scholarly journals PHP3 Patient Preferences Considering the Choice of Health Care Providers in Hungary – Results From Discrete Choice Experiment

2011 ◽  
Vol 14 (7) ◽  
pp. A333-A334
Author(s):  
P. Baji ◽  
M. Pavlova ◽  
L. Gulacsi ◽  
W. Groot
Keyword(s):  
Health Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Health Care Providers ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Care Providers

scholarly journals Personal health records in the Netherlands: potential user preferences quantified by a discrete choice experiment

2016 ◽  
Vol 24 (3) ◽  
pp. 529-536 ◽  
Author(s):  
Domino Determann ◽  
Mattijs S Lambooij ◽  
Dorte Gyrd-Hansen ◽  
Esther W de Bekker-Grob ◽  
Ewout W Steyerberg ◽  
...  
Keyword(s):  
Health Care ◽  
Data Storage ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Health Care Providers ◽  
Choice Experiment ◽  
Personal Health Records ◽  
Personal Health ◽  
Care Providers ◽  
Health Records

Objective: To identify groups of potential users based on their preferences for characteristics of personal health records (PHRs) and to estimate potential PHR uptake. Methods: We performed a discrete choice experiment, which consisted of 12 choice scenarios, each comprising 2 hypothetical PHR alternatives and an opt-out. The alternatives differed based on 5 characteristics. The survey was administered to Internet panel members of the Dutch Federation of Patients and Consumer Organizations. We used latent class models to analyze the data. Results: A total of 1,443 potential PHR users completed the discrete choice experiment. We identified 3 latent classes: “refusers” (class probability 43%), “eager adopters” (37%), and “reluctant adopters” (20%). The predicted uptake for the reluctant adopters ranged from 4% in the case of a PHR with the worst attribute levels to 68% in the best case. Those with 1 or more chronic diseases were significantly more likely to belong to the eager adopter class. The data storage provider was the most decisive aspect for the eager and reluctant adopters, while cost was most decisive for the refusers. Across all classes, health care providers and independent organizations were the most preferred data storage providers. Conclusion: We identified 3 groups, of which 1 group (more than one-third of potential PHR users) indicated great interest in a PHR irrespective of PHR characteristics. Policymakers who aim to expand the use of PHRs will be most successful when health care providers and health facilities or independent organizations store PHR data while refraining from including market parties.

scholarly journals Preferences of psychotherapists for blended mental health interventions in Germany: a discrete choice experiment

2021 ◽  
Author(s):  
Elena Phillips ◽  
Sebastian Himmler ◽  
Jonas Schreyögg
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Mental Health Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Health Care Providers ◽  
Choice Experiment ◽  
Financial Incentive ◽  
Care Providers ◽  
Choice Data

Abstract Objectives: Digital treatment formats are emerging within mental health care. Evidence suggests that mental health care providers and recipients prefer a combination of digital and traditional elements within psychotherapy treatment formats, also called blended care (BC), over standalone digital formats. We examined the attitudes and preferences of licensed psychotherapists in Germany regarding such BC applications.Methods: We fielded a survey among psychotherapists, including questions about attitudes, previous experiences, and expectations regarding BC, as well as a discrete choice experiment. Attributes for the experiment were developed using a stepwise qualitative approach. A Bayesian D-efficient design was used to generate the choice tasks. The choice data were analyzed by applying mixed logit models.Results: The survey was completed by 200 psychotherapists. Attitudes towards BC were mainly positive, with strong reported intentions to use BC formats. In the choice experiment, recommendation from a professional society for a BC online component was the most important characteristic. Greater effectiveness and a larger share of face-to-face vs. online time were also desired features, while a financial incentive to use BC was less relevant.

scholarly journals Preferences for Sun Protection With a Self-Monitoring App: Protocol of a Discrete Choice Experiment Study

10.2196/16087 ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. e16087 ◽  
Author(s):  
Vasileios Nittas ◽  
Margot Mütsch ◽  
Milo Alan Puhan
Keyword(s):  
Health Care ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Sun Protection ◽  
Fractional Factorial ◽  
Rapid Review ◽  
Care Providers ◽  
Self Monitoring ◽  
Ongoing Research

Background The incidence of sun-exposure-related skin conditions, such as melanoma, is a gradually increasing and largely preventable public health problem. Simultaneously, the availability of mobile apps that enable the self-monitoring of health behavior and outcomes is ever increasing. Inevitably, recent years have seen an emerging volume of electronic patient-generated health data (PGHD), as well as their targeted application across primary prevention areas, including sun protection and skin health. Despite their preventive potential, the actual impact of these apps relies on the engagement of health care consumers, who are primarily responsible for recording, sharing, and using their PGHD. Exploring preferences is a key step toward facilitating consumer engagement and ultimately realizing their potential. Objective This paper describes an ongoing research project that aims to elicit the preferences of health care consumers for sun protection via app-based self-monitoring. Methods A discrete choice experiment (DCE) will be conducted to explore how healthy consumers choose between two alternative preventive self-monitoring apps. DCE development and attribute selection were built on extensive qualitative work, consisting of the secondary use of a previously conducted scoping review, a rapid review of reviews, 13 expert interviews, and 12 health care consumer interviews, the results of which are reported in this paper. Following D-optimality criteria, a fractional factorial survey design was generated. The final DCE will be administered in the waiting room of a travel clinic, targeting a sample of 200 participants. Choice data will be analyzed with conditional logit and multinomial logit models, accounting for individual participant characteristics. Results An ethics approval was waived by the Ethics Committee Zurich. The study started in September 2019 and estimated data collection and completion is set for January 2020. Five two-level attributes have been selected for inclusion in the DCE, addressing (1) data generation methods, (2) privacy control, (3) data sharing with general practitioner, (4) reminder timing, and (5) costs. Data synthesis, analysis, and reporting are planned for January and February 2020. Results are expected to be submitted for publication by February 2020. Conclusions Our results will target technology developers, health care providers, and policy makers, potentially offering some guidance on how to design or use sun-protection-focused self-monitoring apps in ways that are responsive to consumer preferences. Preferences are ultimately linked to engagement and motivation, which are key elements for the uptake and success of digital health. Our findings will inform the design of person-centered apps, while also inspiring future preference-eliciting research in the field of emerging and complex eHealth services. International Registered Report Identifier (IRRID) PRR1-10.2196/16087

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 Patient preferences for use of virtual consultations in an orthopaedic rehabilitation setting: Results from a discrete choice experiment

2021 ◽  
pp. 135581962110354
Author(s):  
Anthony W Gilbert ◽  
Emmanouil Mentzakis ◽  
Carl R May ◽  
Maria Stokes ◽  
Jeremy Jones
Keyword(s):  
Conceptual Model ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Best Practice ◽  
Time Of Day ◽  
Problem Area ◽  
Fractional Factorial ◽  
The Impact

Objective Virtual Consultations may reduce the need for face-to-face outpatient appointments, thereby potentially reducing the cost and time involved in delivering health care. This study reports a discrete choice experiment (DCE) that identifies factors that influence patient preferences for virtual consultations in an orthopaedic rehabilitation setting. Methods Previous research from the CONNECT (Care in Orthopaedics, burdeN of treatmeNt and the Effect of Communication Technology) Project and best practice guidance informed the development of our DCE. An efficient fractional factorial design with 16 choice scenarios was created that identified all main effects and partial two-way interactions. The design was divided into two blocks of eight scenarios each, to reduce the impact of cognitive fatigue. Data analysis were conducted using binary logit regression models. Results Sixty-one paired response sets (122 subjects) were available for analysis. DCE factors (whether the therapist is known to the patient, duration of appointment, time of day) and demographic factors (patient qualifications, access to equipment, difficulty with activities, multiple health issues, travel costs) were significant predictors of preference. We estimate that a patient is less than 1% likely to prefer a virtual consultation if the patient has a degree, is without access to the equipment and software to undertake a virtual consultation, does not have difficulties with day-to-day activities, is undergoing rehabilitation for one problem area, has to pay less than £5 to travel, is having a consultation with a therapist not known to them, in 1 weeks’ time, lasting 60 minutes, at 2 pm. We have developed a simple conceptual model to explain how these factors interact to inform preference, including patients’ access to resources, context for the consultation and the requirements of the consultation. Conclusions This conceptual model provides the framework to focus attention towards factors that might influence patient preference for virtual consultations. Our model can inform the development of future technologies, trials, and qualitative work to further explore the mechanisms that influence preference.

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