Healthcare policy reforms in postcolonial countries: Putting Surinamese developments in context.

This article was published in Early View in error. The article is under review and will republish shortly.

Preferences of patients, clinicians, and healthy controls for the management of a Bethesda III thyroid nodule.

BACKGROUND: Active surveillance is propagated as an alternative for hemithyroidectomy in the management of Bethesda III thyroid nodules. METHODS: A cross-sectional survey questioned respondents on their willingness to accept risks related to active surveillance and hemithyroidectomy. RESULTS: In case of active surveillance, respondents (129 patients, 46 clinicians, and 66 healthy controls) were willing to accept a risk of 10%-15% for thyroid cancer and 15% for needing more extensive surgery in the future. Respondents were willing to accept a risk of 22.5%-30% for hypothyroidism after hemithyroidectomy. Patients and controls were willing to accept a higher risk on permanent voice changes compared with clinicians (10% vs. 3%, p < 0.001). CONCLUSION: Real-life risks associated which active surveillance and hemithyroidectomy for Bethesda III nodules are equivalent or less than the risks people are willing to accept. Clinicians accepted less risk for permanent voice changes.

Comparing Outcomes of a Discrete Choice Experiment and Case 2 Best-Worst Scaling: An Application to Neuromuscular Disease Treatment.

BACKGROUND AND OBJECTIVES: Case 2 best-worst scaling (BWS-2) is an increasingly popular method to elicit patient preferences. Because BWS-2 potentially has a lower cognitive burden compared with discrete choice experiments, the aim of this study was to compare treatment preference weights and relative importance scores. METHODS: Patients with neuromuscular diseases completed an online survey at two different moments in time, completing one method per occasion. Patients were randomly assigned to either first a discrete choice experiment or BWS-2. Attributes included: muscle strength, energy endurance, balance, cognition, chance of blurry vision, and chance of liver damage. Multinomial logit was used to calculate overall relative importance scores and latent class logit was used to estimate heterogeneous preference weights and to calculate the relative importance scores of the attributes for each latent class. RESULTS: A total of 140 patients were included for analyses. Overall relative importance scores showed differences in attribute importance rankings between a discrete choice experiment and BWS-2. Latent class analyses indicated three latent classes for both methods, with a specific class in both the discrete choice experiment and BWS-2 in which (avoiding) liver damage was the most important attribute. Ex-post analyses showed that classes differed in sex, age, level of education, and disease status. The discrete choice experiment was easier to understand compared with BWS-2. CONCLUSIONS: This study showed that using a discrete choice experiment and BWS-2 leads to different outcomes, both in preference weights as well as in relative importance scores, which might have been caused by the different framing of risks in BWS-2. However, a latent class analysis revealed similar latent classes between methods. Careful consideration about method selection is required, while keeping the specific decision context in mind and pilot testing the methods.

A Systematic Review of Discrete Choice Experiments in Oncology Treatments.

BACKGROUND: As the number and type of cancer treatments available rises and patients live with the consequences of their disease and treatments for longer, understanding preferences for cancer care can help inform decisions about optimal treatment development, access, and care provision. Discrete choice experiments (DCEs) are commonly used as a tool to elicit stakeholder preferences; however, their implementation in oncology may be challenging if burdensome trade-offs (e.g. length of life versus quality of life) are involved and/or target populations are small. OBJECTIVES: The aim of this review was to characterise DCEs relating to cancer treatments that were conducted between 1990 and March 2020. DATA SOURCES: EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews were searched for relevant studies. STUDY ELIGIBILITY CRITERIA: Studies were included if they implemented a DCE and reported outcomes of interest (i.e. quantitative outputs on participants' preferences for cancer treatments), but were excluded if they were not focused on pharmacological, radiological or surgical treatments (e.g. cancer screening or counselling services), were non-English, or were a secondary analysis of an included study. ANALYSIS METHODS: Analysis followed a narrative synthesis, and quantitative data were summarised using descriptive statistics, including rankings of attribute importance. RESULT: Seventy-nine studies were included in the review. The number of published DCEs relating to oncology grew over the review period. Studies were conducted in a range of indications (n = 19), most commonly breast (n =10, 13%) and prostate (n = 9, 11%) cancer, and most studies elicited preferences of patients (n = 59, 75%). Across reviewed studies, survival attributes were commonly ranked as most important, with overall survival (OS) and progression-free survival (PFS) ranked most important in 58% and 28% of models, respectively. Preferences varied between stakeholder groups, with patients and clinicians placing greater importance on survival outcomes, and general population samples valuing health-related quality of life (HRQoL). Despite the emphasis of guidelines on the importance of using qualitative research to inform attribute selection and DCE designs, reporting on instrument development was mixed. LIMITATIONS: No formal assessment of bias was conducted, with the scope of the paper instead providing a descriptive characterisation. The review only included DCEs relating to cancer treatments, and no insight is provided into other health technologies such as cancer screening. Only DCEs were included. CONCLUSIONS AND IMPLICATIONS: Although there was variation in attribute importance between responder types, survival attributes were consistently ranked as important by both patients and clinicians. Observed challenges included the risk of attribute dominance for survival outcomes, limited sample sizes in some indications, and a lack of reporting about instrument development processes. PROTOCOL REGISTRATION: PROSPERO 2020 CRD42020184232.

Preferences of patients and clinicians for treatment of Graves' disease: a discrete choice experiment.

OBJECTIVE: Treatment options for Graves' disease (GD) consist of antithyroid drugs (ATD), radioactive iodine (RAI) and total thyroidectomy (TT). Guidelines recommend to discuss these options with patients, taking into account patients' preferences. This study aims to evaluate and compare patients' and clinicians' preferences and the trade-offs made in choosing treatment. DESIGN AND METHODS: A discrete choice experiment (DCE) was performed with GD patients with a first diagnosis or recurrence in the previous year, and with clinicians. Participants were offered hypothetical treatment options which differed in type of treatment, rates of remission, severe side effects, permanent voice changes and hypocalcemia. Preference heterogeneity was assessed by latent-class analysis. RESULTS: In this study, 286 (82%) patients and 61 (18%) clinicians participated in the DCE. All treatment characteristics had a significant effect on treatment choice (P < 0.05). Remission rate was the most important determinant and explained 37 and 35% of choices in patients and clinicians, respectively. Both patients and clinicians preferred ATD over surgery and RAI. A strong negative preference toward RAI treatment was observed in a subclass of patients, whereas clinicians preferred RAI over surgery. CONCLUSION: For both patients and clinicians, remission rate was the most important determinant of treatment choice and ATD was the most preferred treatment option. Patients had a negative preference toward RAI compared to alternatives, whereas clinicians preferred RAI over surgery. Clinicians should be aware that their personal attitude toward RAI differs from that of their patients. This study on patients' and clinicians' preferences can support shared decision making and thereby improve clinical treatment.

A study protocol for quantifying patient preferences in neuromuscular disorders: a case study of the IMI PREFER Project.

Objectives: Patient preference studies are increasingly used to inform decision-making during the medical product lifecycle but are rarely used to inform early stages of drug development.  The primary aim of this study is to quantify treatment preferences of patients with neuromuscular disorders, which represent serious and debilitating conditions with limited or no treatment options available. Methods: This quantitative patient preferences study was designed as an online survey, with a cross-over design.  This study will target two different diseases from the neuromuscular disorders disease group, myotonic dystrophy type 1 (DM1) and mitochondrial myopathies (MM). Despite having different physio-pathological pathways both DM1 and MM manifest in a clinically similar manner and may benefit from similar treatment options.  The sample will be stratified into three subgroups: two patient groups differentiated by age of symptom onset and one caregivers group.   Each subgroup will be randomly assigned to complete two of three different preference elicitation methods at two different time points: Q-methodology survey, discrete choice experiment, and best-worst scaling type 2, allowing cross-comparisons of the results across each study time within participants and within elicitation methods. Additional variables such as sociodemographic, clinical and health literacy will be collected to enable analysis of potential heterogeneity. Ethics and Dissemination: This study protocol has undergone ethical review and approval by the Newcastle University R&D Ethics Committee (Ref: 15169/2018). All participants will be invited to give electronic informed consent to take part in the study prior accessing the online survey. All electronic data will be anonymised prior analysis. This study is part of the Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle (IMI-PREFER) project, a public-private collaborative research project aiming to develop expert and evidence-based recommendations on how and when patient preferences can be assessed and used to inform medical product decision making.

Methods for exploring and eliciting patient preferences in the medical product lifecycle: a literature review.

Preference studies are becoming increasingly important within the medical product decision-making context. Currently, there is limited understanding of the range of methods to gain insights into patient preferences. We developed a compendium and taxonomy of preference exploration (qualitative) and elicitation (quantitative) methods by conducting a systematic literature review to identify these methods. This review was followed by analyzing prior preference method reviews, to cross-validate our results, and consulting intercontinental experts, to confirm our outcomes. This resulted in the identification of 32 unique preference methods. The developed compendium and taxonomy can serve as an important resource for assessing these methods and helping to determine which are most appropriate for different research questions at varying points in the medical product lifecycle.

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.