ArticleThe International journal of health planning and management2021
The 'hub and spoke model' for the management of surgical patients during the COVID-19 pandemic.
Article in The International journal of health planning and management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Strategies to strengthen elective surgery systems during the SARS-CoV-2 pandemic: systematic review and framework development.The British journal of surgery · 2024Pooled it
- Enhanced recovery after surgery (ERAS) guided gynecologic/oncology surgery - The patient's perspective.Gynecologic oncology reports · 2024Article
- Centralization of Major Trauma Influences Liver Availability for Transplantation in Northern Italy: Lesson Learned from COVID-19 Pandemic.Journal of clinical medicine · 2022Article
- The 'hub and spoke model' for the management of surgical patients during the COVID-19 pandemic.The International journal of health planning and management · 2021Article
- The impact of delaying surgery during the COVID-19 pandemic in Alberta: a qualitative study.CMAJ openArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
During the on-going COVID-19 pandemic a number of key public health services have been severely impacted. These include elective surgical services due to the synergetic resources required to provide both perioperative surgical care whilst also treating acute COVID-19 patients and also the poor outcomes associated with surgical patients who develop COVID-19 in the perioperative period. This article discusses the important principles and concepts for providing important surgical services during the COVID-19 pandemic based on the model of the RMCancerSurgHub which is providing surgical cancer services for a population of approximately 2 million people across London during the pandemic. The model focusses on creating local and regional hub centres which provide urgent treatment for surgical patients in an environment that is relatively protected from the burden of COVID-19 illness. The model extensively utilises the extended multidisciplinary team to allow for a flexible approach with core services delivered in 'clean' sites which can adapt to viral surges. A key requirement is that of a clinical prioritisation process which allows for equity in access within and between specialties ensuring that patients are treated on the basis of greatest need, while at the same time protecting those whose conditions can safely wait from exposure to the virus. Importantly, this model has the ability to scale-up activity and lead units and networks into the recovery phase. The model discussed is also broadly applicable to providing surgical services during any viral pandemic.
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.