The heterogeneity of public preferences for the first healthcare visit: A discrete choice experiment in the context of Vietnam

Primary healthcare is critical in addressing the main health problems of communities. In Vietnam, the increasing healthcare demands cause major challenges, especially overcrowding. This study identified public preferences regarding the selection of healthcare facilities for first visit. A discrete choice online survey was generated from five attributes including visit duration, travel time, personal connection with medical staff, doctors' experience, and health insurance. A D_z -efficient design constructed 36 choice sets, divided into three blocks of 12 choice sets. Each block formed one version of the questionnaire, which was randomly distributed to the participants. Heterogeneity in participant preferences was analysed by a latent class model with socio demographic characteristics and experiences of the last visit. 822 participants valued doctors' experience for both minor and severe symptoms. Preference heterogeneity for minor symptoms was quick service provision, highly experienced doctors, and payment through health insurance for the first (44.18%), second (32.17%), and third classes (23.66%), respectively. Regarding severe symptoms, they favoured all five attributes, quick health service, and reduced travel time for the first, second, and third classes, respectively (heterogeneities of 58.16%, 27.79%, and 14.05%, respectively). Predictions of choice from the worst to optimal healthcare facility scenario were 8.91%-61.91% and 10.16%-69.83% for minor and severe symptoms, respectively. Knowledge regarding public preference heterogeneity supports policymakers increase public acceptance in choosing primary healthcare facilities. Visit duration and doctors' experience should be considered a priority in decision making.

Healthcare preferences of the general Chinese population in the hierarchical medical system: A discrete choice experiment

Background

Chinese health insurance system faces resource distribution challenges. A patient-centric approach allows decision-makers to be keenly aware of optimized medical resource allocation.

Objective

This study aims to use the discrete choice model to determine the main factors affecting the healthcare preferences of the general Chinese population and their weights in the three scenarios (chronic non-communicable diseases, acute infectious diseases, and major diseases).

Methods

This study firstly identified the key factors affecting people's healthcare preferences through literature review and qualitative interviews, and then designed the DCE questionnaire. An online questionnaire produced by Lighthouse Studio (version 9.9.1) software was distributed to voluntary respondents recruited from mainland China's entire population from January 2021 to June 2021. Participants were required to answer a total of 21 questions of three scenarios in the questionnaire. The multinomial logit model and latent class model were used to analyze the collected data.

Results

A total of 4,156 participants from mainland China were included in this study. The multinomial logit and latent class model analyses showed that medical insurance reimbursement is the most important attribute in all three disease scenarios. In the scenario of "non-communicable diseases," the attributes that participants valued were, from the most to the least, medical insurance reimbursement (45.0%), hospital-level (21.6%), distance (14.4%), cost (9.7%), waiting time (8.3%), and care provider (1.0%). As for willingness to pay (WTP), participants were willing to pay 204.5 yuan, or 1,743.8 yuan, to change from private hospitals or community hospitals to tertiary hospitals, respectively.

Conclusions

This study explores the healthcare preferences of Chinese residents from a new perspective, which can provide theoretical reference for the refinement of many disease medical reimbursement policies, such as developing different reimbursement ratios for various common diseases and realizing rational configuration of medical resources.

Conjoint analyses of patients’ preferences for primary care: a systematic review

Background

While patients’ preferences in primary care have been examined in numerous conjoint analyses, there has been little systematic effort to synthesise the findings. This review aimed to identify, to organise and to assess the strength of evidence for the attributes and factors associated with preference heterogeneity in conjoint analyses for primary care outpatient visits.

Methods

We searched five bibliographic databases (PubMed, Embase, PsycINFO, Econlit and Scopus) from inception until 15 December 2021, complemented by hand-searching. We included conjoint analyses for primary care outpatient visits. Two reviewers independently screened papers for inclusion and assessed the quality of all included studies using the checklist by ISPOR Task Force for Conjoint Analysis. We categorized the attributes of primary care based on Primary Care Monitoring System framework and factors based on Andersen’s Behavioural Model of Health Services Use. We then assessed the strength of evidence and direction of preference for the attributes of primary care, and factors affecting preference heterogeneity based on study quality and consistency in findings.

Results

Of 35 included studies, most (82.4%) were performed in high-income countries. Each study examined 3–8 attributes, mainly identified through literature reviews (n = 25). Only six examined visits for chronic conditions, with the rest on acute or non-specific / other conditions. Process attributes were more commonly examined than structure or outcome attributes. The three most commonly examined attributes were waiting time for appointment, out-of-pocket costs and ability to choose the providers they see. We identified 24/58 attributes with strong or moderate evidence of association with primary care uptake (e.g., various waiting times, out-of-pocket costs) and 4/43 factors with strong evidence of affecting preference heterogeneity (e.g., age, gender).

Conclusions

We found 35 conjoint analyses examining 58 attributes of primary care and 43 factors that potentially affect the preference of these attributes. The attributes and factors, stratified into evidence levels based on study quality and consistency, can guide the design of research or policies to improve patients’ uptake of primary care. We recommend future conjoint analyses to specify the types of visits and to define their attributes clearly, to facilitate consistent understanding among respondents and the design of interventions targeting them.

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Trial registration

On Open Science Framework: https://osf.io/m7ts9

Treatment Preferences of Residents Assumed to Have Severe Chronic Diseases in China: A Discrete Choice Experiment

Objectives: This study aims to elicit the relative importance of treatment attributes that influence residents’ choice, assuming they are suffering severe non-communicable diseases (NCDs), to explore how they make trade-offs between these attributes and to estimate the monetary value placed on different attributes and attribute levels. Methods: A discrete choice experiment (DCE) was conducted with adults over 18 years old in China. Preferences were evaluated based on four treatment attributes: care provider, mode of service, distance to practice and cost. A mixed logit model was used to analyze the relative importance of the four attributes and to calculate the willingness to pay (WTP) for a changed attribute level. Results: A total of 93.47% (2019 of 2160) respondents completed valid questionnaires. The WTP results suggested that participants would be willing to pay CNY 822.51 (USD 124.86), CNY 470.54 (USD 71.41) and CNY 68.20 (USD 10.35) for services provided by experts, with integrated traditional Chinese medicine (TCM) and Western medicine (WM) and with a service distance <=30 min, respectively. Conclusions: The results suggested that mode of service, care provider, distance to practice and cost should be considered in priority-setting decisions. The government should strengthen the curative service capability in primary health facilities and give full play to the role of TCM in the prevention and treatment of severe chronic diseases.

Reporting Quality of Marginal Rates of Substitution in Discrete Choice Experiments That Elicit Patient Preferences

BACKGROUND

Discrete choice experiments (DCEs) are commonly used to elicit patient preferences as marginal rates of substitution (MRSs) between treatment or health service attributes. Because these studies are increasing in importance, it is vital that uncertainty around MRS estimates is reported.

OBJECTIVE

To review recently published DCE studies that elicit patient preferences in relation to MRS reporting and to explore the accuracy of using other reported information to estimate the uncertainty of the MRSs.

METHODS

A systematic literature review of DCEs conducted with patients between 2014 and July 2019 was performed. The number of studies reporting coefficients, MRSs, standard errors (SEs), and confidence intervals was recorded. If all information was reported, studies were included in an analysis to determine the impact of estimating the SEs of MRSs using coefficients and assuming zero covariance, to determine the impact of this assumption.

RESULTS

Two hundred and thirty-two patient DCEs were identified in the review; 34.1% (n = 79) reported 1 or more MRS and, of these, only 62.0% (n = 49) provided an estimate of the uncertainty. Of these studies, 16 contained enough information for inclusion in the analysis, providing 116 datapoints. Actual SEs were smaller than estimated SEs in 75.0% of cases (n = 87), and estimated SEs were within 25% of the actual SE in 59.5% of cases (n = 69).

CONCLUSION

Uncertainty of MRS estimates is unreported in a substantial proportion of recently published DCE studies. Estimating the SE of a MRS by solely using the SEs of the utility coefficients is likely to lead to biased estimates of the precision of patient trade-offs.

Preferences heterogeneity of health care utilization of community residents in China: a stated preference discrete choice experiment

Background

To tackle the issue with the low usage of primary healthcare service in China, it is essential to align resource distribution with the preferences of the community residents. There are few academic researches for describing residents’ perceived characteristics of healthcare services in China. This study aims to investigate the preferences of healthcare services utilization in community residents and explore the heterogeneity. The findings will be useful for the policy makers to take targeted measures to tailor the provision of healthcare services.

Methods

The face-to-face interviews and surveys were conducted to elicit four key attributes (care provider; mode of services; cost; travel time) of the preference from community residents for healthcare utilization. A rational test was presented first to confirm the consistency, and then 16 pairs of choice tasks with 12 sociodemographic items were given to the respondents. Two hypothetical options for each set, without an opt-out option, were presented in each choice task. The latent class analysis (LCA) was used to analyse the data.

Results

Two thousand one hundred sixty respondents from 36 communities in 6 cities were recruited for our study. 2019 (93.47%) respondents completed valid discrete choice experiment (DCE) questionnaires. The LCA results suggested that four groups of similar preferences were identified. The first group (27.29%) labelled as “Comprehensive consideration” had an even preference of all four attributes. The second group (37.79%) labelled as “Price-driven” preferred low-price healthcare services. The third group labelled as “Near distance” showed a clear preference for seeking healthcare services nearby. The fourth group (34.18%) labelled as “Quality seeker” preferred the healthcare service provided by experts. Willingness to pay (WTP) results showed that people were willing to accept CNY202.12($29.37) for Traditional Chinese Medicine (TCM) services and willing to pay CNY604.31($87.81) for the service provided by experts.

Conclusions

Our study qualitatively measures the distinct preferences for healthcare utilization in community residents in China. The results suggest that the care provider, mode of services, travel time and cost should be considered in priority setting decisions. The study, however, reveals substantial disagreement in opinion of TCM between different population subgroups.

A Multinational European Study of Patient Preferences for Novel Diagnostics to Manage Antimicrobial Resistance

BACKGROUND

Novel diagnostics are needed to manage antimicrobial resistance (AMR). Patient preferences are important in determining whether diagnostic tests are successful in practice, but there are few data describing the test attributes which matter most to patients. We elicited patients' preferences for attributes of diagnostic tests that could be used to reduce unnecessary antibiotic use in primary care across seven European countries.

METHODS

We used an online stated preference survey, including a discrete choice experiment (DCE). The DCE explored how patients make trade-offs between three key attributes of diagnostic tests: the speed that results were available, confidence in the test results, and how convenient it is to take the test. Individuals were eligible to complete the survey if they had taken antibiotics within the last 2 years and were resident in Germany, Italy, Spain, France, Greece, the Netherlands or the United Kingdom (UK).

RESULTS

In total, 988 respondents completed the survey. The DCE responses illustrated that speed was the least important attribute in most countries. Responses from Germany and the Netherlands indicated that confidence was most important in these countries. Responses from the UK, France, Spain and Italy showed convenience as the most important attribute in these countries. Two attributes, confidence and convenience, were jointly favoured by respondents in Greece.

CONCLUSION

Patients in different European countries do not have the same preferences for the attributes of diagnostic tests to manage AMR in primary care. Failure to account for such differences during test development could reduce test uptake, result in continued overuse of antibiotics, and hamper marketisation.

Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review

BACKGROUND

Scale heterogeneity, or differences in the error variance of choices, may account for a significant amount of the observed variation in the results of discrete choice experiments (DCEs) when comparing preferences between different groups of respondents.

OBJECTIVE

The aim of this study was to identify if, and how, scale heterogeneity has been addressed in healthcare DCEs that compare the preferences of different groups.

METHODS

A systematic review identified all healthcare DCEs published between 1990 and February 2016. The full-text of each DCE was then screened to identify studies that compared preferences using data generated from multiple groups. Data were extracted and tabulated on year of publication, samples compared, tests for scale heterogeneity, and analytical methods to account for scale heterogeneity. Narrative analysis was used to describe if, and how, scale heterogeneity was accounted for when preferences were compared.

RESULTS

A total of 626 healthcare DCEs were identified. Of these 199 (32%) aimed to compare the preferences of different groups specified at the design stage, while 79 (13%) compared the preferences of groups identified at the analysis stage. Of the 278 included papers, 49 (18%) discussed potential scale issues, 18 (7%) used a formal method of analysis to account for scale between groups, and 2 (1%) accounted for scale differences between preference groups at the analysis stage. Scale heterogeneity was present in 65% (n = 13) of studies that tested for it. Analytical methods to test for scale heterogeneity included coefficient plots (n = 5, 2%), heteroscedastic conditional logit models (n = 6, 2%), Swait and Louviere tests (n = 4, 1%), generalised multinomial logit models (n = 5, 2%), and scale-adjusted latent class analysis (n = 2, 1%).

CONCLUSIONS

Scale heterogeneity is a prevalent issue in healthcare DCEs. Despite this, few published DCEs have discussed such issues, and fewer still have used formal methods to identify and account for the impact of scale heterogeneity. The use of formal methods to test for scale heterogeneity should be used, otherwise the results of DCEs potentially risk producing biased and potentially misleading conclusions regarding preferences for aspects of healthcare.

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.

Assessing Rationality in Discrete Choice Experiments in Health: An Investigation into the Use of Dominance Tests

BACKGROUND

Dominance tests are often applied to test for the rationality in the choice behavior of participants in discrete choice experiments (DCEs).

OBJECTIVES

To examine how dominance tests have been implemented in recent DCE applications in health and discuss their theoretical and empirical interpretation.

METHODS

Health-related DCEs published in 2015 were reviewed for the inclusion of tests on choice behavior. For studies that implemented a dominance test, information on application and interpretation of the test was extracted. Authors were contacted for test choice sets and observed proportions of subjects who chose the dominated option. Coefficients corresponding to the choice set were extracted to estimate the expected probability of choosing the dominated option with a logistic model and compared with the observed proportion. The theoretical range of expected probabilities of possible dominance tests was calculated.

RESULTS

Of 112 health-related DCEs, 49% included at least one test for choice behavior; 28 studies (25%) included a dominance test. The proportion of subjects in each study who chose the dominated option ranged from 0% to 21%. In 46% of the studies, the dominance test led to the exclusion of participants. In the 15 choice sets that were analyzed, 2 had larger proportions of participants choosing the dominated option than expected (P < 0.05).

CONCLUSIONS

Although dominance tests are frequently applied in DCEs, there is no consensus on how to account for them in data analysis and interpretation. Comparison of expected and observed proportions of participants failing the test might be indicative of DCE quality.

Improving quality care for diabetes in the community: What do Cypriot patients want?

Objective

To measure patient preferences for their diabetic care in community setting.

Design

Discrete-choice survey.

Setting

Community setting (primary physician and hospital sites) in Cyprus.

Participants

Diabetic patients attending community sites.

Main Outcome Measure(s)

Patient preferences, to estimate which components of quality healthcare service people value, their relative importance but also the potential shift to shared decision-making (SDM).

Results

Older respondents with experience of the private sector already received SDM (managing their care and choosing their treatments; detailed and accurate information, continuity of care; compassion for their personal situation) from their primary care physician with waiting time shorter than 1 h. They valued their 'current' option and they did not want to change it with other services. Younger people from the public sector valued a change in policy and wanted to move from their 'current' to alternative diabetic care services where the waiting times were shorter, they could not only manage their care but also choose their treatments (together with receiving information, continuity of care and compassionate care). Individuals agreed with receiving multidisciplinary care from a team of healthcare providers but they mostly preferred being supported by their primary care physician. The pooled sample valued their 'current' option but they also supported policy changes that would implement SDM service for everybody.

Conclusions

Diabetic patients value SDM and are willing to support a shift of practice to receive it not only in the private but also in the public sector. The forthcoming National Health Insurance Service would aim to address such developments as anticipated both in the European Troika's recommendations and the relevant laws.

Exploring the training and scope of practice of GPs in England, Germany and Spain

OBJECTIVE

To explore general practitioner (GP) training, continuing professional development, scope of practice, ethical issues and challenges in the working environment in three European countries.

METHOD

Qualitative study of 35 GPs from England, Germany and Spain working in urban primary care practices. Participants were recruited using convenience and snowball sampling techniques. Semi-structured interviews were recorded, transcribed and analysed by four independent researchers adopting a thematic approach.

RESULTS

Entrance to and length of GP training differ between the three countries, while continuing professional development is required in all three, although with different characteristics. Key variations in the scope of practice include whether there is a gatekeeping role, whether GPs work in multidisciplinary teams or singlehandedly, the existence of appraisal processes, and the balance between administrative and clinical tasks. However, similar challenges, including the need to adapt to an ageing population, end-of-life care, ethical dilemmas, the impact of austerity measures, limited time for patients and gaps in coordination between primary and secondary care are experienced by GPs in all three countries.

CONCLUSION

Primary health care variations have strong historical roots, derived from the different national experiences and the range of clinical services delivered by GPs. There is a need for an accessible source of information for GPs themselves and those responsible for safety and quality standards of the healthcare workforce. This paper maps out the current situation before Brexit is being implemented in the UK which could see many of the current EU arrangements and legislation to assure professional mobility between the UK and the rest of Europe dismantled.

Patients' preferences for primary health care - a systematic literature review of discrete choice experiments

BACKGROUND

Primary care is a key element of health care systems and addresses the main health problems of the population. Due to the demographic change, primary care even gains in importance. The knowledge of the patients' preferences can help policy makers as well as physicians to set priorities in their effort to make health care delivery more responsive to patients' needs. Our objective was to describe which aspects of primary care were included in preference studies and which of them were the most preferred aspects.

METHODS

In order to elicit the preferences for primary care, a systematic literature search was conducted. Two researchers searched three electronic databases (PubMed, Scopus, and PsycINFO) and conducted a narrative synthesis. Inclusion criteria were: focus on primary health care delivery, discrete choice experiment as elicitation method, and studies published between 2006 and 2015 in English language.

RESULTS

We identified 18 studies that elicited either the patients' or the population's preferences for primary care based on a discrete choice experiment. Altogether the studies used 16 structure attributes, ten process attributes and four outcome attributes. The most commonly applied structure attribute was "Waiting time till appointment", the most frequently used process attribute was "Shared decision making / professional's attention paid to your views". "Receiving the 'best' treatment" was the most commonly applied outcome attribute. Process attributes were most often the ones of highest importance for patients or the population. The attributes and attribute levels used in the discrete choice experiments were identified by literature research, qualitative research, expert interviews, or the analysis of policy documents.

CONCLUSIONS

The results of the DCE studies show different preferences for primary health care. The diversity of the results may have several reasons, such as the method of analysis, the selection procedure of the attributes and their levels or the specific research question of the study. As the results of discrete choice experiments depend on many different factors, it is important for a better comprehensibility of the studies to transparently report the steps undertaken in a study as well as the interim results regarding the identification of attributes and levels.