Preferences of healthcare providers for capitation payment in Kenya: a discrete choice experiment

• DOI: 10.1093/heapol/czaa016
• Publication Date: 2020-02-25T20:14:49Z
• Authors: Melvin Obadha; Jane Chuma; Jacob Kazungu; Gilbert Abotisem ...; Matthew J Beck; Edwine Barasa
• Keywords: Economics and Econometrics; Economics; Health Personnel; Actuarial science; Discrete Choice Models in Economics and Health Care; Social Sciences; health personnel; 03 medical and health sciences; Preference Elicitation; Capitation; 0302 clinical medicine; Universal Health Insurance; Health Sciences; Microeconomics; Humans; Business; Capitation fee; Payment; health services; provider payment mechanism; Economic growth; Global Maternal and Child Health Outcomes; Prospective Payment System; discrete choice experiment; Health care; 1. No poverty; Bayes Theorem; Original Articles; Kenya; 3. Good health; Economics, Econometrics and Finance; kenya; physician payment; Stated Preference Methods; Financing of Health Care Systems and Universal Coverage; Pediatrics, Perinatology and Child Health; strategic purchasing; Medicine; Health Facilities; capitation payment system; Incentive; Finance

AbstractProvider payment mechanisms (PPMs) are important to the universal health coverage (UHC) agenda as they can influence healthcare provider behaviour and create incentives for health service delivery, quality and efficiency. Therefore, when designing PPMs, it is important to consider providers’ preferences for PPM characteristics. We set out to uncover senior health facility managers’ preferences for the attributes of a capitation payment mechanism in Kenya. We use a discrete choice experiment and focus on four capitation attributes, namely, payment schedule, timeliness of payments, capitation rate per individual per year and services to be paid by the capitation rate. Using a Bayesian efficient experimental design, choice data were collected from 233 senior health facility managers across 98 health facilities in seven Kenyan counties. Panel mixed multinomial logit and latent class models were used in the analysis. We found that capitation arrangements with frequent payment schedules, timelier disbursements, higher payment rates per individual per year and those that paid for a limited set of health services were preferred. The capitation rate per individual per year was the most important attribute. Respondents were willing to accept an increase in the capitation rate to compensate for bundling a broader set of health services under the capitation payment. In addition, we found preference heterogeneity across respondents and latent classes. In conclusion, these attributes can be used as potential targets for interventions aimed at configuring capitation to achieve UHC.