Construct Validity, Reliability, and Responsiveness of the 10-Item Well-Being Instrument for Use in Economic Evaluation Studies.

OBJECTIVES: Economic evaluations of interventions in health and social care require outcome measures that capture their full benefits, including those beyond health. This study aimed to assess construct validity, test-retest reliability, and responsiveness of the newly developed 10-item Well-being instrument (WiX). METHODS: Data were gathered via an online survey in a representative sample of the adult general population in The Netherlands (N = 1045). Construct validity was assessed by inspecting convergent, structural, and discriminant validity, following the COnsensus-based Standards for the selection of health status Measurement INstruments methodology. Regression analyses of the WiX and its items on other validated measures of well-being were performed to assess the convergent validity of the instrument and the relevance of its items. Dimensionality of the WiX was assessed using exploratory factor analysis. To assess discriminant validity, several hypotheses in terms of well-being differences were assessed. Finally, a second survey was sent out 2 weeks after the initial survey (n = 563; 53.9% response rate) to assess the test-retest reliability and responsiveness of the WiX. RESULTS: The WiX showed to be correlated with alternative well-being measures as expected and able to sufficiently differentiate between relevant subgroups in the population. Moreover, the dimensionality analysis indicated that the WiX captures a broad array of elements relevant to well-being, including physical and mental health. The test-retest reliability was good, with an intraclass correlation coefficient of 0.82. CONCLUSIONS: The results regarding the WiX are favorable and indicate that this new instrument may be a promising alternative for existing measures of well-being for evaluating interventions in health and social care.

A Roadmap for Increasing the Usefulness and Impact of Patient-Preference Studies in Decision Making in Health: A Good Practices Report of an ISPOR Task Force.

Many qualitative and quantitative methods are readily available to study patient preferences in health. These methods are now being used to inform a wide variety of decisions, and there is a growing body of evidence showing studies of patient preferences can be used for decision making in a wide variety of contexts. This ISPOR Task Force report synthesizes current good practices for increasing the usefulness and impact of patient-preference studies in decision making. We provide the ISPOR Roadmap for Patient Preferences in Decision Making that invites patient-preference researchers to work with decision makers, patients and patient groups, and other stakeholders to ensure that studies are useful and impactful. The ISPOR Roadmap consists of 5 key elements: (1) context, (2) purpose, (3) population, (4) method, and (5) impact. In this report, we define these 5 elements and provide good practices on how patient-preference researchers and others can actively contribute to increasing the usefulness and impact of patient-preference studies in decision making. We also present a set of key questions that can support researchers and other stakeholders (eg, funders, reviewers, readers) to assess efforts that promote the ongoing impact (both intended and unintended) of a particular preference study and additional studies in the future.

Suitability of Preference Methods Across the Medical Product Lifecycle: A Multicriteria Decision Analysis.

OBJECTIVES: This study aimed to understand the importance of criteria describing methods (eg, duration, costs, validity, and outcomes) according to decision makers for each decision point in the medical product lifecycle (MPLC) and to determine the suitability of a discrete choice experiment, swing weighting, probabilistic threshold technique, and best-worst scale cases 1 and 2 at each decision point in the MPLC. METHODS: Applying multicriteria decision analysis, an online survey was sent to MPLC decision makers (ie, industry, regulatory, and health technology assessment representatives). They ranked and weighted 19 methods criteria from an existing performance matrix about their respective decisions across the MPLC. All criteria were given a relative weight based on the ranking and rating in the survey after which an overall suitability score was calculated for each preference elicitation method per decision point. Sensitivity analyses were conducted to reflect uncertainty in the performance matrix. RESULTS: Fifty-nine industry, 29 regulatory, and 5 health technology assessment representatives completed the surveys. Overall, "estimating trade-offs between treatment characteristics" and "estimating weights for treatment characteristics" were highly important criteria throughout all MPLC decision points, whereas other criteria were most important only for specific MPLC stages. Swing weighting and probabilistic threshold technique received significantly higher suitability scores across decision points than other methods. Sensitivity analyses showed substantial impact of uncertainty in the performance matrix. CONCLUSION: Although discrete choice experiment is the most applied preference elicitation method, other methods should also be considered to address the needs of decision makers. Development of evidence-based guidance documents for designing, conducting, and analyzing such methods could enhance their use.

Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer reviewed journals as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

Preference Variation: Where Does Health Risk Attitude Come Into the Equation?

OBJECTIVES: Decisions about health often involve risk, and different decision makers interpret and value risk information differently. Furthermore, an individual's attitude toward health-specific risks can contribute to variation in health preferences and behavior. This study aimed to determine whether and how health-risk attitude and heterogeneity of health preferences are related. METHODS: To study the association between health-risk attitude and preference heterogeneity, we selected 3 discrete choice experiment case studies in the health domain that included risk attributes and accounted for preference heterogeneity. Health-risk attitude was measured using the 13-item Health-Risk Attitude Scale (HRAS-13). We analyzed 2 types of heterogeneity via panel latent class analyses, namely, how health-risk attitude relates to (1) stochastic class allocation and (2) systematic preference heterogeneity. RESULTS: Our study did not find evidence that health-risk attitude as measured by the HRAS-13 distinguishes people between classes. Nevertheless, we did find evidence that the HRAS-13 can distinguish people's preferences for risk attributes within classes. This phenomenon was more pronounced in the patient samples than in the general population sample. Moreover, we found that numeracy and health literacy did distinguish people between classes. CONCLUSIONS: Modeling health-risk attitude as an individual characteristic underlying preference heterogeneity has the potential to improve model fit and model interpretations. Nevertheless, the results of this study highlight the need for further research into the association between health-risk attitude and preference heterogeneity beyond class membership, a different measure of health-risk attitude, and the communication of risks.

Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Explanation and Elaboration: A Report of the ISPOR CHEERS II Good Practices Task Force.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces the previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, and the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as healthcare, public health, education, and social care). This Explanation and Elaboration Report presents the new CHEERS 2022 28-item checklist with recommendations and explanation and examples for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer-reviewed journals and the peer reviewers and editors assessing them for publication. Nevertheless, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, given that there is an increasing emphasis on transparency in decision making.

Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) Statement: Updated Reporting Guidance for Health Economic Evaluations.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer reviewed journals as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer reviewed journals as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

Surgeons preference for lumbar disk surgery: a discrete choice experiment.

PURPOSE: Multiple surgical techniques are practiced to treat sciatica caused by lumbar disk herniation. It is unknown which factors surgeons find important when offering certain surgical techniques. The objective of this study is threefold: 1) determine the relative weight surgeons place on various characteristics of sciatica treatment, 2) determine the trade-offs surgeons make between these characteristics and 3) identify preference heterogeneity for sciatica treatment. METHODS: A discrete choice experiment was conducted among members of two international neurosurgical organizations. Surgeons were asked on their preferences for surgical techniques using specific scenarios based on five characteristics: effectiveness on leg pain, risk of recurrent disk herniation, duration of postoperative back pain, risk of complications and recovery period. RESULTS: Six-hundred and forty-one questionnaires were filled in, the majority by neurosurgeons. All characteristics significantly influenced the preferences of the respondents. Overall, the risk of complications was the most important characteristic in the decision to opt-in or opt-out for surgery (35.7%). Risk of recurrent disk herniation (19.6%), effectiveness on leg pain (18.8%), postoperative back pain duration (13.5%) and length of recovery period (12.4%) followed. Four latent classes were identified, which was partly explained by the tenure of the surgeon. Surgeons were willing to trade-off 57.8% of effectiveness on leg pain to offer a treatment that has a 1% complication risk instead of 10%. CONCLUSION: In the context of this discrete choice experiment, it is shown that neurosurgeons consider the risk of complications as most important when a surgical technique is offered to treat sciatica, while the risk of recurrent disk herniation and effectiveness are also important factors. Neurosurgeons were prepared to trade off substantial amounts of effectiveness to achieve lower complication rates.

Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer reviewed journals as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

Consolidated health economic evaluation reporting standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations.

Health economic evaluations are comparative analyses of alternative courses of action in terms of their costs and consequences. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, published in 2013, was created to ensure health economic evaluations are identifiable, interpretable, and useful for decision making. It was intended as guidance to help authors report accurately which health interventions were being compared and in what context, how the evaluation was undertaken, what the findings were, and other details that may aid readers and reviewers in interpretation and use of the study. The new CHEERS 2022 statement replaces previous CHEERS reporting guidance. It reflects the need for guidance that can be more easily applied to all types of health economic evaluation, new methods and developments in the field, as well as the increased role of stakeholder involvement including patients and the public. It is also broadly applicable to any form of intervention intended to improve the health of individuals or the population, whether simple or complex, and without regard to context (such as health care, public health, education, social care, etc.). This summary article presents the new CHEERS 2022 28-item checklist and recommendations for each item. The CHEERS 2022 statement is primarily intended for researchers reporting economic evaluations for peer-reviewed journals, as well as the peer reviewers and editors assessing them for publication. However, we anticipate familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for health technology assessment bodies seeking guidance on reporting, as there is an increasing emphasis on transparency in decision making.

How to integrate evidence from patient preference studies into health technology assessment: a critical review and recommendations.

Health technology assessment (HTA) agencies vary in their use of quantitative patient preference data (PP) and the extent to which they have formalized this use in their guidelines. Based on the authors' knowledge of the literature, we identified six different PP "use cases" that integrate PP into HTA in five different ways: through endpoint selection, clinical benefit rating, predicting uptake, input into economic evaluation, and a means to weight all HTA criteria. Five types of insight are distinguished across the use cases: understanding what matters to patients, predicting patient choices, estimating the utility generated by treatment benefits, estimating the willingness to pay for treatment benefits, and informing distributional considerations. Summarizing the literature on these use cases, we recommend circumstances in which PP can add value to HTA and the further research and guidance that is required to support the integration of PP in HTA. Where HTA places more emphasis on clinical outcomes, novel endpoints are available; or where there are already many treatment options, PP can add value by helping decision makers to understand what matters to patients. Where uptake is uncertain, PP can be used to estimate uptake probability. Where indication-specific utility functions are required or where existing utility measures fail to capture the value of treatments, PP can be used to generate or supplement existing utility estimates. Where patients are paying out of pocket, PP can be used to estimate willingness to pay.

Mimicking Real-Life Decision Making in Health: Allowing Respondents Time to Think in a Discrete Choice Experiment.

OBJECTIVE: To empirically test the impact of allowing respondents time to think (TTT) about their choice options on the outcomes of a discrete choice experiments (DCE). METHODS: In total, 613 participants of the Swedish CArdioPulmonary bioImage Study (SCAPIS) completed a DCE questionnaire that measured their preferences for receiving secondary findings of a genetic test. A Bayesian D-efficient design with 60 choice tasks divided over 4 questionnaires was used. Each choice task contained 2 scenarios with 4 attributes: type of disease, disease penetrance probability, preventive opportunities, and effectiveness of prevention. Respondents were randomly allocated to the TTT or no TTT (NTTT) sample. Latent class models (LCMs) were estimated to determine attribute-level values and their relative importance. In addition, choice certainty, attribute-level interpretation, choice consistency, and potential uptake rates were compared between samples. RESULTS: In the TTT sample, 92% of the respondents (245 of 267) indicated they used the TTT period to (1) read the information they received (72%) and (2) discuss with their family (24%). In both samples, respondents were very certain about their choices. A 3-class LCM was fitted for both samples. Preference reversals were found for 3 of the 4 attributes in one class in the NTTT sample (34% class-membership probability). Relative importance scores of the attributes differed between the 2 samples, and significant scale effects indicating higher choice consistency in TTT sample were found. CONCLUSIONS: Offering respondents TTT influences decision making and preferences. Developers of future DCEs regarding complex health-related decisions are advised to consider this approach to enhance the validity of the elicited preferences.

Important components for Dutch in-home care based on qualitative interviews with persons with dementia and informal caregivers.

BACKGROUND: Dementia care in the Netherlands is increasingly dependent on informal care and has the aim to keep persons with dementia at home for as long as possible. However, little is known about the preferences and needs of people with dementia living at home. Including people with dementia and their informal caregivers in research and policy creation could help to identify necessary forms of support, and tailor care to their personal preferences and needs. OBJECTIVE: To identify important components of in-home care for persons with dementia and their informal caregivers in the Netherlands. DESIGN: Semi-structured interviews across the Netherlands, between March and June 2019 using thematic analysis. SETTING AND PARTICIPANTS: Persons with dementia (n = 5) and informal caregivers (n = 14) were primarily recruited through dementia care organizations. Additionally, a case manager was recruited to reflect upon the semi-structured interviews findings. RESULTS: Five themes concerning important care components were identified including the need for: a social network, formal care, information, emotional support and easier access to care. The complexity of the dementia care system posed a common difficulty for persons with dementia and informal caregivers. CONCLUSION: This study suggests that a dementia care package should be developed that includes both informal and formal care, the provision of information and emotional support, and help with access to care. The creation of this care package could help to tailor dementia care to the preferences and needs of the persons with dementia and their informal caregivers.

Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison.

BACKGROUND: Incorporating patient preference (PP) information into decision-making has become increasingly important to many stakeholders. However, there is little guidance on which patient preference assessment methods, including preference exploration (qualitative) and elicitation (quantitative) methods, are most suitable for decision-making at different stages in the medical product lifecycle (MPLC). This study aimed to use an empirical approach to assess which attributes of PP assessment methods are most important, and to identify which methods are most suitable, for decision-makers' needs during different stages in the MPLC. METHODS: A four-step cumulative approach was taken: 1) Identify important criteria to appraise methods through a Q-methodology exercise, 2) Determine numerical weights to ascertain the relative importance of each criterion through an analytical hierarchy process, 3) Assess the performance of 33 PP methods by applying these weights, consulting international health preference research experts and review of literature, and 4) Compare and rank the methods within taxonomy groups reflecting their similar techniques to identify the most promising methods. RESULTS: The Q-methodology exercise was completed by 54 stakeholders with PP study experience, and the analytical hierarchy process was completed by 85 stakeholders with PP study experience. Additionally, 17 health preference research experts were consulted to assess the performance of the PP methods. Thirteen promising preference exploration and elicitation methods were identified as likely to meet decision-makers' needs. Additionally, eight other methods that decision-makers might consider were identified, although they appeared appropriate only for some stages of the MPLC. CONCLUSIONS: This transparent, weighted approach to the comparison of methods supports decision-makers and researchers in selecting PP methods most appropriate for a given application.

What Is Next for Patient Preferences in Health Technology Assessment? A Systematic Review of the Challenges.

BACKGROUND: Integrating patient preferences in Health Technology Assessment (HTA) is argued to improve uptake, adherence, and patient satisfaction. However, how to elicit and incorporate these preferences in HTA in a systematic and scientifically valid manner is subject to debate. OBJECTIVE: This article provides a systematic review of the challenges to integrating patient preferences in HTA that have been raised in the literature about patient preferences in HTA. METHODS: A systematic review of articles published between 2013 and 2017 addressing challenges to the integration of patient preferences in HTA was conducted in 7 databases. All issues with respect to the integration of patient preferences in HTA were extracted and divided into 5 categories: conceptual, normative, procedural, methodological, and practical issues. The issues were ranked according to how often they were mentioned. RESULTS: Of 2147 retrieved articles, 67 were included in the analysis. Thirty-seven unique research issues were identified. In the majority of the articles, methodological issues were posed (82%), followed by procedural (73%), normative (51%), practical (24%), and conceptual (9%) issues. Frequently posed methodological issues concerned preference heterogeneity and choice of method. Common procedural issues concerned how to evaluate the impact of preference studies and their degree of being evidence based. CONCLUSIONS: This article provides an overview of issues with respect to the integration of patient preferences in HTA procedures. Most issues were of a methodological or procedural nature; yet, the large number of different issues points to the overall importance of further researching the different aspects concerned with patient preferences in HTA. Through its ranking of how many articles mention particular issues, this article proposes an implicit research agenda.

Are Healthcare Choices Predictable? The Impact of Discrete Choice Experiment Designs and Models.

BACKGROUND: Lack of evidence about the external validity of discrete choice experiments (DCEs) is one of the barriers that inhibit greater use of DCEs in healthcare decision making. OBJECTIVES: To determine whether the number of alternatives in a DCE choice task should reflect the actual decision context, and how complex the choice model needs to be to be able to predict real-world healthcare choices. METHODS: Six DCEs were used, which varied in (1) medical condition (involving choices for influenza vaccination or colorectal cancer screening) and (2) the number of alternatives per choice task. For each medical condition, 1200 respondents were randomized to one of the DCE formats. The data were analyzed in a systematic way using random-utility-maximization choice processes. RESULTS: Irrespective of the number of alternatives per choice task, the choice for influenza vaccination and colorectal cancer screening was correctly predicted by DCE at an aggregate level, if scale and preference heterogeneity were taken into account. At an individual level, 3 alternatives per choice task and the use of a heteroskedastic error component model plus observed preference heterogeneity seemed to be most promising (correctly predicting >93% of choices). CONCLUSIONS: Our study shows that DCEs are able to predict choices-mimicking real-world decisions-if at least scale and preference heterogeneity are taken into account. Patient characteristics (eg, numeracy, decision-making style, and general attitude for and experience with the health intervention) seem to play a crucial role. Further research is needed to determine whether this result remains in other contexts.

Understanding Patients' Preferences: A Systematic Review of Psychological Instruments Used in Patients' Preference and Decision Studies.

BACKGROUND: Research has been mainly focused on how to elicit patient preferences, with less attention on why patients form certain preferences. OBJECTIVES: To assess which psychological instruments are currently used and which psychological constructs are known to have an impact on patients' preferences and health-related decisions including the formation of preferences and preference heterogeneity. METHODS: A systematic database search was undertaken to identify relevant studies. From the selected studies, the following information was extracted: study objectives, study population, design, psychological dimensions investigated, and instruments used to measure psychological variables. RESULTS: Thirty-three studies were identified that described the association between a psychological construct, measured using a validated instrument, and patients' preferences or health-related decisions. We identified 33 psychological instruments and 18 constructs, and categorized the instruments into 5 groups, namely, motivational factors, cognitive factors, individual differences, emotion and mood, and health beliefs. CONCLUSIONS: This review provides an overview of the psychological factors and related instruments in the context of patients' preferences and decisions in healthcare settings. Our results indicate that measures of health literacy, numeracy, and locus of control have an impact on health-related preferences and decisions. Within the category of constructs that could explain preference and decision heterogeneity, health locus of control is a strong predictor of decisions in several healthcare contexts and is useful to consider when designing a patient preference study. Future research should continue to explore the association of psychological constructs with preference formation and heterogeneity to build on these initial recommendations.

Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments.

A randomized controlled discrete choice experiment (DCE) with 3,320 participating respondents was used to investigate the individual and combined impact of level overlap and color coding on task complexity, choice consistency, survey satisfaction scores, and dropout rates. The systematic differences between the study arms allowed for a direct comparison of dropout rates and cognitive debriefing scores and accommodated the quantitative comparison of respondents' choice consistency using a heteroskedastic mixed logit model. Our results indicate that the introduction of level overlap made it significantly easier for respondents to identify the differences and choose between the choice options. As a stand-alone design strategy, attribute level overlap reduced the dropout rate by 30%, increased the level of choice consistency by 30%, and avoided learning effects in the initial choice tasks of the DCE. The combination of level overlap and color coding was even more effective: It reduced the dropout rate by 40% to 50% and increased the level of choice consistency by more than 60%. Hence, we can recommend attribute level overlap, with color coding to amplify its impact, as a standard design strategy in DCEs.

Opportunities and challenges for the inclusion of patient preferences in the medical product life cycle: a systematic review.

BACKGROUND: The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. This review aimed to understand the potential roles, reasons for using PP and the expectations, concerns and requirements associated with PP in industry processes, regulatory benefit-risk assessment (BRA) and marketing authorization (MA), and HTA and reimbursement decision-making. METHODS: A systematic review of peer-reviewed and grey literature published between January 2011 and March 2018 was performed. Consulted databases were EconLit, Embase, Guidelines International Network, PsycINFO and PubMed. A two-step strategy was used to select literature. Literature was analyzed using NVivo (QSR international). RESULTS: From 1015 initially identified documents, 72 were included. Most were written from an academic perspective (61%) and focused on PP in BRA/MA and/or HTA/reimbursement (73%). Using PP to improve understanding of patients' valuations of treatment outcomes, patients' benefit-risk trade-offs and preference heterogeneity were roles identified in all three decision-making contexts. Reasons for using PP relate to the unique insights and position of patients and the positive effect of including PP on the quality of the decision-making process. Concerns shared across decision-making contexts included methodological questions concerning the validity, reliability and cognitive burden of preference methods. In order to use PP, general, operational and quality requirements were identified, including recognition of the importance of PP and ensuring patient understanding in PP studies. CONCLUSIONS: Despite the array of opportunities and added value of using PP throughout the different steps of the MPLC identified in this review, their inclusion in decision-making is hampered by methodological challenges and lack of specific guidance on how to tackle these challenges when undertaking PP studies. To support the development of such guidance, more best practice PP studies and PP studies investigating the methodological issues identified in this review are critically needed.