ArticleBMJ open quality2019
Using Always Events to derive patient-centred quality improvement priorities in a specialist primary care service providing care to a homeless population.
Article in BMJ open quality, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- A scoping review examining patient experience and what matters to people experiencing homelessness when seeking healthcare.BMC health services research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 'Always Events' (AE) is a validated quality improvement (QI) method where patients, and/or carers, are asked what is so important that it should 'always' happen when they interact with healthcare services. Answers that meet defined criteria can be used to direct patient-centred QI activities. This method has never, to our knowledge, been applied in the care of a UK homeless population. We aimed to test the aspects of the acceptability and feasibility of the AE method to inform on its potential application to improve care for this vulnerable group of patients. Methods: All patients attending three consecutive drop-in clinics at a specialist homeless general practitioner service in Glasgow, who agreed to participate, were interviewed. Anonymised responses were transcribed and coded and a thematic analysis performed. Themes were summarised to generate candidate AE using the patient's own words. The authors then determined if they met the AE criteria. Results: Twenty out of 22 eligible patients were interviewed. Oral transcribing was found to be an acceptable way to gather data in this group. Nine candidate AEs were generated, of which five fitted the criteria to be used as metrics for future QI projects. This project generated AEs and QI targets, and highlighted issues of importance to patients that could be easily addressed. Conclusion: In the homeless context, obtaining high engagement and useful patient feedback, in a convenient way, is difficult. The AE method is an acceptable and feasible tool for generating QI targets that can lead to improvements in care for this vulnerable group.
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