ArticleInternational journal of environmental research and public health2013
Performance evaluation of public non-profit hospitals using a BP artificial neural network: the case of Hubei Province in China.
Article in International journal of environmental research and public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting.BMC medical informatics and decision making · 2015Pooled it
- Study on regional disparities and influencing factors of public health service supply in China from the perspective of fairness.BMC health services research · 2025Article
- Efficiency divergence and convergence in China's hospital sector: empirical insights from Guangdong Province using a multi-method approach.Frontiers in public health · 2025Article
- Hospital performance evaluation models: A scoping review.Journal of education and health promotion · 2025Review
- Impact of provincial economic development levels on public-private hospital co-development in China: an empirical analysis.BMJ open · 2024Article
- Hospital performance evaluation indicators: a scoping review.BMC health services research · 2024Article
- Satisfaction with Public Hospital Reform and Associated Factors Among Medical Staff: A Cross-Sectional Survey in Wuhan, China.Risk management and healthcare policy · 2021Article
- Assessment of performance in teaching hospitals: Using multicriteria decision-making techniques.Journal of education and health promotion · 2020Article
- Neural Classification of Compost Maturity by Means of theInternational journal of environmental research and public health · 2019Article
- Balanced scorecard-based performance evaluation of Chinese county hospitals in underdeveloped areas.The Journal of international medical research · 2018Article
- What do patients care most about in China's public hospitals? Interviews with patients in Jiangsu Province.BMC health services research · 2018Article
- Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network.International journal of environmental research and public health · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To provide a reference for evaluating public non-profit hospitals in the new environment of medical reform, we established a performance evaluation system for public non-profit hospitals. The new "input-output" performance model for public non-profit hospitals is based on four primary indexes (input, process, output and effect) that include 11 sub-indexes and 41 items. The indicator weights were determined using the analytic hierarchy process (AHP) and entropy weight method. The BP neural network was applied to evaluate the performance of 14 level-3 public non-profit hospitals located in Hubei Province. The most stable BP neural network was produced by comparing different numbers of neurons in the hidden layer and using the "Leave-one-out" Cross Validation method. The performance evaluation system we established for public non-profit hospitals could reflect the basic goal of the new medical health system reform in China. Compared with PLSR, the result indicated that the BP neural network could be used effectively for evaluating the performance public non-profit hospitals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.