Evidence map›Paper›PMID 32381075›Full record

ArticleBMC health services research2020

Implementing a digital patient feedback system: an analysis using normalisation process theory.

Bie Nio Ong, Damian Hodgson, Nicola Small, Papreen Nahar, Caroline Sanders

Abstract read
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

15 citing papers in PubMed.

  1. Trial
  2. Stimulating Employability and Job Crafting Behaviour of Physicians: A Randomized Controlled Trial.International journal of environmental research and public health · 2022
    Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Ensuring patient and public involvement in the transition to AI-assisted mental health care: A systematic scoping review and agenda for design justice.Health expectations : an international journal of public participation in health care and health policy · 2021
    Article
  14. Article
  15. 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.

Bie Nio OngNIHR School for Primary Care Research, University of Manchester, Manchester, UK.
Damian HodgsonSheffield University Management School, University of Sheffield, Sheffield, UK.
Nicola SmallNIHR School for Primary Care Research, University of Manchester, Manchester, UK.
Papreen NaharBrighton and Sussex Medical School, Department of Global Health and Infection, Brighton and Sussex Medical School, University of Sussex, Brighton, UK.
Caroline SandersNIHR School for Primary Care Research, University of Manchester, Manchester, UK. caroline.sanders@manchester.ac.uk.

Funding

Department of Health HS&DR/14/156/16National Institute for Health Research 14/156/16
6 · The paper itself

Abstract

backgroundPatient feedback in the English NHS is now widespread and digital methods are increasingly used. Adoption of digital methods depends on socio-technical and contextual factors, alongside human agency and lived experience. Moreover, the introduction of these methods may be perceived as disruptive of organisational and clinical routines. The focus of this paper is on the implementation of a particular digital feedback intervention that was co-designed with health professionals and patients (the DEPEND study).

methodsThe digital feedback intervention was conceptualised as a complex intervention and thus the study focused on the contexts within which it operated, and how the different participants made sense of the intervention and engaged with it (or not). Four health care sites were studied: an acute setting, a mental health setting, and two general practices. Qualitative data was collected through interviews and focus groups with professionals, patients and carers. In total 51 staff, 24 patients and 8 carers were included. Forty-two observations of the use of the digital feedback system were carried out in the four settings. Data analysis was based on modified grounded theory and Normalisation Process Theory (NPT) formed the conceptual framework.

resultsDigital feedback made sense to health care staff as it was seen as attractive, fast to complete and easier to analyse. Patients had a range of views depending on their familiarity with the digital world. Patients mentioned barriers such as kiosk not being visible, privacy, lack of digital know-how, technical hitches with the touchscreen. Collective action in maintaining participation again differed between sites because of workload pressure, perceptions of roles and responsibilities; and in the mental health site major organisational change was taking place. For mental health service users, their relationship with staff and their own health status determined their digital use.

conclusionThe potential of digital feedback was recognised but implementation should take local contexts, different patient groups and organisational leadership into account. Patient involvement in change and adaptation of the intervention was important in enhancing the embedding of digital methods in routine feedback. NPT allowed for a in-depth understanding of actions and interactions of both staff and patients.

Indexed as

FeedbackProfessional-Patient RelationsEnglandFocus GroupsHumansPsychological TheoryQualitative ResearchState MedicineAcute careDigital methodsMental healthNormalisation process theoryPatient feedbackPrimary care

Identifiers

PMID32381075
PMCPMC7203816

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.