evaluations of medical technologies

BACKGROUND

Increasing costs have generated concern among governments and healthcare providers who have realized the need for cost containment measures and more efficient resource utilization. Health economics is one potential source of information that can make healthcare more efficient.

SCOPE

This review article summarizes the published literature on self-reported attitudes of healthcare decision-makers towards economic evaluations of medical technologies and examines the extent to which economic evaluations are used in health policy decisions.

METHODS

A systematic literature review of published English language studies was conducted using MEDLINE, EMBASE, and HEED from January 1995 to December 2007.

FINDINGS

Fifty-five articles investigated the use of economic evaluations on three levels of decision-making: central, local, and physician level. Results indicate the use of economic evaluation information increased from limited/minor to moderate use. The influence of economic evaluations increased with the level of centralization of healthcare system. Barriers to use health economics research varied across levels and included health economics research-related barriers such as timely availability, lack of credibility, insufficient methodological quality and decision-context-related barriers including limited decision makers' knowledge, inflexibility in healthcare budgets and variability among healthcare organizations.

CONCLUSIONS

For consistent policy-making it is important that similar recommendations for cost-effective interventions and programs are developed at all levels and that implementation is promoted by incorporating the appropriate incentives in healthcare provision.