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Record W4213379602 · doi:10.1093/jcag/gwab049.076

A77 IMPLEMENTATION OF GUT LINK-IBS; RESULTS OF A SEMI-STRUCTURED INTERVIEW OF PRIMARY CARE PROVIDERS

2022· article· en· W4213379602 on OpenAlexaffabout
Sowmya Sharma, Courtney Heisler, Jennifer Jones, Michael J. Stewart

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsHealth Sciences CentreDalhousie University
Fundersnot available
KeywordsReferralMedicineQualitative researchPrimary careNursingStakeholderFamily medicineStakeholder engagement

Abstract

fetched live from OpenAlex

Abstract Background The Division of Digestive Care and Endoscopy in Halifax, Nova Scotia has had longstanding challenges with GI referral volume outstripping divisional capacity resulting in limited access to specialist care. Many referrals for functional bowel disorders (FBD) are returned to referring providers. Although this helps rationalize limited system resources, it often impairs access to appropriate and necessary GI care. The co-development and implementation of clinical care pathways across gastroenterology and primary care may help to improve access to high-quality GI care. Aims The project aimed to engage primary healthcare providers (PHCPs) to identify environmental and behavioral barriers and facilitators for managing undifferentiated lower GI disorders in primary care. Data generated from stakeholder engagement will be used to develop, implement, and evaluate strategies for referral and management of FBD. A real-world, functional clinical care pathway that supports the implementation of evidence-based practices in the diagnosis and management of functional GI conditions within primary care will enhance care and timely access to specialist. Methods This is a qualitative study using semi-structured interviews of PHCPs working in Nova Scotia. Interview questions were developed and guided by the evidence-based implementation science frameworks. Physicians were recruited through existing primary care networks. Participants were offered a Zoom™virtual semi-structured interview. A brief intake questionnaire was administered to collect baseline demographics. Interviews were recorded and transcribed for data analysis. Data were categorized into coding schemes and themes were created using an inductive coding approach. Results As of October 2021, 9 interviews have been conducted. Average participant age was 44 years, with the majority identifying practice in a group or collaborative care setting (n=7, 78%). Five worked in urban practice settings and the remainder in rural areas. Preliminary major themes included: 1. A lack of satisfaction with access to gastrointestinal care, with most physicians noting it to be worse than access to other specialist services. 2. Management of FBDs were felt to be within the scope of primary care practice 3. Access to diagnostic tests like fecal calprotectin with appropriate education on its use as a diagnostic tool would be useful. 4. PHCP’s suggested care pathways be easy to use, require minimal time, and ideally be implemented within their pre-existing EMR or in paper form. Conclusions PHCPs acknowledge a significant burden of undifferentiated lower GI complaints in their practice and poor access to gastroenterology services. All participants were open to helping develop and use a clinical care pathway for the investigation and management of undifferentiated lower GI symptoms. Data collection and analysis are ongoing. Funding Agencies None

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.004
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.180
GPT teacher head0.439
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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