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Scaling-up through piloting: dual-track provider payment reforms in China’s health system

Gaining wide prominence in the global health arena, scaling-up increases the coverage of health innovations emerging from pilots and experimental projects to a larger scale. However, scaling-up in the health sector should not follow a linear ‘pilot-diffusion’ pathway in order to better facilitate lo...

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Detalles Bibliográficos
Autor principal: He, Alex Jingwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923375/
https://www.ncbi.nlm.nih.gov/pubmed/36103333
http://dx.doi.org/10.1093/heapol/czac080
Descripción
Sumario:Gaining wide prominence in the global health arena, scaling-up increases the coverage of health innovations emerging from pilots and experimental projects to a larger scale. However, scaling-up in the health sector should not follow a linear ‘pilot-diffusion’ pathway in order to better facilitate local adaptation and policy refinement. This paper puts forth ‘scaling-up through piloting’ as a distinctive pathway for the strategic management of scaling-up in the health sector. It analyses the recent development of provider payment reforms in China, focusing particularly on the ongoing pilot programmes, namely diagnosis-related groups (DRGs) and diagnosis-intervention packet (DIP), that are being piloted in a dual-track fashion since 2020. Data were drawn from extensive documentary analysis and 20 in-depth interviews with key stakeholders, including decision-makers and implementers. This paper finds that scaling-up through piloting helps Chinese policymakers minimize the vast uncertainties associated with complex payment reforms and maximize the local adaptability of provider payment innovations. This pathway has forged a phased implementation process, allowing new payment models to be tested, evaluated, compared and adjusted in a full spectrum of local contexts before national rollout. The phased implementation creates a ‘slower is faster’ effect, helping reduce long-term negative consequences arising from improperly managed scaling-up in a complex system. Error detection and correction and recalibration of new policy tools can support national-level policy refinement in a more robust and dynamic fashion. Several key factors have been identified as crucial for strategic scaling-up: necessary central steering, a pragmatic piloting design, strong technical capacity and effective policy learning mechanisms