Willingness to participate in combination screening for lung cancer, chronic obstructive pulmonary disease and cardiovascular disease in four European countries

OBJECTIVES

Lung cancer screening (LCS), using low-dose computed tomography (LDCT), can be more efficient by simultaneously screening for chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD), the Big-3 diseases. This study aimed to determine the willingness to participate in (combinations of) Big-3 screening in four European countries and the relative importance of amendable participation barriers.

METHODS

An online cross-sectional survey aimed at (former) smokers aged 50-75 years elicited the willingness of individuals to participate in Big-3 screening and used analytical hierarchy processing (AHP) to determine the importance of participation barriers.

RESULTS

Respondents were from France (n = 391), Germany (n = 338), Italy (n = 399), and the Netherlands (n = 342), and consisted of 51.2% men. The willingness to participate in screening was marginally influenced by the diseases screened for (maximum difference of 3.1%, for Big-3 screening (73.4%) vs. lung cancer and COPD screening (70.3%)) and by country (maximum difference of 3.7%, between France (68.5%) and the Netherlands (72.3%)). The largest effect on willingness to participate was personal perceived risk of lung cancer. The most important barriers were the missed cases during screening (weight 0.19) and frequency of screening (weight 0.14), while diseases screened for (weight 0.11) ranked low.

CONCLUSIONS

The difference in willingness to participate in LCS showed marginal increase with inclusion of more diseases and limited variation between countries. A marginal increase in participation might result in a marginal additional benefit of Big-3 screening. The amendable participation barriers are similar to previous studies, and the new criterion, diseases screened for, is relatively unimportant.

CLINICAL RELEVANCE STATEMENT

Adding diseases to combination screening modestly improves participation, driven by personal perceived risk. These findings guide program design and campaigns for lung cancer and Big-3 screening. Benefits of Big-3 screening lie in long-term health and economic impact, not participation increase.

KEY POINTS

• It is unknown whether or how combination screening might affect participation. • The addition of chronic obstructive pulmonary disease and cardiovascular disease to lung cancer screening resulted in a marginal increase in willingness to participate. • The primary determinant influencing individuals' engagement in such programs is their personal perceived risk of the disease.

Chasing Certainty After Cardiac Arrest: Can a Technological Innovation Solve a Moral Dilemma?

When information on a coma patient’s expected outcome is uncertain, a moral dilemma arises in clinical practice: if life-sustaining treatment is continued, the patient may survive with unacceptably poor neurological prospects, but if withdrawn a patient who could have recovered may die. Continuous electroencephalogram-monitoring (cEEG) is expected to substantially improve neuroprognostication for patients in coma after cardiac arrest. This raises expectations that decisions whether or not to withdraw will become easier. This paper investigates that expectation, exploring cEEG’s impacts when it becomes part of a socio-technical network in an Intensive Care Unit (ICU). Based on observations in two ICUs in the Netherlands and one in the USA that had cEEG implemented for research, we interviewed 25 family members, healthcare professionals, and surviving patients. The analysis focuses on (a) the way patient outcomes are constructed, (b) the kind of decision support these outcomes provide, and (c) how cEEG affects communication between professionals and relatives. We argue that cEEG can take away or decrease the intensity of the dilemma in some cases, while increasing uncertainty for others. It also raises new concerns. Since its actual impacts furthermore hinge on how cEEG is designed and implemented, we end with recommendations for ensuring responsible development and implementation.

Quantitative Benefit-Risk Assessment: State of the Practice Within Industry

BACKGROUND

Benefit-risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit-risk assessment (qBRA) methods.

METHODS

Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit-risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis.

RESULTS

While most surveyed companies had applied qBRA, application was limited to a small number of assets-primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances.

CONCLUSION

qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so.

Selecting Image-Guided Surgical Technologies in Oncology: A Surgeon's Perspective

BACKGROUND

To improve surgical performance, image-guided (IG) technologies are increasingly introduced. Yet, it is unknown which oncological procedures yield most value from these technologies. This study aimed to select the most promising IG technology per oncologic indication.

METHODS

An Analytic Hierarchical Process was used to evaluate three IG technologies: navigation, optical imaging, and augmented reality, in five oncologic indications compared with usual care. Sixteen decision criteria were selected. The relative importance of the criteria and the expected performance of the technologies were evaluated among surgeons. The combination of these scores gives the expected value per technology.

RESULTS

On criteria level, sparing critical tissue (9%-18%) and reducing the risk of local recurrence (11%-27%) were most important. Navigation was preferred in three indications-removal of lymph nodes (42%), liver (47%), and rectal tumors (33%). In removing rectal tumors, optical imaging was equally preferred (34%). In removing breast and tongue tumors, no technology was clearly preferred.

CONCLUSIONS

In selecting IG technologies, especially optical and navigation technologies are expected to add value in addition to usual care. Further development of those technologies for the preferred indications seems valuable. Multi-attribute analysis showed to be useful in prioritization of conducting clinical studies and steer research and development initiatives.

Heterogeneity in Preferences for Anti-coagulant Use in Atrial Fibrillation: A Latent Class Analysis

Introduction

Recent reviews on patients’ preferences towards attributes of oral anti-coagulant therapy have shown that preference for convenience of therapy is heterogeneous. In this study, we used a novel approach—latent class analysis (LCA)—to assess heterogeneity.

Methods

We developed a health preference survey that consisted of 12 discrete choice questions. The following attributes of convenience were included: intake frequency; need for regular coagulation monitoring; diet or drug interactions; relation between medication and food intake; and pill type. Background questions about gender, age, current therapy [i.e., direct-acting oral anti-coagulant (DOAC) or vitamin K antagonist (VKA)], self-reported medication adherence, and pill burden were included. Mixed logit analysis (MLA) and LCA were performed. The scale-adjusted LCA model with two scale classes and four preference classes emerged as the model with the best fit and interpretability.

Results

A total of 508 patients with non-valvular atrial fibrillation from five European countries (Germany, Italy, Spain, France, and the UK) were surveyed in August 2017. The most important attributes were need for monitoring (37%) and intake frequency (27%). Patient preferences were significantly influenced by country, gender, and current anti-coagulant therapy. Four different preference classes of patients were identified in the LCA. First, most patients (57%) were in the “no need for regular coagulation monitoring” class. Current DOAC users and patients who were the least adherent to therapy were more likely to prefer no coagulation monitoring. Second, 20% of patients were in the “balanced” class of patients. Current VKA users with moderate adherence were more likely to be in this class. Patients who reported the lowest adherence were most likely in the “once daily, interactions likely” class (16%). Fourth, current VKA users and highly adherent patients were most likely to prefer therapies with a need for regular coagulation monitoring (7%).

Conclusions

This study demonstrated significant preference heterogeneity among patients with atrial fibrillation and linked these preferences to differences in background characteristics. Country of residence and currently prescribed therapy influenced patient preferences in both the MLA and LCA models.

Electronic supplementary material

The online version of this article (10.1007/s40271-020-00420-z) contains supplementary material, which is available to authorized users.

Multicriteria Decision Analysis to Support Health Technology Assessment Agencies: Benefits, Limitations, and the Way Forward

OBJECTIVE

Recent years have witnessed an increased interest in the use of multicriteria decision analysis (MCDA) to support health technology assessment (HTA) agencies for setting healthcare priorities. However, its implementation to date has been criticized for being "entirely mechanistic," ignoring opportunity costs, and not following best practice guidelines. This article provides guidance on the use of MCDA in this context.

METHODS

The present study was based on a systematic review and consensus development. We developed a typology of MCDA studies and good implementation practice. We reviewed 36 studies over the period 1990 to 2018 on their compliance with good practice and developed recommendations. We reached consensus among authors over the course of several review rounds.

RESULTS

We identified 3 MCDA study types: qualitative MCDA, quantitative MCDA, and MCDA with decision rules. The types perform differently in terms of quality, consistency, and transparency of recommendations on healthcare priorities. We advise HTA agencies to always include a deliberative component. Agencies should, at a minimum, undertake qualitative MCDA. The use of quantitative MCDA has additional benefits but also poses design challenges. MCDA with decision rules, used by HTA agencies in The Netherlands and the United Kingdom and typically referred to as structured deliberation, has the potential to further improve the formulation of recommendations but has not yet been subjected to broad experimentation and evaluation.

CONCLUSION

MCDA holds large potential to support HTA agencies in setting healthcare priorities, but its implementation needs to be improved.

What Does the Public Want? Structural Consideration of Citizen Preferences in Health Care Coverage Decisions

Background. Multi-criteria decision analysis can improve the legitimacy of health care reimbursement decisions by taking societal preferences into account when weighting decision criteria. This study measures the relative importance of health care coverage criteria according to the Belgian general public and policy makers. Criteria are structured into three domains: therapeutic need, societal need, and new treatments’ added value. Methods. A sample of 4,288 citizens and 161 policy makers performed a discrete choice experiment. Data were analyzed using multinomial logistic regression analysis. Level-independent criteria weights were determined using the log-likelihood method. Results. Both the general public and policy makers gave the highest weight to quality of life in the appraisal of therapeutic need (0.43 and 0.53, respectively). The general public judged life expectancy (0.14) as less important than inconvenience of current treatment (0.43), unlike decision makers (0.32 and 0.15). The general public gave more weight to “impact of a disease on public expenditures” (0.65) than to “prevalence of the disease” (0.56) when appraising societal need, whereas decision makers’ weights were 0.44 and 0.56, respectively. When appraising added value, the general public gave similar weights to “impact on quality of life” and “impact on prevalence” (0.37 and 0.36), whereas decision makers judged “impact on quality of life” (0.39) more important than “impact on prevalence” (0.29). Both gave the lowest weight to impact on life expectancy (0.14 and 0.21). Limitations. Comparisons between the general public and policy makers should be treated with caution because the policy makers’ sample size was small. Conclusion. Societal preferences can be measured and used as decision criteria weights in multi-criteria decision analysis. This cannot replace deliberation but can improve the transparency of health care coverage decision processes.

Does technique matter; a pilot study exploring weighting techniques for a multi-criteria decision support framework

Background

There is an increased interest in the use of multi-criteria decision analysis (MCDA) to support regulatory and reimbursement decision making. The EVIDEM framework was developed to provide pragmatic multi-criteria decision support in health care, to estimate the value of healthcare interventions, and to aid in priority-setting. The objectives of this study were to test 1) the influence of different weighting techniques on the overall outcome of an MCDA exercise, 2) the discriminative power in weighting different criteria of such techniques, and 3) whether different techniques result in similar weights in weighting the criteria set proposed by the EVIDEM framework.

Methods

A sample of 60 Dutch and Canadian students participated in the study. Each student used an online survey to provide weights for 14 criteria with two different techniques: a five-point rating scale and one of the following techniques selected randomly: ranking, point allocation, pairwise comparison and best worst scaling.

Results

The results of this study indicate that there is no effect of differences in weights on value estimates at the group level. On an individual level, considerable differences in criteria weights and rank order occur as a result of the weight elicitation method used, and the ability of different techniques to discriminate in criteria importance. Of the five techniques tested, the pair-wise comparison of criteria has the highest ability to discriminate in weights when fourteen criteria are compared.

Conclusions

When weights are intended to support group decisions, the choice of elicitation technique has negligible impact on criteria weights and the overall value of an innovation. However, when weights are used to support individual decisions, the choice of elicitation technique influences outcome and studies that use dissimilar techniques cannot be easily compared. Weight elicitation through pairwise comparison of criteria is preferred when taking into account its superior ability to discriminate between criteria and respondents’ preferences.

Electronic supplementary material

The online version of this article (doi:10.1186/1478-7547-12-22) contains supplementary material, which is available to authorized users.

From efficacy to equity: Literature review of decision criteria for resource allocation and healthcare decisionmaking

Objectives

Resource allocation is a challenging issue faced by health policy decisionmakers requiring careful consideration of many factors. Objectives of this study were to identify decision criteria and their frequency reported in the literature on healthcare decisionmaking.

Method

An extensive literature search was performed in Medline and EMBASE to identify articles reporting healthcare decision criteria. Studies conducted with decisionmakers (e.g., focus groups, surveys, interviews), conceptual and review articles and articles describing multicriteria tools were included. Criteria were extracted, organized using a classification system derived from the EVIDEM framework and applying multicriteria decision analysis (MCDA) principles, and the frequency of their occurrence was measured.

Results

Out of 3146 records identified, 2790 were excluded. Out of 356 articles assessed for eligibility, 40 studies included. Criteria were identified from studies performed in several regions of the world involving decisionmakers at micro, meso and macro levels of decision and from studies reporting on multicriteria tools. Large variations in terminology used to define criteria were observed and 360 different terms were identified. These were assigned to 58 criteria which were classified in 9 different categories including: health outcomes; types of benefit; disease impact; therapeutic context; economic impact; quality of evidence; implementation complexity; priority, fairness and ethics; and overall context. The most frequently mentioned criteria were: equity/fairness (32 times), efficacy/effectiveness (29), stakeholder interests and pressures (28), cost-effectiveness (23), strength of evidence (20), safety (19), mission and mandate of health system (19), organizational requirements and capacity (17), patient-reported outcomes (17) and need (16).

Conclusion

This study highlights the importance of considering both normative and feasibility criteria for fair allocation of resources and optimized decisionmaking for coverage and use of healthcare interventions. This analysis provides a foundation to develop a questionnaire for an international survey of decisionmakers on criteria and their relative importance. The ultimate objective is to develop sound multicriteria approaches to enlighten healthcare decisionmaking and priority-setting.