Primary care providers' preferences for pay-for-performance programs: a discrete choice experiment study in Shandong China.

Background: Pay-for-performance (P4P) schemes are commonly used to incentivize primary healthcare (PHC) providers to improve the quality of care they deliver. However, the effectiveness of P4P schemes can vary depending on their design. In this study, we aimed to investigate the preferences of PHC providers for participating in P4P programs in a city in Shandong province, China.

Method: We conducted a discrete choice experiment (DCE) with 882 PHC providers, using six attributes: type of incentive, whom to incentivize, frequency of incentive, size of incentive, the domain of performance measurement, and release of performance results. Mixed logit models and latent class models were used for the statistical analyses.

Results: Our results showed that PHC providers had a strong negative preference for fines compared to bonuses (- 1.91; 95%CI - 2.13 to - 1.69) and for annual incentive payments compared to monthly (- 1.37; 95%CI - 1.59 to - 1.14). Providers also showed negative preferences for incentive size of 60% of monthly income, group incentives, and non-release of performance results. On the other hand, an incentive size of 20% of monthly income and including quality of care in performance measures were preferred. We identified four distinct classes of providers with different preferences for P4P schemes. Class 2 and Class 3 valued most of the attributes differently, while Class 1 and Class 4 had a relatively small influence from most attributes.

Conclusion: P4P schemes that offer bonuses rather than fines, monthly rather than annual payments, incentive size of 20% of monthly income, paid to individuals, including quality of care in performance measures, and release of performance results are likely to be more effective in improving PHC performance. Our findings also highlight the importance of considering preference heterogeneity when designing P4P schemes.