Evidence map›Paper›PMID 35516829›Full record

ArticleBMJ simulation & technology enhanced learning2021

Failure modes and effects analysis to assess COVID-19 protocols in the management of obstetric emergencies.

Sam Curtis, Rebecca Flower, Lola Emanuel-Kole, Premala Nadarajah

Abstract read
In one paragraph

Article in BMJ simulation & technology enhanced learning, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sam CurtisDepartment of Anaesthesia, Royal Free Hospital, London, UK.ORCID 0000-0002-5390-9600
Rebecca FlowerDepartment of Anaesthesia, Royal Free Hospital, London, UK.
Lola Emanuel-KoleDepartment of Anaesthesia, Royal Free Hospital, London, UK.
Premala NadarajahDepartment of Anaesthesia, Royal Free Hospital, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Royal Free Hospital is one of four High Consequence Infectious Disease centres in England and as of the end of May 2020, seven women were confirmed COVID-19 peri-delivery. We developed a standard operating procedure (SOP) for suspected and confirmed COVID-19 women undergoing operative delivery. This was revised in response to our ongoing clinical experience and changes in guidance from medical and public health organisations. Following 10 weeks of clinical practice, we formally tested the SOP using point-of-care simulation to enable optimisation for a potential second surge. Our high-fidelity simulation of a COVID-19-positive parturient requiring an emergency caesarean was facilitated by the simulation team in our obstetric unit. It was designed to test the performance and safety of our SOP as well as staff performance. We used the Failure Modes and Effect Analysis tool (a systematic, prospective method of process mapping) to identify how a complex task might fail and assess the relative impact of different failures. The decision-to-delivery was 17 minutes, which we considered to be successful. However, a number of operational deficiencies were identified. The main failures related to lack of situational awareness, ill-fitting personal protective equipment and difficulties communicating between theatre and the neonatal teams located outside, posing serious potential risks to safe neonatal care. Subsequently, we have modified our SOP to include a communication check, implemented communication training for the neonatal team and organised further simulation training for theatre staff unfamiliar with COVID-19 considerations.

Indexed as

anaesthesiaobstetricspatient safetysimulation

Identifiers

PMID35516829
PMCPMC8936552

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.