Be Careful What You Ask For: Effects of Benefit Descriptions on Diabetes Patients' Benefit-Risk Tradeoff Preferences

Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly used to elicit preferences for health and healthcare. Although many applications assume preferences are homogenous, there is a growing portfolio of methods to understand both explained (because of observed factors) and unexplained (latent) heterogeneity. Nevertheless, the selection of analytical methods can be challenging and little guidance is available. This study aimed to determine the state of practice in accounting for preference heterogeneity in the analysis of health-related DCEs, including the views and experiences of health preference researchers and an overview of the tools that are commonly used to elicit preferences.

METHODS

An online survey was developed and distributed among health preference researchers and nonhealth method experts, and a systematic review of the DCE literature in health was undertaken to explore the analytical methods used and summarize trends.

RESULTS

Most respondents (n = 59 of 70, 84%) agreed that accounting for preference heterogeneity provides a richer understanding of the data. Nevertheless, there was disagreement on how to account for heterogeneity; most (n = 60, 85%) stated that more guidance was needed. Notably, the majority (n = 41, 58%) raised concern about the increasing complexity of analytical methods. Of the 342 studies included in the review, half (n = 175, 51%) used a mixed logit with continuous distributions for the parameters, and a third (n = 110, 32%) used a latent class model.

CONCLUSIONS

Although there is agreement about the importance of accounting for preference heterogeneity, there are noticeable disagreements and concerns about best practices, resulting in a clear need for further analytical guidance.

Use of Patient Preference Information in Benefit-Risk Assessment, Health Technology Assessment, and Pricing and Reimbursement Decisions: A Systematic Literature Review of Attempts and Initiatives

Objectives: Inclusion of patient preference (PP) data in decision making has been largely discussed in recent years. Healthcare decision makers—regulatory and health technology assessment (HTA)—are more and more conscious of the need for a patient-centered approach to decide on optimal allocation of scarce money, time, and technological resources. This literature review aims to examine the use of and recommendations for the integration of PP in decision making.

Methods: A literature search was conducted through PubMed/Medline in May 2019 to identify publications on PP studies used to inform benefit–risk assessments (BRAs) and HTAs and patient-centered projects and guidelines related to the inclusion of PPs in health policy decision making. After title and abstract screening and full-text review, selected publications were analyzed to retrieve data related to the collection, use, and/or submission of PPs informing BRA or HTA as well as attempts and initiatives in recommendations for PPs integration in decision-making processes.

Results: Forty-nine articles were included: 24 attempts and pilot project discussions and 25 PP elicitation studies. Quantitative approaches, particularly discrete choice experiments, were the most used (24 quantitative elicitation studies and 1 qualitative study). The objective of assessing PPs was to prioritize outcome-specific information, to value important treatment characteristics, to provide patient-focused benefit–risk trade-offs, and to appraise the patients' willingness to pay for new technologies. Moreover, attempts and pilot projects to integrate PPs in BRAs and HTAs were identified at the European level and across countries, but no clear recommendations have been issued yet. No less than seven public and/or private initiatives have been undertaken by governmental agencies and independent organizations to set guidance targeting improvement of patients' involvement in decision making.

Conclusion: Despite the initiatives undertaken, the pace of progress remains slow. The use of PPs remains poorly implemented, and evidence of proper use of these data in decision making is lacking. Guidelines and recommendations formalizing the purpose of collecting PPs, what methodology should be adopted and how, and who should be responsible for generating these data throughout the decision-making processes are needed to improve and empower integration of PPs in BRA and HTA.

Comparing the Preferences of Patients and the General Public for Treatment Outcomes in Type 2 Diabetes Mellitus

BACKGROUND

Healthcare treatments and interventions are traditionally evaluated from the societal perspective, but a more patient-centric perspective has been proposed in recent years. We sought to compare preferences of patients and the general public for treatment outcomes of type 2 diabetes using both best-worst scaling (BWS) and rating approaches.

METHODS

A survey evaluating the treatment priorities for type 2 diabetes was conducted in the United States. Members of the general public and patients with type 2 diabetes were recruited from a nationally sampled panel. Participants indicated the importance of seven potential treatment outcomes (hypoglycemic events, glycated hemoglobin [A1c], weight loss, mental health, functioning, glycemic stability, and cardiovascular health) using (1) BWS case 1 and (2) a rating task. Preference differences from BWS prioritizations were explored using mixed logistic regression (BWS preference weights were probability re-scaled so that the weightings of the seven items collectively summed to 100). The consistency of scale between samples was explored using heteroskedastic conditional logistic regression of BWS data. Spearman rank correlation was used to compare standardized BWS preference weights and rating scores for each group. Both groups evaluated the BWS and rating activities using debriefing questions.

RESULTS

The public and patient samples included 314 and 313 respondents, respectively. The public was on average 16 years younger than patients (48 vs 64 years, P < 0.001). In BWS, patients and the public both ranked A1c, glycemic stability, and cardiovascular health within their top three outcomes. Patients valued the outcome A1c most highly and found it twice as important as did the public (41.0 vs 20.2, P < 0.001). The public valued cardiovascular health most highly, and found it to be twice as important than did patients (31.3 vs 17.4, P < 0.001). Patients were more consistent in their preferences than the public (λ = 1.66, P = 0.01). Preferences elicited using BWS and rating approaches were highly correlated for both patients (ρ = 0.96) and the public (ρ = 0.92). Patients were more likely than the public to endorse the BWS as easy to answer (P < 0.001), easy to understand (P < 0.001), consistent with preferences (P < 0.001), and relevant (P < 0.001). Both patients and the public found the rating activity easier to answer and understand, and more consistent with their preferences, than the BWS (P < 0.001).

CONCLUSIONS

We provide some of the first evidence demonstrating a difference in patient and public treatment priorities for diabetes. That patients were more consistent in their preferences than the public and found the BWS and Likert rating instruments more relevant suggests that patient priorities may be more appropriate than those of the general public in some medical decision-making contexts.

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Factors and situations influencing the value of patient preference studies along the medical product lifecycle: a literature review

Industry, regulators, health technology assessment (HTA) bodies, and payers are exploring the use of patient preferences in their decision-making processes. In general, experience in conducting and assessing patient preference studies is limited. Here, we performed a systematic literature search and review to identify factors and situations influencing the value of patient preference studies, as well as applications throughout the medical product lifecyle. Factors and situations identified in 113 publications related to the organization, design, and conduct of studies, and to communication and use of results. Although current use of patient preferences is limited, we identified possible applications in discovery, clinical development, marketing authorization, HTA, and postmarketing phases.