Evidence map›Paper›PMID 29982201›Full record

ArticleBMJ open2018

Care pathway and organisational features driving patient experience: statistical analysis of large NHS datasets.

Kelsey Flott, Ara Darzi, Erik Mayer

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

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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

3 authors.

Kelsey FlottNIHR Imperial Patient Safety Translational Research Centre (PSTRC), Imperial College London, London, UK.
Ara DarziCentre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, UK.
Erik MayerCentre for Health Policy, Institute of Global Health Innovation, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe aim of this study was to identify the care pathway and organisational factors that predict patient experience.

designStatistical analysis of large National Health Service (NHS) datasets. SETTING ANDPARTICIPANTS: England; acute NHS organisational-level data. PRIMARY AND SECONDARY OUTCOME MEASURES: The relationship of care pathway and organisational variables to organisation-level patient experience.

resultsA framework of 18 care pathway and organisational variables were created based on the existing literature. 11 of these correlated to patient experience in univariate analyses. Multicollinearity tests resulted in 1 of the 11 variables holding a correlation to another variable larger than r=0.70. A significant multilinear regression equation, including the final 10 variables, was found (F(10,108)=6.214, p<0.00), with an [Formula: see text] of 0.365. Two variables were significant in predicting better in patient experience: Amount of support to clinical staff (beta=0.2, p=0.02) and the proportion of staff who would recommend the trust as a place to work or receive treatment (beta=0.26, p=0.01). Two variables were significant in predicting a negative impact on the patient's rating of their experience: Number of patients spending over 4 hours from decision to admit to admission (beta=-1.99, p=0.03) and the percentage of estates and hotel services contracted out (beta=-0.23, p=0.01).

conclusionsThese results indicate that augmenting clinical support and investing in the mechanisms that facilitate positive staff experience is essential to delivering appropriate, informative and patient-centric care. Reducing wait times and the extent of external contracting within hospitals is also likely to improve patient ratings of experience. Understanding the relationship between patient experience and objective, measurable organisational features promote a more patient-centric interpretation of quality and compel a better use of patient experience feedback to drive improvement.

Indexed as

HospitalizationState MedicineAcute DiseaseEnglandFemaleHealth Care SurveysHealth Services ResearchHumansInpatientsLogistic ModelsMalePatient AdmissionPatient SatisfactionQuality Assurance, Health CareQuality Improvementhealth policyorganisational developmentquality in health care

Identifiers

PMID29982201
PMCPMC6042542

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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.