A Protocol for Developing a Discrete Choice Experiment to Elicit Preferences of General Practitioners for the Choice of Specialty

Consumer Preferences for a Healthcare Appointment Reminder in Australia: A Discrete Choice Experiment

BACKGROUND

It is essential to consider the evidence of consumer preferences and their specific needs when determining which strategies to use to improve patient attendance at scheduled healthcare appointments.

OBJECTIVES

This study aimed to identify key attributes and elicit healthcare consumer preferences for a healthcare appointment reminder system.

METHODS

A discrete choice experiment was conducted in a general Australian population sample. The respondents were asked to choose between three options: their preferred reminder (A or B) or a 'neither' option. Attributes were developed through a literature review and an expert panel discussion. Reminder options were defined by four attributes: modality, timing, content and interactivity. Multinomial logit and mixed multinomial logit models were estimated to approximate individual preferences for these attributes. A scenario analysis was performed to estimate the likelihood of choosing different reminder systems.

RESULTS

Respondents (n = 361) indicated a significant preference for an appointment reminder to be delivered via a text message (β = 2.42, p < 0.001) less than 3 days before the appointment (β = 0.99, p < 0.001), with basic details including the appointment cost (β = 0.13, p < 0.10), and where there is the ability to cancel or modify the appointment (β = 1.36, p < 0.001). A scenario analysis showed that the likelihood of choosing an appointment reminder system with these characteristics would be 97%.

CONCLUSIONS

Our findings provide evidence on how healthcare consumers trade-off between different characteristics of reminder systems, which may be valuable to inform current or future systems. Future studies may focus on exploring the effectiveness of using patient-preferred reminders alongside other mitigation strategies used by providers.

Attribute Development in Health-Related Discrete Choice Experiments: A Systematic Review of Qualitative Methods and Techniques to Inform Quantitative Instruments

OBJECTIVES

This review sought to identify the qualitative methods and techniques that researchers have used in the past decade to develop attributes and inform health-related discrete choice experiments (DCEs) surveys from a patient perspective.

METHODS

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for reporting systematic reviews. An adapted appraisal tool following guidelines for reporting qualitative research for quantitative instruments and criteria for attribute development in DCEs was applied for quality assessment and data extraction. A narrative approach was used to synthesize data. This examination included consideration of issues pertaining to sampling, data collection, data analysis, attribute list reduction, wording, methodological adaptations to capture patient preferences, and testing the pre-experimental design decisions of the DCE survey.

RESULTS

Of 8505 articles identified for abstract screening, 680 were included for full-text screening, 36 of which met the inclusion criteria. Practices to improve methodological robustness included pre-data collection materials to inform instruments, data collection methods specific for decision-making scenarios, purposeful selection of data analysis methods to address the research question, and participants' involvement in reducing the list of attributes. Examples of methodological adaptations for patients were noted.

CONCLUSIONS

DCEs have the potential to become a mixed-method approach in which the qualitative phase informs a reduced list of attributes for a survey, serves the predesign decisions of the experiment by testing trade-offs, overlapping, understandability, face, and content validity and provides explanations of the quantitative results. Establishing guidelines for using qualitative methods for DCE attribute development may help to broadly enhance the methodological robustness of DCEs.

Predictive Models for the Transition from Mild Neurocognitive Disorder to Major Neurocognitive Disorder: Insights from Clinical, Demographic, and Neuropsychological Data

Neurocognitive disorders (NCDs) are progressive conditions that severely impact cognitive function and daily living. Understanding the transition from mild to major NCD is crucial for personalized early intervention and effective management. Predictive models incorporating demographic variables, clinical data, and scores on neuropsychological and emotional tests can significantly enhance early detection and intervention strategies in primary healthcare settings. We aimed to develop and validate predictive models for the progression from mild NCD to major NCD using demographic, clinical, and neuropsychological data from 132 participants over a two-year period. Generalized Estimating Equations were employed for data analysis. Our final model achieved an accuracy of 83.7%. A higher body mass index and alcohol drinking increased the risk of progression from mild NCD to major NCD, while female sex, higher praxis abilities, and a higher score on the Geriatric Depression Scale reduced the risk. Here, we show that integrating multiple factors-ones that can be easily examined in clinical settings-into predictive models can improve early diagnosis of major NCD. This approach could facilitate timely interventions, potentially mitigating the progression of cognitive decline and improving patient outcomes in primary healthcare settings. Further research should focus on validating these models across diverse populations and exploring their implementation in various clinical contexts.

What do Iranian physicians value most when choosing a specialty? Evidence from a discrete choice experiment

BACKGROUND

Choosing a specialty by physicians is fundamentally linked to the performance of health systems and public health outcomes. Identifying the determinants of specialty selection is important to health policy for targeting resources and planning the development of services. This study examined preferences of Iranian physicians for medical specialty using a discrete choice experiment (DCE) method.

METHODS

In this study, the attributes of the DCE were determined using rigorous qualitative approach. Then we applied D-efficiency criteria to design the DCE and validated it at a pilot study. In the final survey, we recruited participants from six Iranian provinces and analyzed data using conditional logit model. We estimated willingness to pay (WTP) for non-monetary attributes.

RESULTS

The WTP analysis revealed that the most important non-monetary attributes in the selection of a specialty were job burnout, opportunity for procedural activities, and job prestige. The results imply that the attributes that were related to the quality of personal life was more important only for physicians who preferred to choose non-surgical specialties.

CONCLUSIONS

The findings demonstrate that traditional gender patterns of specialty selection are changing and quality of personal life characteristics might be the most important factor when developing policies to recruit physicians into non-surgical specialties.

Attributes Used for Cancer Screening Discrete Choice Experiments: A Systematic Review

BACKGROUND

Evidence from discrete choice experiments can be used to enrich understanding of preferences, inform the (re)design of screening programmes and/or improve communication within public campaigns about the benefits and harms of screening. However, reviews of screening discrete choice experiments highlight significant discrepancies between stated choices and real choices, particularly regarding willingness to undergo cancer screening. The identification and selection of attributes and associated levels is a fundamental component of designing a discrete choice experiment. Misspecification or misinterpretation of attributes may lead to non-compensatory behaviours, attribute non-attendance and responses that lack external validity.

OBJECTIVES

We aimed to synthesise evidence on attribute development, alongside an in-depth review of included attributes and methodological challenges, to provide a resource for researchers undertaking future studies in cancer screening.

METHODS

A systematic review was conducted to identify discrete choice experiments estimating preferences towards cancer screening, dated between 1990 and December 2020. Data were synthesised narratively. In-depth analysis of attributes led to classification into four categories: test specific, service delivery, outcomes and monetary. Attribute significance and relative importance were also analysed. The International Society for Pharmacoeconomics and Outcomes Research conjoint analysis checklist was used to assess the quality of reporting.

RESULTS

Forty-nine studies were included at full text. They covered a range of cancer sites: over half (26/49) examined colorectal screening. Most studies elicited general public preferences (34/49). In total, 280 attributes were included, 90% (252/280) of which were significant. Overall, test sensitivity and mortality reduction were most frequently found to be the most important to respondents.

CONCLUSIONS

Improvements in reporting the identification, selection and construction of attributes used within cancer screening discrete choice experiments are needed. This review also highlights the importance of considering the complexity of choice tasks when considering risk information or compound attributes. Patient and public involvement and stakeholder engagement are recommended to optimise understanding of unavoidably complex choice tasks throughout the design process. To ensure quality and maximise comparability across studies, further research is needed to develop a risk-of-bias measure for discrete choice experiments.