Evidence map›Paper›PMID 32030194›Full record

ArticleDigital health

Anonymity, veracity and power in online patient feedback: A quantitative and qualitative analysis of staff responses to patient comments on the 'Care Opinion' platform in Scotland.

Louise Locock, Zoë Skea, Gina Alexander, Caroline Hiscox, Lynn Laidlaw, Jenna Shepherd

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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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

The trial behind it

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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

8 citing papers in PubMed.

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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

6 authors.

Louise LocockHealth Services Research Unit, University of Aberdeen, UK.
Zoë SkeaHealth Services Research Unit, University of Aberdeen, UK.ORCID https://orcid.org/0000-0003-4685-4266
Gina AlexanderCare Opinion Scotland, Stirling, UK.
Caroline HiscoxNHS Grampian, Aberdeen, UK.
Lynn LaidlawPatient partner, UK.
Jenna ShepherdUniversity of Aberdeen, UK.

Funding

Chief Scientist Office HSRU2Department of Health 14/156/06
6 · The paper itself

Abstract

objectiveTo analyse how staff in one Scottish hospital respond to anonymised patient feedback posted on the nationally endorsed feedback platform Care Opinion; and to understand staff experiences of, and attitudes towards, engaging with Care Opinion data.

methodsThis was a multi-method study comprising: (a) numerical and thematic analysis of stories posted during a six-month period, using a published framework; (b) thematic analysis of interviews with a range of 10 hospital staff responsible for organisational responses to feedback.

resultsSeventy-seven stories were published during the six-month period. All received a response, with a mean response time of 3.9 days. Ninety-six responses were made in total, from 20 staff members. Personalisation and tailoring was mostly assessed as performing well against the published framework. Only two 'changes made' were reported. While staff interviewed were mostly understanding of why patients might prefer giving anonymised feedback, some found it uncomfortable and challenging. Participants described instances where they might seek to de-anonymise the individual, in order to pass on personal thanks to the relevant staff member, or to investigate the issue raised and seek resolution offline. Patients did not always want to identify themselves; this could sometimes lead staff to query the veracity or importance of issues raised. Sometimes staff could identify individuals anyway, including one described as 'our regular person'.

conclusionsStaff used to engaging directly with patients and families, both clinically and in dealing with feedback, need support in dealing with anonymous feedback, and the uncomfortable situation of unequal power it may create.

Indexed as

anonymityCare OpinionNHS staffonline feedbackPatient experiencepatient feedbackpowerqualitative research

Identifiers

PMID32030194
PMCPMC6978824

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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.