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Record W2792509405 · doi:10.1093/jcag/gwz006.077

A78 IMPACT OF IMPLEMENTING A RAPID ACCESS CLINIC IN A HIGH-VOLUME INFLAMMATORY BOWEL DISEASE CENTER: ACCESSIBILITY, REASOURCE UTILISATION AND OUTCOMES

2019· article· en· W2792509405 on OpenAlexaffabout
S Nene, Jason Reinglas, Lóránt Gönczi, Zsuzsanna Kürti, Sophie Restellini, Rita Kohen, Waqqas Afif, Talat Bessissow, Gary Wild, Ernest G. Seidman, Alain Bitton, Péter L. Lakatos

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseEmergency departmentDiseaseCalprotectinPhoneEmergency medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

Emergency situations in inflammatory bowel diseases (IBD) put significant burden on the patient and healthcare system as well. We aimed to prospectively measure indicators of quality-of-care, after implementation of a new rapid access clinic (RAC) at the McGill University Health Centre (MUHC) tertiary care IBD center. The RAC provides patients an opportunity to be evaluated by IBD specialists urgently without having to present to the emergency department. RAC was structured by providing an emergency contact email address to the patients, with a specific document explaining the pertinent symptoms that merit utilization of this access avenue. Each email was read and reviewed by a specialized IBD nurse or physician. Patient access, resource utilization and outcome parameters were collected from MUHC IBD Center Rapid Access clinic including consecutive patients who contacted the RAC via email between July 2017 and September 2018. 261 patients (44.1% men, mean age: 39 years, CD: 64% [L3: 46.2%, B2–3: 31.8%], UC: 32% [extensive colitis: 56.6%], biological therapy: 61.6%, previous surgery: 20.4%) were included. 85.7% of requests were deemed appropriate for a rapid appointment. The reason for RAC appointment was potential disease flare in 62.5% of patients. The median time to RAC visit was 3 days (IQR: 1–6 days) from the first point of contact (email/phone) by the patient. Patients had a fast track evaluation with optimized resource utilization in the majority of cases. CRP and fecal calprotectin were the most common measures of disease severity performed, 85.2% and 62.5%, respectively. Clostridium difficile stool test and stool culture test were performed in 43.8% and 42.4% of the patients. The frequency of colonoscopy and flexible sigmoidoscopy following the RAC visit were 22.9% and 6.7%. Only a minority of patients underwent CT (7.1%) and MR (1%) imaging. A change in therapy occurred in 57.0% of patients. Within 30 days from the index visit, 21 patients (19 patients with IBD related symptoms) required ER. 8 ER visits were initiated during the RAC visit and resulted in admission, 7 other patients had unplanned ER visit due to continuous IBD activity. Only 5 patients who were screened by the RAC physician and deemed not to require an urgent consultation presented at the ER (unplanned ER visit rate were 1.8%, no patient required admission). Implementation of an RAC improved healthcare delivery by avoiding unnecessary ER visits and by increasing access to an IBD center. Patients had a fast track evaluation with optimized resource utilization. Data presented here can serve as example for a more optimal cost utilization for future IBD centers. McGill Department of Medicine CAS Research Support

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.383
Teacher spread0.299 · 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 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
Published2019
Admission routes2
Has abstractyes

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