| Citation: |
MAO Run, CAI Yiyuan, YANG Wei, LIU Zhiguo, LINGHU Lang, CHEN Jiajia, LIANG Mengjiao, HUANG Lieyu, LIU Siyuan, XU Dong. Stakeholder Preference Assessment in Implementation Research: Application of Best-worst Scaling[J]. Medical Journal of Peking Union Medical College Hospital, 2025, 16(1): 224-234. DOI: 10.12290/xhyxzz.2024-0693
|
In the field of healthcare service, it is crucial to optimize medical innovation services by combining the preferences of health service providers and demanders (i.e., stakeholders). The best-worst scaling (BWS) method is a recently developed stated preference method for assessing preferences with distinctive advantages. Nevertheless, there is a lack of a comprehensive introduction to stakeholder preference assessment using BWS, thus constraining its applications and promotion. This paper introduces the process of using BWS to assess service providers' preferences for the Shared Medical Appointment for diabetes (SMART), an integrated healthcare service of medicine and health management, in the hope of providing reference for researchers for promoting the use of BWS in implementation research.
| [1] |
Williams N J, Candon M, Stewart R E, et al. Community stakeholder preferences for evidence-based practice implementation strategies in behavioral health: a best-worst scaling choice experiment[J]. BMC Psychiatry, 2021, 21(1): 74. DOI: 10.1186/s12888-021-03072-x
|
| [2] |
Salloum R G, Bishop J R, Elchynski A L, et al. Best-worst scaling methodology to evaluate constructs of the Consoli-dated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy[J]. Implement Sci Commun, 2022, 3(1): 52. DOI: 10.1186/s43058-022-00300-7
|
| [3] |
Irie W C, Kerkhoff A, Kim H Y, et al. Using stated preference methods to facilitate knowledge translation in implementation science[J]. Implement Sci Commun, 2024, 5(1): 32. DOI: 10.1186/s43058-024-00554-3
|
| [4] |
徐东, 陈江芸, 蔡毅媛. 实施科学的前世今生(上篇): 起源与发展[J]. 协和医学杂志, 2024, 15(2): 442-449. DOI: 10.12290/xhyxzz.2024-0023
Xu D, Chen J Y, Cai Y Y. Past and present of implementation science (part Ⅰ): origin and development[J]. Med J PUMCH, 2024, 15(2): 442-449. DOI: 10.12290/xhyxzz.2024-0023
|
| [5] |
Flynn T N, Louviere J J, Peters T J, et al. Best--worst scaling: What it can do for health care research and how to do it[J]. J Health Econ, 2007, 26(1): 171-189. DOI: 10.1016/j.jhealeco.2006.04.002
|
| [6] |
Ryan M, Kolstad J R, Rockers P C, et al. How to conduct a discrete choice experiment for health workforce recruitment and retention in remote and rural areas: a user guide with case studies[M]. Geneva: World Health Organization, 2012: 35.
|
| [7] |
杨惠芝, 王立敏, 李顺平. 离散选择实验和优劣尺度法在医药卫生领域联合使用及比较研究评述[J]. 医学与社会, 2022, 35(5): 102-107.
Yang H Z, Wang L M, Li S P. Review on the combined use and comparative study of discrete choice experiment and best-worst scaling in the field of healthcare[J]. Med Soc, 2022, 35(5): 102-107.
|
| [8] |
宋奎勐, 孟庆跃, Scott A, 等. 利用离散选择实验研究卫生服务人员工作偏好的国际研究进展[J]. 中国卫生经济, 2012, 31(10): 91-93.
Song K M, Meng Q Y, Scott A, et al. Analyzing health care providers' job preferences by discrete choice experiments: a literature review[J]. Chin Health Econ, 2012, 31(10): 91-93.
|
| [9] |
沈荣蕃, 祁小倩, 杨奇城, 等. 居民新冠疫苗接种意愿及选择接种偏好的优劣尺度法调查分析[J]. 现代养生, 2022, 22(12): 933-935.
Shen R F, Qi X Q, Yang Q C, et al. Survey and analysis of residents' willingness to vaccinate COVID-19 vaccine and preference for vaccination[J]. Health Prot Promot, 2022, 22(12): 933-935.
|
| [10] |
Norman R, Moorin R, Maxwell S, et al. Public attitudes on lung cancer screening and radiation risk: a best-worst experiment[J]. Value Health, 2020, 23(4): 495-505. DOI: 10.1016/j.jval.2019.11.006
|
| [11] |
顾文勇, 蒋明珠, 沈晓, 等. 基于优差测度法的慢性病患者对慢性病医防融合服务的偏好及支付意愿研究[J]. 中国社会医学杂志, 2022, 39(6): 720-724. DOI: 10.3969/j.issn.1673-5625.2022.06.026
Gu W Y, Jiang M Z, Shen X, et al. Study on the preference and willingness to pay of chronic disease patients to medical and prevention fusion service: based on best worst scaling method[J]. Chin J Soc Med, 2022, 39(6): 720-724. DOI: 10.3969/j.issn.1673-5625.2022.06.026
|
| [12] |
Louviere J J, Flynn T N, Marley A A J. Best-worst scaling: Theory, methods and applications[M]. Cambridge: Cambridge University Press, 2015: 83-84.
|
| [13] |
Severin F, Schmidtke J, Mühlbacher A, et al. Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments[J]. Eur J Hum Genet, 2013, 21(11): 1202-1208. DOI: 10.1038/ejhg.2013.36
|
| [14] |
Aizaki H, Fogarty J. R packages and tutorial for case 1 best-worst scaling[J]. J Choice Model, 2023, 46: 100394. DOI: 10.1016/j.jocm.2022.100394
|
| [15] |
Aizaki H, Fogarty J. An R package and tutorial for case 2 best-worst scaling[J]. J Choice Model, 2019, 32: 100171. DOI: 10.1016/j.jocm.2019.100171
|
| [16] |
IDF Diabetes Atlas 10th Edition Scientific Committee. IDF diabetes atlas: Chapter 1 What is diabetes?[M]. 10th ed. Brussels: International Diabetes Federation, 2021.
|
| [17] |
Shrivastav M, Gibson W, Jr, Shrivastav R, et al. Type 2 diabetes management in primary care: the role of retrospec-tive, professional continuous glucose monitoring[J]. Diabetes Spectr, 2018, 31(3): 279-287. DOI: 10.2337/ds17-0024
|
| [18] |
Yuan B B, Balabanova D, Gao J, et al. Strengthening public health services to achieve universal health coverage in China[J]. BMJ, 2019, 365: l2358.
|
| [19] |
Naik A G, Staab E, Li J, et al. Factors related to recruitment and retention of patients into diabetes group visits in Federally Qualified Health Centers[J]. J Eval Clin Pract, 2023, 29(1): 146-157. DOI: 10.1111/jep.13746
|
| [20] |
Cai Y Y, He H, Chen Z, et al. Shared Medical Appoint-ment for diabetes (SMART) in China: design of an optimization trial[EB/OL]. (2024-03-21)[ 2024-09-01]. https://doi.org/10.21203/rs.3.rs-3987350/v1.
|
| [21] |
刘世蒙, 李顺平, 杨毅, 等. 离散选择实验应用于2型糖尿病患者治疗偏好的文献分析[J]. 中国药房, 2020, 31(20): 2524-2531. DOI: 10.6039/j.issn.1001-0408.2020.20.17
Liu S M, Li S P, Yang Y, et al. Literature analysis of the application of discrete choice experiment in the treatment preferences of patient with type 2 diabetes[J]. China Pharm, 2020, 31(20): 2524-2531. DOI: 10.6039/j.issn.1001-0408.2020.20.17
|
| [22] |
Hollin I L, Paskett J, Schuster A L R, et al. Best-worst scaling and the prioritization of objects in health: a systematic review[J]. Pharmacoeconomics, 2022, 40(9): 883-899. DOI: 10.1007/s40273-022-01167-1
|
| [23] |
关丽征, 金岳, 滕菲, 等. 联合分析法在社区卫生服务选择偏好中的应用[J]. 中国全科医学, 2011, 14(16): 1758-1762. DOI: 10.3969/j.issn.1007-9572.2011.16.004
Guan L Z, Jin Y, Teng F, et al. Application of conjoint analysis in preference of community health services[J]. Chin Gen Pract, 2011, 14(16): 1758-1762. DOI: 10.3969/j.issn.1007-9572.2011.16.004
|
| [24] |
Flynn T N. Valuing citizen and patient preferences in health: recent developments in three types of best-worst scaling[J]. Expert Rev Pharmacoecon Outcomes Res, 2010, 10(3): 259-267. DOI: 10.1586/erp.10.29
|
| [25] |
刘仲琦, 郝春, 顾菁, 等. 离散选择试验中试验设计步骤的实现: 基于SAS宏程序的应用[J]. 中国卫生统计, 2018, 35(6): 949-952.
Liu Z Q, Hao C, Gu J, et al. Implementation of experimental design steps in discrete choice experiments: application based on SAS macro program[J]. Chin J Health Stat, 2018, 35(6): 949-952.
|
| [26] |
Dobischok S, Metcalfe R, Matzinger E, et al. Measuring the preferences of injectable opioid agonist treatment (iOAT) clients: development of a person-centered scale (best-worst scaling)[J]. Int J Drug Policy, 2023, 112: 103948. DOI: 10.1016/j.drugpo.2022.103948
|
| [27] |
Cheung K L, Wijnen B F M, Hollin I L, et al. Using best-worst scaling to investigate preferences in health care[J]. Pharmacoeconomics, 2016, 34(12): 1195-1209. DOI: 10.1007/s40273-016-0429-5
|
| [28] |
Van Bulck L, Wampers M, Moons P. Research electronic data capture (REDCap): tackling data collection, management, storage, and privacy challenges[J]. Eur J Cardiovasc Nurs, 2022, 21(1): 85-91. DOI: 10.1093/eurjcn/zvab104
|
| [29] |
Van Dijk J D, Groothuis-Oudshoorn C G M, Marshall D A, et al. An empirical comparison of discrete choice experiment and best-worst scaling to estimate stakeholders' risk tolerance for hip replacement surgery[J]. Value Health, 2016, 19(4): 316-322. DOI: 10.1016/j.jval.2015.12.020
|
| [30] |
Janse S A, Dumanis S B, Huwig T, et al. Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: a best-worst scaling[J]. Epilepsy Behav, 2019, 96: 183-191. DOI: 10.1016/j.yebeh.2019.04.018
|
| [31] |
罗楠晟. 基于离散选择实验的公共卫生与预防医学专业硕士研究生就业偏好研究[D]. 沈阳: 中国医科大学, 2023: 16-17.
Luo N S. Research on employment preference of postgra-duates majoring in public health and preventive medicine based on discrete choice experiment[D]. Shenyang: China Medical University, 2023: 16-17.
|
| [32] |
Cheung K L, Mayer S, Simon J, et al. Comparison of statistical analysis methods for object case best-worst scaling[J]. J Med Econ, 2019, 22(6): 509-515. DOI: 10.1080/13696998.2018.1553781
|
| [33] |
Mühlbacher A C, Kaczynski A, Zweifel P, et al. Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview[J]. Health Econ Rev, 2016, 6(1): 2. DOI: 10.1186/s13561-015-0079-x
|
| [34] |
Cohen S H. Maximum difference scaling: improved measures of importance and preference for segmentation[R]. Provo, UT: Sawtooth Software Inc., 2003.
|
Supported by: Beijing Renhe Information Technology Co., Ltd. 
Submit
Review
Office
Email Alert
RSS
DownLoad: