ArticleBMJ open2020
Can network science reveal structure in a complex healthcare system? A network analysis using data from emergency surgical services.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- The impact of atypical intrahospital transfers on patient outcomes: a mixed methods study.Scientific reports · 2023Article
- Social network analysis of nationwide interhospital emergency department transfers in Taiwan.Scientific reports · 2023Article
- Modular structures and the delivery of inpatient care in hospitals: a Network Science perspective on healthcare function and dysfunction.BMC health services research · 2022Article
- Machine learning for real-time aggregated prediction of hospital admission for emergency patients.NPJ digital medicine · 2022Article
- Using network analysis to model the effects of the SARS Cov2 pandemic on acute patient care within a healthcare system.Scientific reports · 2022Article
- Article
- Observational
- Making sense of the French public hospital system: a network-based approach to hospital clustering using unsupervised learning methods.BMC health services research · 2021Article
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
introductionHospitals are complex systems and optimising their function is critical to the provision of high quality, cost effective healthcare. Metrics of performance have to date focused on the performance of individual elements rather than the whole system. Manipulation of individual elements of a complex system without an integrative understanding of its function is undesirable and may lead to counterintuitive outcomes and a holistic metric of hospital function might help design more efficient services.
objectivesWe aimed to use network analysis to characterise the structure of the system of perioperative care for emergency surgical admissions in our tertiary care hospital.
designWe constructed a weighted directional network representation of the emergency surgical services using patient location data from electronic health records.
settingA single-centre tertiary care hospital in the UK.
participantsWe selected data from the retrospective electronic health record data of all unplanned admissions with a surgical intervention during their stay during a 3.5-year period, which resulted in a set of 16 500 individual admissions.
methodsWe then constructed and analysed the structure of this network using established methods from network science such as degree distribution, betweenness centrality and small-world characteristics.
resultsThe analysis showed the service to be a complex system with scale-free, small-world network properties. We also identified such potential hubs and bottlenecks in the system.
conclusionsOur holistic, system-wide description of a hospital service may provide tools to inform service improvement initiatives and gives us insights into the architecture of a complex system of care. The implications for the structure and resilience of the service is that while being robust in general, the system may be vulnerable to outages at specific key nodes.
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.