Taking the Shortcut: Simplifying Heuristics in Discrete Choice Experiments

Exploring the Factors that Drive Clinical Negligence Claims: Stated Preferences of Those Who Have Experienced Unintended Harm

BACKGROUND

Better understanding of the factors that influence patients to make a financial claim for compensation is required to inform policy decisions. This study aimed to assess the relative importance of factors that influence those who have experienced a patient safety incident (PSI) to make a claim for compensation.

METHOD

Participants completed an online discrete choice experiment (DCE) involving 10 single profile tasks where they chose whether or not to file a claim. DCE data were modelled using logistic, mixed logit and latent class regressions; scenario analyses, external validity, and willingness to accept were also conducted.

RESULTS

A total of 1029 participants in the United Kingdom responded to the survey. An appropriate apology and a satisfactory investigation reduced the likelihood of claiming. Respondents were more likely to claim if they could hold those responsible accountable, if the process was simple and straightforward, if the compensation amount was higher, if the likelihood of compensation was high or uncertain, if the time to receive a decision was quicker, and if they used the government compensation scheme. Men are more likely to claim for low impact PSIs.

DISCUSSION AND CONCLUSIONS

The actions taken by the health service after a PSI, and people's perceptions about the probability of success and the size of potential reward, can influence whether a claim is made. Results show the importance of giving an appropriate apology and conducting a satisfactory investigation. This stresses the importance around how patients are treated after a PSI in influencing the clinical negligence claims that are made.

Making Use of Technology to Improve Stated Preference Studies

The interest in quantifying stated preferences for health and healthcare continues to grow, as does the technology available to support and improve health preference studies. Technological advancements in the last two decades have implications and opportunities for preference researchers designing, administering, analysing, interpreting and applying the results of stated preference surveys. In this paper, we summarise selected technologies and how these can benefit a preference study. We discuss empirical evaluations of the technology in preference research, with examples from health where possible. The technologies reviewed include serious games, virtual reality, eye tracking, innovative formats and decision aids with values clarification components. We conclude with a critical reflection on the benefits and limitations of implementing (often costly) technology alongside stated preference studies.

Comparing heuristic valuation processes between health state valuation from child and adult perspectives

OBJECTIVES

Health state valuation assumes that respondents trade off between all aspects of choice tasks and maximize their utility. Yet, respondents may use heuristic valuation processes, i.e., strategies to simplify or avoid the trade-offs that are core to health state valuation. The objective of this study is to explore if heuristic valuation processes are more prevalent for valuation from a 10-year-old child's perspective compared to the use of an adult perspective.

METHODS

We reused existing data in which EQ-5D health states were valued from adult and child perspectives with composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks. Our analyses focused on comparing completion time and responding patterns across both perspectives. We also explored how reflective of a set of heuristic strategies respondents' choices were in both perspectives.

RESULTS

We found no evidence for systematic differences in completion time across perspectives. Generally, we find different responding patterns in child perspectives, e.g., more speeding, dominance violations, and clustering of utilities at 1.0, 0.8, and 0. Very few heuristic strategies provide a coherent explanation for the observed DCE responses.

CONCLUSION

Our results provide some, albeit indirect, evidence for differences in heuristic valuation processes between perspectives, although not across all data sources. Potential effects of heuristic valuation processes, such as transfer of responsibility, may be identified through studying responding patterns in cTTO and DCE responses.

Stated-Preference Survey Design and Testing in Health Applications

Following the conceptualization of a well-formulated and relevant research question, selection of an appropriate stated-preference method, and related methodological issues, researchers are tasked with developing a survey instrument. A major goal of designing a stated-preference survey for health applications is to elicit high-quality data that reflect thoughtful responses from well-informed respondents. Achieving this goal requires researchers to design engaging surveys that maximize response rates, minimize hypothetical bias, and collect all the necessary information needed to answer the research question. Designing such a survey requires researchers to make numerous interrelated decisions that build upon the decision context, selection of attributes, and experimental design. Such decisions include considering the setting(s) and study population in which the survey will be administered, the format and mode of administration, and types of contextual information to collect. Development of a survey is an interactive process in which feedback from respondents should be collected and documented through qualitative pre-test interviews and pilot testing. This paper describes important issues to consider across all major steps required to design and test a stated-choice survey to elicit patient preferences for health preference research.

Preferences for Physical Examination Service in Community Health Service Center in China: A Discrete Choice Experiment

Objective

Physical examination services play a crucial role in the early detection of diseases, improving the effectiveness of treatment. However, the current physical examination services provided by community health service centers are limited. The objective of this study was to investigate the aspects of physical examination services that are most valued by residents.

Methods

Identify and develop attributes and levels through literature research and expert group interviews. A discrete choice experiment was designed. The main effects design gives rise to 16 choice sets. The 16 choice sets were grouped into 2 blocks, and respondents were randomly assigned to one of the blocks. In each choice set, respondents were asked to choose from two alternatives with an opt-out option. In 2023, the discrete choice experiment was administered in several community health service centers within a China population sample. A mixed logit and a latent class analysis were conducted.

Results

Participants (n = 399) preferred to receive health advice service. The services provided by the basic team with clinical experts are preferred over those provided solely by the basic team. The results indicated a preference for a participant to be serviced by face-to-face or telephone compared with WeChat. Low cost is also preferred. As participants grow older, their preference for face-to-face or telephone-based services increased. As participants' service demand increase, participants more preferred to receive interpretation of physical examination report and follow-up of important abnormal results, participants more preferred to be serviced by basic team with clinical experts or basic team with health manager etc.

Conclusion

We should improve the construction of the service team, optimize the service mode, expand the scope of examination services, reduce the cost of examination services, and meet the needs of residents for physical examination services. More attention should be paid to the needs of elderly and rural residents.

Two Methods, One Story? Comparing Results of a Choice Experiment and Multidimensional Thresholding From a Clinician Preference Study in Aneurysmal Subarachnoid Hemorrhage

OBJECTIVES

An increasing number of methods are used to elicit health preference information. It is unclear whether different elicitation methods produce similar results and policy advice. Here, we compared the results from a discrete choice experiment (DCE) and multidimensional thresholding (MDT) that were conducted in the same sample.

METHODS

Clinicians (N = 350) completed a DCE and MDT to elicit their preferences for 4 attributes related to the medical management of subarachnoid hemorrhage after aneurysm repair. Preference weights were compared between the DCE and MDT using a complete combinatorial convolution test. Additionally, data from the DCE and MDT were used to compute preference-based net treatment values for 16 hypothetical treatment profiles versus 1000 simulated comparators. The implied treatment recommendations were compared between the DCE and MDT.

RESULTS

Preference weight distributions and median weights did not differ significantly between the DCE and MDT for any attribute: likelihood of delayed cerebral ischemia (medians 0.48 vs 0.40; P = .41), risk of lung complications (medians 0.27 vs 0.30; P = .52), risk of hypotension (medians 0.10 vs 0.11; P = .55), and risk of anemia (medians 0.07 vs 0.07; P = .50). The DCE and MDT produced similar treatment net value distributions (P > .05) and implied the same treatment recommendations in 82.3% of cases.

CONCLUSIONS

The DCE and MDT elicited similar preference distributions and produced the same treatment recommendations for most tested cases. However, the share of people supporting the average treatment recommendation differed. More research is needed to determine how these findings would compare with those in other populations (in particular, patients) and applications.

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life

Background

The increasing interest in early identification of people at risk of developing dementia, has led to the development of numerous models aimed at estimating the likelihood of progression from mild cognitive impairment (MCI) to dementia. It is important to study both the need for and possible outcomes related with such prediction models, including the impact of risk predictions on perceived quality of life (QoL).

Objective

This study aimed to quantify the impact that receiving a risk prediction on progression from MCI to dementia has on QoL.

Methods

A Discrete Choice Experiment (DCE) and Time Trade Off (TTO) study were performed. Participants completed choice tasks related to dementia prognosis while imagining having MCI. We collected DCE data by an online survey, and TTO data via videoconferencing interviews. DCE data were analyzed using a mixed multinomial logit model and were anchored to a health state utility scale using mean observed TTO valuations.

Results

296 people participated in the DCE and 42 in the TTO. Moderate and high predicted dementia risks were associated with decrements in utility (-0.05 and -0.18 respectively), compared to no prognostic information. Low predicted risk was associated with an increase in utility (0.06), as well as the availability of medication or lifestyle interventions (0.05 and 0.13 respectively).

Conclusions

This study shows a significant impact of dementia risk predictions on QoL and highlights the importance of caution when sharing information about expected MCI disease courses.