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For improving the current pricing mode of medical services, the present study seeks to explore the pricing elements and processes, and establish the dynamic pricing model of involving both the government and hospitals. The pricing process and mathematical model show the logical relationships between medical prices and pricing elements. The causal relationship model reveals how to accomplish dynamic equilibrium between elements. The simulation model has been built based on system dynamics theory. Results of the simulation and sensitivity tests show that different grades of hospitals while applying the pricing model may better perform their respective responsibilities and continuously improve core strengths. [ABSTRACT FROM AUTHOR]

Background: The literature comparing private not-for-profit, for-profit, and government providers mostly relies on empirical evidence from high-income and established market economies. Studies from developing and transitional economies remain scarce, especially regarding patient case-mix and quality of care in public and private hospitals, even though countries such as China have expanded a mixed-ownership approach to service delivery. The purpose of this study is to compare the operations and performance of public and private hospitals in Guangdong Province, China, focusing on differences in patient case-mix and quality of care. Methods: We analyze survey data collected from 362 government-owned and private hospitals in Guangdong Province in 2005, combining mandatorily reported administrative data with a survey instrument designed for this study. We use univariate and multi-variate regression analyses to compare hospital characteristics and to identify factors associated with simple measures of structural quality and patient outcomes. Results: Compared to private hospitals, government hospitals have a higher average value of total assets, more pieces of expensive medical equipment, more employees, and more physicians (controlling for hospital beds, urban location, insurance network, and university affiliation). Government and for-profit private hospitals do not statistically differ in total staffing, although for-profits have proportionally more support staff and fewer medical professionals. Mortality rates for non-government non-profit and for-profit hospitals do not statistically differ from those of government hospitals of similar size, accreditation level, and patient mix. Conclusions: In combination with other evidence on health service delivery in China, our results suggest that changes in ownership type alone are unlikely to dramatically improve or harm overall quality. System incentives need to be designed to reward desired hospital performance and protect vulnerable patients, regardless of hospital ownership type. [ABSTRACT FROM AUTHOR]

The reluctance or incapability of further increasing production resources has made many enterprises suffering from high resource-workload situation. Production dynamics thus cannot be resolved by single resource independently, yet have to make an integral use of the adjustable capability of multiple resources of the whole system in a synchronized way. This paper considers a dynamic production logistics (PL) process comprising multiple independently operated PL stages, which adopts Internet of Things to capture real-time execution dynamics and rely on plan (re)scheduling and cloud-based resources re-configuration to cope with dynamics. A generic dynamic production logistics synchronization (PLS) solution is proposed. Qualitatively, a multi-phase multi-stage multi-degree synchronization control mechanism is put forward toward a PL system with generic structure and typical execution dynamics. Quantitatively, collaborative optimization is applied to assist the PLS to obtain the synchronization results. With a real-life case study, the effectiveness of the proposed mechanism and method has been verified. A set of sensitivity analysis is also conducted toward dynamics of different degree and different time, which provides significant managerial implication to PL managers to better deal with dynamics. [ABSTRACT FROM AUTHOR]