scholarly journals Using discrete choice experiments to define patient preferences for outcomes in trials

Trials ◽  
2013 ◽  
Vol 14 (S1) ◽  
Author(s):  
Emily Fargher ◽  
Dyfrig Hughes ◽  
Adele Ring ◽  
Ann Jacoby ◽  
Margaret Rawnsley ◽  
...  
2019 ◽  
Vol 12 (6) ◽  
pp. 559-569 ◽  
Author(s):  
Renata Leborato Guerra ◽  
Luciana Castaneda ◽  
Rita de Cássia Ribeiro de Albuquerque ◽  
Camila Belo Tavares Ferreira ◽  
Flávia de Miranda Corrêa ◽  
...  

2021 ◽  
Author(s):  
Alan R. Ellis ◽  
Kathleen Thomas ◽  
Kirsten Howard ◽  
Mandy Ryan ◽  
Esther de Bekker-Grob ◽  
...  

2020 ◽  
Vol 17 (5) ◽  
pp. 467-477
Author(s):  
I Eshun-Wilson ◽  
H-Y Kim ◽  
S Schwartz ◽  
M Conte ◽  
D V Glidden ◽  
...  

Abstract Purpose of Review Aligning HIV treatment services with patient preferences can promote long-term engagement. A rising number of studies solicit such preferences using discrete choice experiments, but have not been systematically reviewed to seek generalizable insights. Using a systematic search, we identified eleven choice experiments evaluating preferences for HIV treatment services published between 2004 and 2020. Recent Findings Across settings, the strongest preference was for nice, patient-centered providers, for which participants were willing to trade considerable amounts of time, money, and travel distance. In low- and middle-income countries, participants also preferred collecting antiretroviral therapy (ART) less frequently than 1 monthly, but showed no strong preference for 3-compared with 6-month refill frequency. Facility waiting times and travel distances were also important but were frequently outranked by stronger preferences. Health facility–based services were preferred to community- or home-based services, but this preference varied by setting. In high-income countries, the availability of unscheduled appointments was highly valued. Stigma was rarely explored and costs were a ubiquitous driver of preferences. Summary While present improvement efforts have focused on designs to enhance access (reduced waiting time, travel distance, and ART refill frequency), few initiatives focus on the patient-provider interaction, which represents a promising critical area for inquiry and investment. If HIV programs hope to truly deliver patient-centered care, they will need to incorporate patient preferences into service delivery strategies. Discrete choice experiments can not only inform such strategies but also contribute to prioritization efforts for policy-making decisions.


2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Laura J. James ◽  
Germaine Wong ◽  
Allison Tong ◽  
Jonathan C. Craig ◽  
Kirsten Howard ◽  
...  

2017 ◽  
Vol 27 (12) ◽  
pp. 3544-3559 ◽  
Author(s):  
Anna Liza M Antonio ◽  
Robert E Weiss ◽  
Christopher S Saigal ◽  
Ely Dahan ◽  
Catherine M Crespi

In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.


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