Evidence map›Paper›PMID 27406641›Full record

ArticleBMJ open2016

Healthcare professional and patient codesign and validation of a mechanism for service users to feedback patient safety experiences following a care transfer: a qualitative study.

Jason Scott, Emily Heavey, Justin Waring, Diana Jones, Pamela Dawson

Abstract readValidation Study
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Assessing and promoting partnership between patients and health-care professionals: Co-construction of the CADICEE tool for patients and their relatives.Health expectations : an international journal of public participation in health care and health policy · 2021
    Article
  7. Article
  8. A governance model for the application of AI in health care.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  9. Article
  10. Article
  11. PReSaFe: A model of barriers and facilitators to patients providing feedback on experiences of safety.Health expectations : an international journal of public participation in health care and health policy · 2017
    Article
  12. Parents' Perspectives on Navigating the Work of Speaking Up in the NICU.Journal of obstetric, gynecologic, and neonatal nursing : JOGNN
    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

5 authors.

Jason ScottInstitute of Health and Society, Newcastle University, Newcastle upon Tyne, UK.
Emily HeaveySocial Policy Research Unit, York University, York, UK.
Justin WaringCentre for Health Innovation, Leadership and Learning, Nottingham University, Nottingham, UK.
Diana JonesFaculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK.
Pamela DawsonFaculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and validate a mechanism for patients to provide feedback on safety experiences following a care transfer between organisations.

designQualitative study using participatory methods (codesign workshops) and cognitive interviews. Workshop data were analysed concurrently with participants, and cognitive interviews were thematically analysed using a deductive approach based on the developed feedback mechanism.

participantsExpert patients (n=5) and healthcare professionals (n=11) were recruited purposively to develop the feedback mechanism in 2 workshops. Workshop 1 explored principles underpinning safety feedback mechanisms, and workshop 2 included the practical development of the feedback mechanism. Final design and content of the feedback mechanism (a safety survey) were verified by workshop participants, and cognitive interviews (n=28) were conducted with patients.

resultsWorkshop participants identified that safety feedback mechanisms should be patient-centred, short and concise with clear signposting on how to complete, with an option to be anonymous and balanced between positive (safe) and negative (unsafe) experiences. The agreed feedback mechanism consisted of a survey split across 3 stages of the care transfer: departure, journey and arrival. Care across organisational boundaries was recognised as being complex, with healthcare professionals acknowledging the difficulty implementing changes that impact other organisations. Cognitive interview participants agreed the content of the survey was relevant but identified barriers to completion relating to the survey formatting and understanding of a care transfer.

conclusionsParticipatory, codesign principles helped overcome differences in understandings of safety in the complex setting of care transfers when developing a safety survey. Practical barriers to the survey's usability and acceptability to patients were identified, resulting in a modified survey design. Further research is required to determine the usability and acceptability of the survey to patients and healthcare professionals, as well as identifying how governance structures should accommodate patient feedback when relating to multiple health or social care providers.

Indexed as

FeedbackPatient SafetyPatient SatisfactionPatient TransferSurveys and QuestionnairesTransportationTransportation of PatientsAgedAged, 80 and overAttitudeAttitude of Health PersonnelFemaleHealth PersonnelHumansMaleMiddle AgedPatient experiencePatient safetyQUALITATIVE RESEARCH

Identifiers

PMID27406641
PMCPMC4947796

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.