Attribute development and level selection for a discrete choice experiment to elicit the preferences of health care providers for capitation payment mechanism in Kenya

Melvin Obadha (), Edwine Barasa (), Jacob Kazungu (), Gilbert Abotisem Abiiro () and Jane Chuma ()
Additional contact information
Melvin Obadha: Health Economics Research Unit, KEMRI | Wellcome Trust Research Programme
Edwine Barasa: Health Economics Research Unit, KEMRI | Wellcome Trust Research Programme
Jacob Kazungu: Health Economics Research Unit, KEMRI | Wellcome Trust Research Programme
Gilbert Abotisem Abiiro: University for Development Studies
Jane Chuma: Health Economics Research Unit, KEMRI | Wellcome Trust Research Programme

Health Economics Review, 2019, vol. 9, issue 1, 1-19

Abstract: Abstract Background Stated preference elicitation methods such as discrete choice experiments (DCEs) are now widely used in the health domain. However, the “quality” of health-related DCEs has come under criticism due to the lack of rigour in conducting and reporting some aspects of the design process such as attribute and level development. Superficially selecting attributes and levels and vaguely reporting the process might result in misspecification of attributes which may, in turn, bias the study and misinform policy. To address these concerns, we meticulously conducted and report our systematic attribute development and level selection process for a DCE to elicit the preferences of health care providers for the attributes of a capitation payment mechanism in Kenya. Methodology We used a four-stage process proposed by Helter and Boehler to conduct and report the attribute development and level selection process. The process entailed raw data collection, data reduction, removing inappropriate attributes, and wording of attributes. Raw data was collected through a literature review and a qualitative study. Data was reduced to a long list of attributes which were then screened for appropriateness by a panel of experts. The resulting attributes and levels were worded and pretested in a pilot study. Revisions were made and a final list of attributes and levels decided. Results The literature review unearthed seven attributes of provider payment mechanisms while the qualitative study uncovered 10 capitation attributes. Then, inappropriate attributes were removed using criteria such as salience, correlation, plausibility, and capability of being traded. The resulting five attributes were worded appropriately and pretested in a pilot study with 31 respondents. The pilot study results were used to make revisions. Finally, four attributes were established for the DCE, namely, payment schedule, timeliness of payments, capitation rate per individual per year, and services to be paid by the capitation rate. Conclusion By rigorously conducting and reporting the process of attribute development and level selection of our DCE,we improved transparency and helped researchers judge the quality.

Keywords: Attribute development; Capitation; Discrete choice experiment; Kenya; Provider payment mechanisms; Sub-Saharan Africa (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1186/s13561-019-0247-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:hecrev:v:9:y:2019:i:1:d:10.1186_s13561-019-0247-5

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13561

DOI: 10.1186/s13561-019-0247-5

Access Statistics for this article

Health Economics Review is currently edited by J. Matthias Graf von der Schulenburg

More articles in Health Economics Review from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().