Literature DB >> 26610687

Discrete choice experiments of pharmacy services: a systematic review.

Caroline Vass1, Ewan Gray1, Katherine Payne2.   

Abstract

Background Two previous systematic reviews have summarised the application of discrete choice experiments to value preferences for pharmacy services. These reviews identified a total of twelve studies and described how discrete choice experiments have been used to value pharmacy services but did not describe or discuss the application of methods used in the design or analysis. Aims (1) To update the most recent systematic review and critically appraise current discrete choice experiments of pharmacy services in line with published reporting criteria and; (2) To provide an overview of key methodological developments in the design and analysis of discrete choice experiments. Methods The review used a comprehensive strategy to identify eligible studies (published between 1990 and 2015) by searching electronic databases for key terms related to discrete choice and best-worst scaling (BWS) experiments. All healthcare choice experiments were then hand-searched for key terms relating to pharmacy. Data were extracted using a published checklist. Results A total of 17 discrete choice experiments eliciting preferences for pharmacy services were identified for inclusion in the review. No BWS studies were identified. The studies elicited preferences from a variety of populations (pharmacists, patients, students) for a range of pharmacy services. Most studies were from a United Kingdom setting, although examples from Europe, Australia and North America were also identified. Discrete choice experiments for pharmacy services tended to include more attributes than non-pharmacy choice experiments. Few studies reported the use of qualitative research methods in the design and interpretation of the experiments (n = 9) or use of new methods of analysis to identify and quantify preference and scale heterogeneity (n = 4). No studies reported the use of Bayesian methods in their experimental design. Conclusion Incorporating more sophisticated methods in the design of pharmacy-related discrete choice experiments could help researchers produce more efficient experiments which are better suited to valuing complex pharmacy services. Pharmacy-related discrete choice experiments could also benefit from more sophisticated analytical techniques such as investigations into scale and preference heterogeneity. Employing these sophisticated methods for both design and analysis could extend the usefulness of discrete choice experiments to inform health and pharmacy policy.

Entities:  

Keywords:  Best–worst scaling; Discrete choice experiment; Preferences; Review; Values

Mesh:

Year:  2016        PMID: 26610687     DOI: 10.1007/s11096-015-0221-1

Source DB:  PubMed          Journal:  Int J Clin Pharm


  59 in total

1.  Rationalising the 'irrational': a think aloud study of discrete choice experiment responses.

Authors:  Mandy Ryan; Verity Watson; Vikki Entwistle
Journal:  Health Econ       Date:  2009-03       Impact factor: 3.046

2.  Pharmacists' acceptable levels of compensation for MTM services: a conjoint analysis.

Authors:  Junling Wang; Song Hee Hong; Songmei Meng; Lawrence M Brown
Journal:  Res Social Adm Pharm       Date:  2010-11-05

3.  Eliciting preferences to the EQ-5D-5L health states: discrete choice experiment or multiprofile case of best-worst scaling?

Authors:  Feng Xie; Eleanor Pullenayegum; Kathryn Gaebel; Mark Oppe; Paul F M Krabbe
Journal:  Eur J Health Econ       Date:  2013-04-04

Review 4.  Clinical pharmacists and inpatient medical care: a systematic review.

Authors:  Peter J Kaboli; Angela B Hoth; Brad J McClimon; Jeffrey L Schnipper
Journal:  Arch Intern Med       Date:  2006-05-08

5.  A comparison of preferences of targeted therapy for metastatic renal cell carcinoma between the patient group and health care professional group in South Korea.

Authors:  Mi-Hai Park; Changik Jo; Eun Young Bae; Eui-Kyung Lee
Journal:  Value Health       Date:  2012 Sep-Oct       Impact factor: 5.725

6.  Making sense of patient priorities: applying discrete choice methods in primary care using 'think aloud' technique.

Authors:  Sudeh Cheraghi-Sohi; Peter Bower; Nicola Mead; Ruth McDonald; Diane Whalley; Martin Roland
Journal:  Fam Pract       Date:  2007-05-02       Impact factor: 2.267

7.  Developing attributes and levels for discrete choice experiments using qualitative methods.

Authors:  Joanna Coast; Sue Horrocks
Journal:  J Health Serv Res Policy       Date:  2007-01

8.  Best--worst scaling: What it can do for health care research and how to do it.

Authors:  Terry N Flynn; Jordan J Louviere; Tim J Peters; Joanna Coast
Journal:  J Health Econ       Date:  2006-05-16       Impact factor: 3.883

9.  Are Thai MSM willing to take PrEP for HIV prevention? An analysis of attitudes, preferences and acceptance.

Authors:  Ana Wheelock; Andreas B Eisingerich; Jintanat Ananworanich; Gabriela B Gomez; Timothy B Hallett; Mark R Dybul; Peter Piot
Journal:  PLoS One       Date:  2013-01-14       Impact factor: 3.240

10.  Patient preferences for adherence to treatment for osteoarthritis: the MEdication Decisions in Osteoarthritis Study (MEDOS).

Authors:  Tracey-Lea Laba; Jo-anne Brien; Marlene Fransen; Stephen Jan
Journal:  BMC Musculoskelet Disord       Date:  2013-05-06       Impact factor: 2.362

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  18 in total

1.  Identifying Community Pharmacist Preferences For Prescribing Services in Primary Care in New Zealand: A Discrete Choice Experiment.

Authors:  Rakhee Raghunandan; Kirsten Howard; Carlo A Marra; June Tordoff; Alesha Smith
Journal:  Appl Health Econ Health Policy       Date:  2020-10-19       Impact factor: 2.561

2.  Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.

Authors:  Mo Zhou; Winter Maxwell Thayer; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2018-02       Impact factor: 4.981

3.  A Hierarchical Bayes Approach to Modeling Heterogeneity in Discrete Choice Experiments: An Application to Public Preferences for Prenatal Screening.

Authors:  Tima Mohammadi; Wei Zhang; Julie Sou; Sylvie Langlois; Sarah Munro; Aslam H Anis
Journal:  Patient       Date:  2020-04       Impact factor: 3.883

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

Authors:  Stuart J Wright; Caroline M Vass; Gene Sim; Michael Burton; Denzil G Fiebig; Katherine Payne
Journal:  Patient       Date:  2018-10       Impact factor: 3.883

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

Authors:  Ming-Zhu Jiang; Qiang Fu; Ju-Yang Xiong; Xiang-Lin Li; Er-Ping Jia; Ying-Ying Peng; Xiao Shen
Journal:  BMC Health Serv Res       Date:  2020-05-18       Impact factor: 2.655

6.  Discrete Choice Experiments in Health Economics: Past, Present and Future.

Authors:  Vikas Soekhai; Esther W de Bekker-Grob; Alan R Ellis; Caroline M Vass
Journal:  Pharmacoeconomics       Date:  2019-02       Impact factor: 4.981

7.  Identifying New Zealand Public Preferences for Pharmacist Prescribers in Primary Care: A Discrete Choice Experiment.

Authors:  Rakhee Raghunandan; Kirsten Howard; Carlo A Marra; June Tordoff; Alesha Smith
Journal:  Patient       Date:  2021-06-10       Impact factor: 3.883

8.  Job preferences of undergraduate pharmacy students in China: a discrete choice experiment.

Authors:  Ping Liu; Shimeng Liu; Tiantian Gong; Quan Li; Gang Chen; Shunping Li
Journal:  Hum Resour Health       Date:  2021-07-06

9.  Preferences of Patients and Pharmacists with Regard to the Management of Drug-Drug Interactions: A Choice-Based Conjoint Analysis.

Authors:  Mette Heringa; Annemieke Floor-Schreudering; Hans Wouters; Peter A G M De Smet; Marcel L Bouvy
Journal:  Drug Saf       Date:  2018-02       Impact factor: 5.606

10.  Understanding Midwives' Preferences for Providing Information About Newborn Bloodspot Screening.

Authors:  Stuart James Wright; Fiona Ulph; Tina Lavender; Nimarta Dharni; Katherine Payne
Journal:  MDM Policy Pract       Date:  2018-01-18
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