Discrete Choice Experiments in Health Care: theory and applications

Health economics is concerned with issues related to scarcity in the allocation of health care. The basic tasks of any economic evaluation are to identify, measure, value, and compare the costs and benefits of alternatives being considered. Traditional means of measuring benefits in the delivery of health care have concentrated on improvements in health outcomes using clinical outcomes and Quality Adjusted Life Years (QALY). The QALY is a measure of the quantity of life gained weighted by the quality of that life. QALYs are extensively used in economic analyses in health care. They claim to capture the health outcome benefits caused by an intervention . However, benefits of a health care intervention or service can be many-sided, e.g. containing non-health outcomes (e.g. amount of information) and process characteristics (e.g. treatment location, route of drug administration, patient experienced burden of testing). For instance, is ‘reduction of dying from cervical cancer’ the only screening characteristic that is considered by women attending a cervical cancer screening programme? Evidence shows that, within the context of cervical cancer screening, women’s preferences for various programmes are also determined by other characteristics than the reduced chance of dying from cervical cancer. Individuals are willing to trade changes in health outcome (change in chance of dying from cervical cance

Public preferences for health care facilities in rural China: A discrete choice experiment

To successfully tackle the problems with the underutilization of primary care in rural China, it is important to align resource allocation with the preferences of the rural population. However, despite growing interest in the factors influencing the rural population's choice of facility, it is unclear how much weight should be placed on these factors, especially under different scenarios of disease severity. In the first study to elicit quantified trade-offs among influential factors in choosing health care facilities, we carried out a discrete choice experiment (DCE) in rural China. We used a Bayesian efficient design to construct 36 choice sets, and then divided them into three blocks. Each block formed one version of questionnaire that contained 12 choice questions. Each question was assigned a hypothetical perceived severity scenario of either minor or severe disease. 559 Rural residents completed the DCE through face-to-face interviews in December 2017–March 2018. We used mixed logit models to analyze the choice data. The factors regarding the availability and affordability of a facility, such as visit time, travel time, and out-of-pocket cost, were highly valued. When the facilities changed simultaneously from the worst to the best case, a huge increase (from 4.8% to 66.5%) in the predicted choice probability of choosing to visit a facility was observed under perceived minor disease scenario, whereas there was no significant change under perceived severe disease scenario. Improvements to drug availability, medical professional skill and equipment in rural primary care system can induce potential medical care seeking, and redirect patient flow from higher level hospitals to primary level. Especially, township health centers, which provide service to the residents in rural communities, have great potential to be the ideal facilities for first-contact care

Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice dat

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

Patients' Preferences for Surgical Management of Esophageal Cancer: A Discrete Choice Experiment

Background: Obtaining insight into patients' preferences is important to optimize cancer care. We investigated patients' preferences for surgical management of esophageal cancer. Methods: We conducted a discrete choice experiment among adult patients who had undergone esophagectomy for adenocarcinoma or squamous cell cancer of the esophagus. Patients' preferences were quantified with regression analysis using scenarios based on five aspects: risk of in-hospital mortality, risk of persistent symptoms, chance of 5-year survival, risk of surgical and non-surgical complications, and hospital volume of esophageal cancer surgery. Results: The response rate was 68 % (104/142). All aspects proved to influence patients' preferences (p < 0.05). Persisting gastrointestinal symptoms and 5-year survival were the most important attributes, but preferences varied between patients. On average, patients were willing to trade-off 9.5 % (CI 2.4-16.6 %) 5-year survival chance to obtain a surgical treatment with 30 % lower risk of gastrointestinal symptoms, or 8.1 % (CI 4.0-12.2 %) 5-year survival chance for being treated in a high instead of a low-volume hospital. Conclusions: Patients are willing to trade-off some 5-year survival chance to achieve an improvement in early outcomes. Given the preference heterogeneity among participants, the present study underlines the importance of a patient-tailored approach when discussing prognosis and treatment

Can healthcare choice be predicted using stated preference data?

Lack of evidence about the external validity of Discrete Choice Experiments (DCEs)-sourced preferences inhibits greater use of DCEs in healthcare decision-making. This study examines the external validity of such preferences, unravels its determinants, and provides evidence of whether healthcare choice is predictable. We focused on influenza vaccination and used a six-step approach: i) literature study, ii) expert interviews, iii) focus groups, iv) survey including a DCE, v) field data, and vi) in-depth interviews with respondents who showed discordance between stated choices and actual healthcare utilization. Respondents without missing values in the survey and the actual healthcare utilization (377/499 = 76%) were included in the analyses. Random-utility-maximization and random-regret-minimization models were used to analyze the DCE data, whereas the in-depth interviews combined five scientific theories to explain discordance.

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

Acceptance of vaccinations in pandemic outbreaks: A discrete choice experiment

Background: Preventive measures are essential to limit the spread of new viruses; their uptake is key to their success. However, the vaccination uptake in pandemic outbreaks is often low. We aim to elicit how disease and vaccination characteristics determine preferences of the general public for new pandemic vaccinations. Methods: In an internet-based discrete choice experiment (DCE) a representative sample of 536 participants (49% participation rate) from the Dutch population was asked for their preference for vaccination programs in hypothetical communicable disease outbreaks. We used scenarios based on two disease characteristics (susceptibility to and severity of the disease) and five vaccination program characteristics (effectiveness, safety, advice regarding vaccination, media attention, and out-of-pocket costs). The DCE design was based on a literature review, expert interviews and focus group discussions. A panel latent class logit model was used to estimate which trade-offs individuals were willing to make. Results: All above mentioned characteristics proved to influence respondents' preferences for vaccination. Preference heterogeneity was substantial. Females who stated that they were never in favor of vaccination made different trade-offs than males who stated that they were (possibly) willing to get vaccinated. As expected, respondents preferred and were willing to pay more for more effective vaccines, especially if the outbreak was more serious (€6-€39 for a 10% more effective vaccine). Changes in effectiveness, out-of-pocket costs and in the body that advises the vaccine all substantially influenced the predicted uptake. Conclusions: We conclude that various disease and vaccination program characteristics influence respondents' preferences for pandemic vaccination programs. Agencies responsible for preventive measures during pandemics can use the knowledge that out-of-pocket costs and the way advice is given affect vaccination uptake to improve their plans for future pandemic outbreaks. The preference heterogeneity shows that information regarding vaccination needs to be targeted differently depending on gender and willingness to get vaccinated

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

Parents' preferences for vaccinating daughters against human papillomavirus in the Netherlands: A discrete choice experiment

Background: To generate knowledge about potential improvements to human papillomavirus (HPV) vaccination information and organization strategies, we assessed how aspects of HPV vaccination are associated with parents' preferences for their daughters' uptake, and which trade-offs parents are willing to make between these aspects. Methods. A discrete choice experiment (DCE) was conducted among parents with a daughter aged 10-12 years. Panel mixed logit regression models were used to determine parents' preferences for vaccination. Trade-offs were quantified between four vaccination programme aspects: degree of protection against cervical cancer, duration of protection, risk of serious side-effects, and age of vaccination. Results: Total response rate was 302/983 (31%). All aspects influenced respondents' preferences for HPV vaccination (p < 0.05). Respondents preferred vaccination at age 14 years instead of at a younger age. Respondents were willing to trade-off 11% of the degree of protection to obtain life-time protection instead of 25 years. To obtain a vaccination with a risk of serious side-effects of 1/750,000 instead of 1/150,000, respondents were willing to trade-off 21%. Conclusions: Uptake may rise if the age ranges for free HPV vaccinations are broadened. Based on the trade-offs parents were willing to make, we conclude that uptake would increase if new evidence indicated outcomes are better than are currently understood, particularly for degree and duration of protection