Evidence map›Paper›PMID 37838681›Full record

ArticleBMC medical research methodology2023

Analysis of applying a patient safety taxonomy to patient and clinician-reported incident reports during the COVID-19 pandemic: a mixed methods study.

Thomas Purchase, Alison Cooper, Delyth Price, Emma Dorgeat, Huw Williams, Paul Bowie, Jean-Pascal Fournier, Peter Hibbert, Adrian Edwards, Rhiannon Phillips and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 20% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Critical illness in prisons: a multi-methods analysis of reported healthcare safety incidents in England.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  3. Parental involvement in paediatric patient safety incidents in general practice: a cross-sectional study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
    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

12 authors at 5 institutions in 3 countries.

Thomas PurchaseDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Alison CooperDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Delyth PriceDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Emma DorgeatDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Huw WilliamsWestway Surgery, Ely, Cardiff, UK.
Paul BowieMedical Directorate, NHS Education for Scotland, Glasgow, UK.
Jean-Pascal FournierDépartement de Médecine Générale, Faculté de Médecine, Nantes Université, Nantes, France.
Peter HibbertAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Adrian EdwardsDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Rhiannon PhillipsCardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, UK.
Natalie Joseph-WilliamsDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK.
Andrew Carson-StevensDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, CF14, UK. carson-stevensap@cardiff.ac.uk.
Cardiff University · GBCardiff Metropolitan University · GBMacquarie University · AUNantes Université · FRUniversity of Staffordshire · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic resulted in major disruption to healthcare delivery worldwide causing medical services to adapt their standard practices. Learning how these adaptations result in unintended patient harm is essential to mitigate against future incidents. Incident reporting and learning system data can be used to identify areas to improve patient safety. A classification system is required to make sense of such data to identify learning and priorities for further in-depth investigation. The Patient Safety (PISA) classification system was created for this purpose, but it is not known if classification systems are sufficient to capture novel safety concepts arising from crises like the pandemic. We aimed to review the application of the PISA classification system during the COVID-19 pandemic to appraise whether modifications were required to maintain its meaningful use for the pandemic context.

methodsWe conducted a mixed-methods study integrating two phases in an exploratory, sequential design. This included a comparative secondary analysis of patient safety incident reports from two studies conducted during the first wave of the pandemic, where we coded patient-reported incidents from the UK and clinician-reported incidents from France. The findings were presented to a focus group of experts in classification systems and patient safety, and a thematic analysis was conducted on the resultant transcript.

resultsWe identified five key themes derived from the data analysis and expert group discussion. These included capitalising on the unique perspective of safety concerns from different groups, that existing frameworks do identify priority areas to investigate further, the objectives of a study shape the data interpretation, the pandemic spotlighted long-standing patient concerns, and the time period in which data are collected offers valuable context to aid explanation. The group consensus was that no COVID-19-specific codes were warranted, and the PISA classification system was fit for purpose.

conclusionsWe have scrutinised the meaningful use of the PISA classification system's application during a period of systemic healthcare constraint, the COVID-19 pandemic. Despite these constraints, we found the framework can be successfully applied to incident reports to enable deductive analysis, identify areas for further enquiry and thus support organisational learning. No new or amended codes were warranted. Organisations and investigators can use our findings when reviewing their own classification systems.

Indexed as

COVID-19Patient SafetyHumansMedical ErrorsPandemicsRisk ManagementClassificationCOVID-19Incident reportingPatient safetyPISASystems learningTaxonomy

Identifiers

PMID37838681
PMCPMC10576389
OpenAlexW4387640217

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.