scholarly journals Understanding uptake of digital health products: Methodology tutorial for a Discrete Choice Experiment using a Bayesian efficient design (Preprint)

Author(s):  
Dorothy Szinay ◽  
Rory Cameron ◽  
Felix Naughton ◽  
Jennifer A. Whitty ◽  
Jamie Brown ◽  
...  
2021 ◽  
Author(s):  
Dorothy Szinay ◽  
Rory Cameron ◽  
Felix Naughton ◽  
Jennifer A. Whitty ◽  
Jamie Brown ◽  
...  

UNSTRUCTURED Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method; a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations where revealed preferences are difficult to collect but is much less used in the field of digital health. This article outlines the stages involved in developing a discrete choice experiment. As a case study, it uses the application of a DCE for revealing preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of two or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique.


BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e053270
Author(s):  
Xiaolan Yu ◽  
Haini Bao ◽  
Jianwei Shi ◽  
Xiaoyu Yuan ◽  
Liangliang Qian ◽  
...  

ObjectivesOur study aimed to support evidence-informed policy-making on patient-centred care by investigating preferences for healthcare services among hypertension patients.DesignWe identified six attributes of healthcare services for a discrete choice experiment (DCE), and applied Bayesian-efficient design with blocking techniques to generate choice sets. After conducting the DCE, we used a mixed logit regression model to investigate patients’ preferences for each attribute and analysed the heterogeneities in preferences. Estimates of willingness to pay were derived from regression coefficients.SettingThe DCE was conducted in Jiangsu province and Shanghai municipality in China.ParticipantsPatients aged 18 years or older with a history of hypertension for at least 2 years and who took medications regularly were recruited.ResultsPatients highly valued healthcare services that produced good treatment effects (β=4.502, p<0.001), followed by travel time to healthcare facilities within 1 hour (β=1.285, p<0.001), and the effective physician–patient communication (β=0.771, p<0.001). Continuity of care and minimal waiting time were also positive predictors (p<0.001). However, the out-of-pocket cost was a negative predictor of patients’ choice (β=−0.168, p<0.001). Older adults, patients with good health-related quality of life, had comorbidities, and who were likely to visit secondary and tertiary hospitals cared more about favourable effects (p<0.05). Patients were willing to pay ¥2489 (95% CI ¥2013 to ¥2965) as long as the clinical benefits gained were substantial.ConclusionsOur findings highlight the importance of effective, convenient, efficient, coordinated and patient-centred care for chronic diseases like hypertension. Policy-makers and healthcare providers are suggested to work on aligning the service provision with patients’ preferences.


2021 ◽  
Author(s):  
Jennifer Johansson ◽  
Heidi Beate Bentzen ◽  
Nisha Shah3 ◽  
Eik Haraldsdóttir4 ◽  
Guðbjörg Andrea Jónsdóttir ◽  
...  

BACKGROUND The digital technological development in the last 20 years has led to a significant growth in collecting, using and sharing health data digitally. In order to maintain public trust in the digital society and for acceptable policy making in the future, it is important to investigate peoples’ preferences for sharing digital health data. OBJECTIVE The aim of this study was to elicit the publics’ preferences in different Northern-European countries (the UK, Norway, Iceland and Sweden) for sharing health information in different contexts. METHODS A discrete choice experiment was answered by 1,967 individuals. Respondents completed several ‘choice tasks’ which asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute level estimates and the heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts where data is shared from the estimates. RESULTS All attributes influenced the participants’ willingness to share health information. The most important attribute was whether the respondents will be informed about their data being shared. The possibility to opt-out from sharing data was preferred over the opportunity to consent (opt-in). CONCLUSIONS Participants from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for the new use. Offering respondents information about the use of their data and the possibility to opt-out is the most preferred governance mechanism.


2018 ◽  
Vol 28 (2) ◽  
pp. 168-175 ◽  
Author(s):  
John Buckell ◽  
Joachim Marti ◽  
Jody L Sindelar

ObjectivesTo provide the policy-relevant estimates of impacts of alternative flavour bans on preferences and demand for cigarettes and e-cigarettes in adult smokers and recent quitters.MethodsA best–best discrete choice experiment (DCE) is used to elicit smokers’ and recent quitters’ preferences for flavours, price, health impact and nicotine level in cigarettes and e-cigarettes. Choice of tobacco products and an opt-out option were examined. An efficient design yielded 36 choice sets. Exploded logit choice models were estimated. Flavour bans are modelled by restricting flavour coefficients in the estimated model.Setting and participantsA sample of 2031 adult smokers and recent quitters was recruited to complete an online survey and DCE.ResultsCurrent smokers and recent quitters, on average, prefer cigarettes and menthol cigarettes over flavoured e-cigarettes. However, there is substantial preference heterogeneity by younger adults (ages 18–25), race/ethnicity and respondents with higher education. Our predictions suggest that a ban on menthol cigarettes would produce the greatest reduction in the choice of cigarettes (−5.2%), but with an accompanying increase in e-cigarettes use (3.8%). In contrast, banning flavours in e-cigarettes, while allowing menthol in cigarettes would result in the greatest increase in the selection of cigarettes (8.3%), and a decline in the use of e-cigarettes (−11.1%). A ban on all flavours, but tobacco in both products would increase ‘opting-out’ the most (5.2%) but would also increase choice of cigarettes (2.7%) and decrease choice of e-cigarettes (−7.9%).ConclusionsA ban on flavoured e-cigarettes alone would likely increase the choice of cigarettes in smokers, arguably the more harmful way of obtaining nicotine, whereas a ban on menthol cigarettes alone would likely be more effective in reducing the choice of cigarettes. A ban on all flavours in both products would likely reduce the smoking/vaping rates, but the use of cigarettes would be higher than in the status quo. Policy-makers should use these results to guide the choice of flavour bans in light of their stance on the potential health impacts both products.


2019 ◽  
Vol 111 (7) ◽  
pp. 1243-1260 ◽  
Author(s):  
Alex Roach ◽  
Bruce K. Christensen ◽  
Elizabeth Rieger

2019 ◽  
Author(s):  
Y Peters ◽  
E van Grinsven ◽  
M van de Haterd ◽  
D van Lankveld ◽  
J Verbakel ◽  
...  

2016 ◽  
Vol 18 (2) ◽  
pp. 155-165 ◽  
Author(s):  
Axel C. Mühlbacher ◽  
John F. P. Bridges ◽  
Susanne Bethge ◽  
Ch.-Markos Dintsios ◽  
Anja Schwalm ◽  
...  

2021 ◽  
pp. 1357633X2110228
Author(s):  
Centaine L Snoswell ◽  
Anthony C Smith ◽  
Matthew Page ◽  
Liam J Caffery

Introduction Telehealth has been shown to improve access to care, reduce personal expenses and reduce the need for travel. Despite these benefits, patients may be less inclined to seek a telehealth service, if they consider it inferior to an in-person encounter. The aims of this study were to identify patient preferences for attributes of a healthcare service and to quantify the value of these attributes. Methods We surveyed patients who had taken an outpatient telehealth consult in the previous year using a survey that included a discrete choice experiment. We investigated patient preferences for attributes of healthcare delivery and their willingness to pay for out-of-pocket costs. Results Patients ( n = 62) preferred to have a consultation, regardless of type, than no consultation at all. Patients preferred healthcare services with lower out-of-pocket costs, higher levels of perceived benefit and less time away from usual activities ( p < 0.008). Most patients preferred specialist care over in-person general practitioner care. Their order of preference to obtain specialist care was a videoconsultation into the patient’s local general practitioner practice or hospital ( p < 0.003), a videoconsultation into the home, and finally travelling for in-person appointment. Patients were willing to pay out-of-pocket costs for attributes they valued: to be seen by a specialist over videoconference ($129) and to reduce time away from usual activities ($160). Conclusion Patients value specialist care, lower out-of-pocket costs and less time away from usual activities. Telehealth is more likely than in-person care to cater to these preferences in many instances.


BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e038865
Author(s):  
Jackline Oluoch-Aridi ◽  
Mary B Adam ◽  
Francis Wafula ◽  
Gilbert Kokwaro

ObjectiveTo identify what women want in a delivery health facility and how they rank the attributes that influence the choice of a place of delivery.DesignA discrete choice experiment (DCE) was conducted to elicit rural women’s preferences for choice of delivery health facility. Data were analysed using a conditional logit model to evaluate the relative importance of the selected attributes. A mixed multinomial model evaluated how interactions with sociodemographic variables influence the choice of the selected attributes.SettingSix health facilities in a rural subcounty.ParticipantsWomen aged 18–49 years who had delivered within 6 weeks.Primary outcomeThe DCE required women to select from hypothetical health facility A or B or opt-out alternative.ResultsA total of 474 participants were sampled, 466 participants completed the survey (response rate 98%). The attribute with the strongest association with health facility preference was having a kind and supportive healthcare worker (β=1.184, p<0.001), second availability of medical equipment and drug supplies (β=1.073, p<0.001) and third quality of clinical services (β=0.826, p<0.001). Distance, availability of referral services and costs were ranked fourth, fifth and sixth, respectively (β=0.457, p<0.001; β=0.266, p<0.001; and β=0.000018, p<0.001). The opt-out alternative ranked last suggesting a disutility for home delivery (β=−0.849, p<0.001).ConclusionThe most highly valued attribute was a process indicator of quality of care followed by technical indicators. Policymakers need to consider women’s preferences to inform strategies that are person centred and lead to improvements in quality of care during delivery.


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