scholarly journals Pricing through health apps generated data—Digital dividend as a game changer: Discrete choice experiment

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254786
Author(s):  
Alexandra Heidel ◽  
Christian Hagist ◽  
Christian Schlereth
Keyword(s):  
Data Processing ◽  
Medical Device ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Health Data ◽  
Third Parties ◽  
Price Expectations ◽  
Monetary Compensation ◽  
Digital Dividend

Objectives The objective of this paper is to study under which circumstances wearable and health app users would accept a compensation payment, namely a digital dividend, to share their self-tracked health data. Methods We conducted a discrete choice experiment alternative, a separated adaptive dual response. We chose this approach to reduce extreme response behavior, considering the emotionally-charged topic of health data sales, and to measure willingness to accept. Previous experiments in lab settings led to demands for high monetary compensation. After a first online survey and two pre-studies, we validated four attributes for the final online study: monthly bonus payment, stakeholder handling the data (e.g., health insurer, pharmaceutical or medical device companies, universities), type of data, and data sales to third parties. We used a random utility framework to evaluate individual choice preferences. To test the expected prices of the main study for robustness, we assigned respondents randomly to one of two identical questionnaires with varying price ranges. Results Over a period of three weeks, 842 respondents participated in the main survey, and 272 respondents participated in the second survey. The participants considered transparency about data processing and no further data sales to third parties as very important to the decision to share data with different stakeholders, as well as adequate monetary compensation. Price expectations resulting from the experiment were high; pharmaceutical and medical device companies would have to pay an average digital dividend of 237.30€/month for patient generated health data of all types. We also observed an anchor effect, which means that people formed price expectations during the process and not ex ante. We found a bimodal distribution between relatively low price expectations and relatively high price expectations, which shows that personal data selling is a divisive societal issue. However, the results indicate that a digital dividend could be an accepted economic incentive system to gather large-scale, self-tracked data for research and development purposes. After the COVID-19 crisis, price expectations might change due to public sensitization to the need for big data research on patient generated health data. Conclusion A continuing success of existing data donation models is highly unlikely. The health care sector needs to develop transparency and trust in data processing. An adequate digital dividend could be an effective long-term measure to convince a diverse and large group of people to share high-quality, continuous data for research purposes.

scholarly journals Governance mechanisms for sharing of health data: An approach towards selecting attributes for complex discrete choice experiment studies

2021 ◽  
Vol 66 ◽  
pp. 101625
Author(s):  
Jennifer Viberg Johansson ◽  
Nisha Shah ◽  
Eik Haraldsdóttir ◽  
Heidi Beate Bentzen ◽  
Sarah Coy ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Health Data ◽  
Governance Mechanisms

scholarly journals Publics’ preferences for sharing health data: a discrete choice experiment (Preprint)

10.2196/29614 ◽  
2021 ◽  
Author(s):  
Jennifer Johansson ◽  
Heidi Beate Bentzen ◽  
Nisha Shah3 ◽  
Eik Haraldsdóttir4 ◽  
Guðbjörg Andrea Jónsdóttir ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Health Data

scholarly journals Publics’ preferences for sharing health data: a discrete choice experiment (Preprint)

2021 ◽  
Author(s):  
Jennifer Johansson ◽  
Heidi Beate Bentzen ◽  
Nisha Shah3 ◽  
Eik Haraldsdóttir4 ◽  
Guðbjörg Andrea Jónsdóttir ◽  
...  
Keyword(s):  
Health Information ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Latent Class ◽  
Technological Development ◽  
Digital Health ◽  
Health Data ◽  
Governance Mechanism ◽  
Opt Out

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.

The essential ingredients of research supervision: A discrete-choice experiment.

2019 ◽  
Vol 111 (7) ◽  
pp. 1243-1260 ◽  
Author(s):  
Alex Roach ◽  
Bruce K. Christensen ◽  
Elizabeth Rieger
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Research Supervision

INDIVIDUALS' PREFERENCES FOR ESOPHAGEAL CANCER SCREENING STRATEGIES: A DISCRETE CHOICE EXPERIMENT

2019 ◽  
Author(s):  
Y Peters ◽  
E van Grinsven ◽  
M van de Haterd ◽  
D van Lankveld ◽  
J Verbakel ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Strategies

Preferences for antiviral therapy of chronic hepatitis C: a discrete choice experiment

2016 ◽  
Vol 18 (2) ◽  
pp. 155-165 ◽  
Author(s):  
Axel C. Mühlbacher ◽  
John F. P. Bridges ◽  
Susanne Bethge ◽  
Ch.-Markos Dintsios ◽  
Anja Schwalm ◽  
...  
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis C ◽  
Antiviral Therapy ◽  
Chronic Hepatitis C ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment

Patient preferences for specialist outpatient video consultations: A discrete choice experiment

2021 ◽  
pp. 1357633X2110228
Author(s):  
Centaine L Snoswell ◽  
Anthony C Smith ◽  
Matthew Page ◽  
Liam J Caffery
Keyword(s):  
General Practitioner ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Healthcare Delivery ◽  
General Practitioner Practice ◽  
Specialist Care ◽  
Time Away ◽  
Out Of Pocket Costs

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.

scholarly journals Understanding what women want: eliciting preference for delivery health facility in a rural subcounty in Kenya, a discrete choice experiment

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e038865
Author(s):  
Jackline Oluoch-Aridi ◽  
Mary B Adam ◽  
Francis Wafula ◽  
Gilbert Kokwaro
Keyword(s):  
Quality Of Care ◽  
Health Facility ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Home Delivery ◽  
Process Indicator ◽  
Opt Out ◽  
Women’S Preferences

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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