ArticleJMIR medical informatics2022
The Application of Graph Theoretical Analysis to Complex Networks in Medical Malpractice in China: Qualitative Study.
Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Eager for an innovative path: solving the puzzle of medical dispute resolution in China combined with bibliometric analysis.Frontiers in health services · 2024Article
- A machine learning-based predictive model of causality in orthopaedic medical malpractice cases in China.PloS one · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStudies have shown that hospitals or physicians with multiple malpractice claims are more likely to be involved in new claims. This finding indicates that medical malpractice may be clustered by institutions.
objectiveWe aimed to identify the underlying mechanisms of medical malpractice that, in the long term, may contribute to developing interventions to reduce future claims and patient harm.
methodsThis study extracted the semantic network in 6610 medical litigation records (unstructured data) obtained from a public judicial database in China. They represented the most serious cases of malpractice in the country. The medical malpractice network of China was presented as a knowledge graph based on the complex network theory; it uses the International Classification of Patient Safety from the World Health Organization as a reference.
resultsWe found that the medical malpractice network of China was a scale-free network-the occurrence of medical malpractice in litigation cases was not random, but traceable. The results of the hub nodes revealed that orthopedics, obstetrics and gynecology, and the emergency department were the 3 most frequent specialties that incurred malpractice; inadequate informed consent work constituted the most errors. Nontechnical errors (eg, inadequate informed consent) showed a higher centrality than technical errors.
conclusionsHospitals and medical boards could apply our approach to detect hub nodes that are likely to benefit from interventions; doing so could effectively control medical risks.
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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.