Evidence map›Paper›PMID 34980606›Full record

ArticleBMJ open2022

Which human factors design issues are influencing system performance in out-of-hours community palliative care? Integration of realist approaches with an established systems analysis framework to develop mid-range programme theory.

Sarah Yardley, Huw Williams, Paul Bowie, Adrian Edwards, Simon Noble, Liam Donaldson, Andrew Carson-Stevens

Abstract read
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Learning from end-of-life injectable medication patient safety incidents in the community: a mixed-methods analysis.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  3. Article
  4. Article
  5. A mixed-methods characterisation of patient safety incidents by primary eye care practitioners.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2022
    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

7 authors.

Sarah YardleyMarie Curie Palliative Care Research Department, University College London, London, UK.ORCID 0000-0002-1645-642X
Huw WilliamsDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, UK.
Paul BowieMedical Directorate, NHS Education for Scotland, Edinburgh, UK.
Adrian EdwardsDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, UK.ORCID 0000-0002-6228-4446
Simon NobleMarie Curie Palliative Care Research Centre, Division of Population Medicine, School of Medicine, Cardiff University, Cardiff, UK.
Liam DonaldsonFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Andrew Carson-StevensDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, UK carson-stevensap@cardiff.ac.uk.

Funding

Marie Curie MCCC-FCO-11-CMarie Curie MCCC-FCO-11-U
6 · The paper itself

Abstract

objectiveTo develop mid-range programme theory from perceptions and experiences of out-of-hours community palliative care, accounting for human factors design issues that might be influencing system performance for achieving desirable outcomes through quality improvement.

settingCommunity providers and users of out-of-hours palliative care.

participants17 stakeholders participated in a workshop event.

designIn the UK, around 30% of people receiving palliative care have contact with out-of-hours services. Interactions between emotions, cognition, tasks, technology and behaviours must be considered to improve safety. After sharing experiences, participants were presented with analyses of 1072 National Reporting and Learning System incident reports. Discussion was orientated to consider priorities for change. Discussions were audio-recorded and transcribed verbatim by the study team. Event artefacts, for example, sticky notes, flip chart lists and participant notes, were retained for analysis. Two researchers independently identified context-mechanism-outcome configurations using realist approaches before studying the inter-relation of configurations to build a mid-range theory. This was critically appraised using an established human factors framework called Systems Engineering Initiative for Patient Safety (SEIPS).

resultsComplex interacting configurations explain relational human-mediated outcomes where cycles of thought and behaviour are refined and replicated according to prior experiences. Five such configurations were identified: (1) prioritisation; (2) emotional labour; (3) complicated/complex systems; (4a) system inadequacies and (4b) differential attention and weighing of risks by organisations; (5) learning. Underpinning all these configurations was a sixth: (6a) trust and access to expertise; and (6b) isolation at night. By developing a mid-range programme theory, we have created a framework with international relevance for guiding quality improvement work in similar modern health systems.

conclusionsMeta-cognition, emotional intelligence, and informal learning will either overcome system limitations or overwhelm system safeguards. Integration of human-centred co-design principles and informal learning theory into quality improvement may improve results.

Indexed as

After-Hours CareHospice and Palliative Care NursingHumansPalliative CareQuality ImprovementSystems Analysisadult palliative careorganisation of health servicesprimary care

Identifiers

PMID34980606
PMCPMC8724735

What OpenQuestion holds

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LicenceCC BY-NC
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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.