ReviewFrontiers in surgery2021
Standardization of Procedures to Contain Cost and Reduce Variability of Care After the Pandemic.
Review in Frontiers in surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- The outcomes of Lean management in a large academic hospital in Finland in 2018-2023: a qualitative study.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2026Article
- Short-term clinical outcomes of changing CSF shunt valve type or shunt valve brand in revision surgeries for the management of pediatric hydrocephalus.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2026Article
- The Inflow, Throughput and Outflow of COVID-19 Patients in Dutch Hospitals: Experiences from Experts and Middle Managers.Healthcare (Basel, Switzerland) · 2023Article
- Editorial on research topic: Surgery and COVID-19 in oncologic patients: What does the recent coronavirus pandemic taught us?Frontiers in surgery · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has changed many aspects of our private and professional routine. In particular, the lockdowns have severely affected the entire healthcare system and hospital activities, forcing it to rethink the protocols in force. We suggest that this scenario, in spite of the new challenges involving so far complex healthcare providers, may lead to the unique opportunity to rethink pathways and management of patients. Indeed, having to resume institutional activity after a long interruption that has completely canceled the previously existing schemes, healthcare providers have the unique opportunity to overcome obsolete and "we have always done in this way" model on the wave of the general desire to resume a normal life. Furthermore, the pandemic has highlighted some flaws in our health system, highlighting those critical issues that most need to be addressed. This article is a review of pre-pandemic literature addressing the use of Lean Six Sigma (LSS) and standardization processes in thoracic surgery to improve efficiency. Our goal is to identify the main issues that could be successfully improved along the entire pathway of a patient from the first referral to diagnosis, hospitalization, and surgical operation up to convalescence. Furthermore, we aim to identify the standardization processes that have been implemented to achieve significant improvements in patient outcomes while reducing costs. The methods and goals that could be used in the near future to modernize our healthcare systems are drawn up from a careful reading and interpretation in light of the pandemic of the most significant review articles in the literature.
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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.