Evidence map›Paper›PMID 37368436›Full record

ArticleHealth services management research2024

How does staff and patient feedback on hospital quality relate to mortality outcomes? A provider-level national study.

Antonio Michael Borrelli, Rebecca J Birch, Katie Spencer

Abstract read
In one paragraph

Article in Health services management research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

3 authors.

Antonio Michael BorrelliSheffield Teaching Hospitals NHS Foundation Trust, Northern General Hospital, South Yorkshire, Sheffield S5 7AT, UK.ORCID 0000-0001-8200-175X
Rebecca J BirchLeeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Katie SpencerLeeds Institute for Data Analytics, University of Leeds, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to use national data to examine the relationship between staff and inpatient survey results (National Health Service (NHS) Friends and Family Test (FFT)) and assess how these align with more traditional measurements of hospital quality as captured by the summary hospital mortality indicator (SHMI). Provider level FFT responses were obtained for 128 English non-specialist acute providers for staff and inpatients between April 2016 and March 2019. Multilevel linear regression models assessed the relationship between staff and patient FFT recommendations, and separately how SHMI related to each of staff and patient FFT recommendations. A total of 1,536 observations were recorded across all providers and financial quarters. Patients were more likely to recommend their provider (95.5%) than staff (76.8%). In multivariable regression, a statistically significant association was observed between staff and patient FFT recommendations. A statistically significant negative relationship was also observed between staff FFT recommendations and SHMI. The association between SHMI and staff FFT recommendations suggests that staff feedback tools may provide a useful analogue for providers in potential need of intervention and improvement in care. For patients meanwhile, qualitative approaches and hospital organisations working in partnership with patients may provide better opportunities for patients to drive improvement.

Indexed as

FeedbackHospital MortalityQuality of Health CareAdultFemaleHospitalsHumansMaleMiddle AgedPatient SatisfactionState MedicineSurveys and Questionnairesmortalitypatient satisfactionquality improvementStaff views

Identifiers

PMID37368436
PMCPMC11041065

What OpenQuestion holds

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LicenceCC BY
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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.