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Record W7053279308

Ultrasound assessment of small bowel Crohn's disease: A mixed methods exploration of barriers and facilitators to implementation in adult NHS IBD services

2023· other· en· W7053279308 on OpenAlexaboutno aff

Bibliographic record

VenueNottingham ePrints (University of Nottingham) · 2023
Typeother
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsnot available
FundersUniversity of NottinghamNational Institute for Health and Care Research
KeywordsDelphi methodSBusStakeholderQualitative researchIntervention (counseling)Health careDelphiInflammatory bowel diseaseDiseaseMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

Background: Crohn’s disease (CD) is a long-term condition which requires repeated disease monitoring via medical imaging, where repeated burdensome medical investigations negatively impact on patients quality of life. Small bowel ultrasound scanning (SBUS) has been shown to be similar in accuracy when compared to magnetic resonance enterography (MRE), has the potential to be quicker, less costly and improve patient experience of care, but it is not routinely used in NHS IBD care.
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\nObjectives: This thesis aims to provide insight on how best to support the implementation of SBUS in practice by collecting information about current national usage and appetite for SBUS uptake, stakeholder perceptions of the adoption of the intervention by health services and the potential impact of use of SBUS on care pathways in routine CD care. Findings from this work will contribute to the production of an implementation package to facilitate national uptake of SBUS in NHS IBD services.
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\nMethods: A scoping literature review and three research studies were undertaken throughout this programme of work. The scoping literature review was undertaken to explore clinical utility of SBUS in IBD settings. A national survey was undertaken to uncover current usage and appetite for use of SBUS in IBD settings. A qualitative semi structured interview study was undertaken to explore stakeholder perceptions of SBUS use and implementation of ultrasound in IBD settings. A care pathway analysis and cost implications analysis were undertaken to gauge the impact of the introduction of SBUS into an NHS IBD service. The quantitative data were analysed using descriptive statistics. Qualitative data were analysed using template analysis.
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\nResults: Ultrasound is reported as quicker, more acceptable to patients and safer when compared to MRE and has been shown to be similarly accurate in detecting presence and extent of small bowel CD. Ultrasound is used widely in central Europe and Canada but has not yet been embraced in the UK. Survey responses indicated that there is an appetite for the uptake of SBUS in NHS services. There is disparity in confidence levels when using ultrasound to make clinical decisions, compared to MRE. The interview study revealed that stakeholders believe that the introduction of SBUS into clinical services would be beneficial to patient experience, outcomes and cost reduction. There are concerns in relation to the availability of training for health care professionals and the belief that there are still concerns relating to accuracy of SBUS compared to MRE. Interview participants believed that the largest barriers to implementation of SBUS in the NHS were the existing practices, beliefs and behaviours of healthcare professionals which are likely to be difficult to amend. Care pathway and costs implications analysis’ showed that there are significant potential cost saving and waiting time reduction implications to the introduction of SBUS into NHS IBD services.
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\nConclusions: Recommendations from this work which will contribute to the generation of an implementation package for SBUS include the need for well-structured and supported training for health care professionals, tools for identifying and fostering leadership roles in promoting and sustaining change and mechanisms for reviewing and adapting SBUS over time to ensure it meets the needs of stakeholders and IBD services.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.289
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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