Evidence map›Paper›PMID 33868704›Full record

ArticleDigital health

Implementing online patient feedback in a 'special measures' acute hospital: A case study using Normalisation Process Theory.

Rebecca Baines, Frazer Underwood, Kim O'Keeffe, Jessica Saunders, Ray B Jones

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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.

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4 · The record

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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.

Rebecca BainesCentre for Health Technology, University of Plymouth, Plymouth, UK.ORCID https://orcid.org/0000-0001-9857-1976
Frazer UnderwoodSouth West Clinical School in Cornwall, University of Plymouth and Royal Cornwall Hospital NHS Trust.
Kim O'KeeffeSouth West Clinical School in Cornwall, University of Plymouth and Royal Cornwall Hospital NHS Trust.
Jessica SaundersRoyal Cornwall Hospital NHS Trust, Truro, UK.
Ray B JonesCentre for Health Technology, University of Plymouth, Plymouth, UK.ORCID https://orcid.org/0000-0002-2963-3421

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveOnline patient feedback is becoming increasingly prevalent on an international scale. However, limited research has explored how healthcare organisations implement such feedback. This research sought to explore how an acute hospital, recently placed into 'special measures' by a regulatory body implemented online feedback to support its improvement journey.

methodsSemi-structured interviews were conducted with eleven key stakeholders involved in the implementation and/or use of online patient feedback. Data was analysed using deductive thematic analysis with Normalisation Process Theory used as the analytical framework. Research findings are translated into the Engage, Support and Promote (ESP) model, a model of rapid feedback adoption.

resultsParticipants viewed the implementation of online feedback as an opportunity to learn, change and improve. Factors found to facilitate implementation were often linked to engagement, support and promotion. Although less frequently described, barriers to implementation included staff anxieties about time pressures, moderation processes and responding responsibilities. Such anxieties were often addressed by activities including the provision of evidence based responder training. Overall, staff were overwhelmingly positive about the value of online feedback with 24 impacts identified at an individual and organisational level, including the ability to boost staff morale, resilience and pride.

conclusionsThe rapid implementation of online patient feedback can be achieved in a 'special measures' organisation. However, the difficulties of implementing such feedback should not be underestimated. In order to embed online feedback, staff members need to be engaged and feel supported, with opportunities to provide, respond and invite patient feedback frequently promoted to both patients and staff members.

Indexed as

care opinionnormalisation process theoryonline patient feedbackpatient experiencePatient feedbackqualitative studies

Identifiers

PMID33868704
PMCPMC8020246

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LicenceCC BY-NC-ND
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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.