NRCMS capitation reform and effect evaluation in Pudong New Area of Shanghai
Bibliographic record
Abstract
The Rural Cooperative Medical Scheme (RCMS) had played an important role in guaranteeing the acquisition of basic medical healthcare of China's rural populations, being an innovative model of the medical insurance system for so many years here in China. Following the boom and bust of RCMS, the central government rebuilt the New Rural Cooperative Medical Scheme (NRCMS) in 2003 across the whole country. Shanghai, one of the developed cities in China, has developed its RCMS and NRCMS as an advanced and exemplary representative of Chinese rural health insurance. But in the past 10 years, its NRCMS has encountered such challenges as a spiral of medical expenditures and a decrease of insurance participants. Previous investigations showed that the capitation and general practitioner (GP) system had great effect on medical cost containment. Thus, the capitation reform combined with GP system reform of NRCMS, based on a system design, was implemented in Pudong New Area of Shanghai as of 1 August 2012. The aim of the current investigation was to present how the reform was designed and implemented, evaluating its effect by analyzing the data acquired from 12 months before and after the reform. This was an empirical study; we made a conceptual design of the reform to be implemented in Pudong New Area. Most data were derived from the institution-based surveys and supplemented by a questionnaire survey, qualitative interviews and policy document analysis. We found that most respondents held an optimistic attitude towards the reform. We employed a structure-process-outcome evaluation index system to evaluate the effect of the reform, finding that the growth rate of the insured population's total medical costs and NRCMS funds slowed down significantly after the reform; that the total medical expenditure of the insured rural population decreased by 3.60%; and that the total expenditure of NRCMS decreased by 3.99%. The capitation was found to help the medical staff build active cost control consciousness. Approximately 2.3% of the outpatients flowed to the primary hospitals from the secondary hospitals; and farmers' annual medical burden was relieved to a certain degree. Meanwhile, it did not affect farmers' utilization and benefits of healthcare. However, further reform still faces new challenges: The capitation reform should be well combined with the primary healthcare system to realize the "dual gatekeeper" of GPs; a variety of payment methods should be mixed on the basis of capitation to avoid possible mistakes by one single approach; and the supervision of medical institutions should be strengthened. A long-term follow-up study need to be carried out to evaluate the effects of the capitation reform so as to improve the design of the program. Copyright © 2015 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".