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Related Experiment Video

Updated: Jun 29, 2026

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Understanding provider behavioral responses to capitation prepayment systems: an integrated mixed-methods approach.

Tao Zhang¹, Boyu Li¹, Jing Liu²

¹Department of Health Policy and Management, School of Public Administration, Hangzhou Normal University, Hangzhou, China.

Cost Effectiveness and Resource Allocation : C/E

|June 27, 2026

Summary

Provider responses to capitation prepayment in China are driven by cost-control measures, influenced by external factors and resources. Policy must address unintended consequences like service shifting for effective healthcare reform.

Keywords:

Capitation prepayment China Healthcare provider behavior Incentive mechanism Mixed methods Provider payment model

Related Experiment Videos

Last Updated: Jun 29, 2026

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Area of Science:

Health Services Research
Health Economics
Public Health Policy

Background:

Provider payment mechanisms significantly shape healthcare delivery.
China's Integrated County Healthcare Consortium (ICHC) system utilizes capitation prepayment.
Understanding provider behavior under these reforms is crucial for system effectiveness.

Purpose of the Study:

To examine capitation prepayment implementation within China's ICHC system.
To elucidate factors influencing provider behavioral responses.
To analyze the resulting healthcare system dynamics.

Main Methods:

Mixed-methods study in Datong prefecture, China.
Qualitative analysis (LDA) of 63 interviews.
Social Network Analysis (SNA), Interpretative Structural Modeling (ISM), and System Dynamics Model (SDM) with 2015-2019 hospital data.

Main Results:

Provider behavior influenced by external environment, institutional resources, and management strategies (cost control).
Management strategies directly determined behavior; environmental and resource factors moderated payment incentives.
Simulations revealed potential cost-shifting from inpatient to outpatient services.

Conclusions:

Provider responses to capitation are primarily driven by institutional cost-control measures.
Contextual and resource factors mediate these responses.
Policy should mitigate unintended consequences like service shifting via referral and monitoring improvements.