P291 Improvements in access to IBD care following the implementation of a novel tiered triage model
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) requires early disease identification and close monitoring of disease activity. Centralised referral systems offer benefits in reduced wait times and opportunities for refinements in referral management. The Vancouver Island IBD Clinic obtains referrals through the regional gastroenterology (GI) group which receives an average of 750 referrals per month. In 2018, our intake system, GI Central Access and Triage (GICAT), was migrated onto a new platform within our electronic medical record allowing us to optimise referral management system-wide. As part of innovative changes to GICAT, we initiated distribution of all IBD referrals directly to IBD specialists for immediate triage. Along with review and prioritisation, immediate specialist triage facilitates proactive ordering of subsequent tests such as faecal calprotectin in a ‘tiered’ triage model to further refine referral management decisions. The aim of this study was to evaluate the short-term impact of our novel electronic tiered triage model on the processing of IBD referrals. Referrals received by central fax were immediately distributed to GIs for triage, requiring identification of referral indication, pathway, urgency, and outstanding information or lab testing. Referrals were then expedited or returned to a common pool for distribution, with triages displayed on a real-time dashboard. Outstanding information was requested either prior to triage completion or scheduling. To understand enhancements to referral refinement, timing of referrals received and cancelled was measured over 10 months following implementation, as were changes to urgency and requests for information or testing. The number of weeks to initial consult for urgent IBD referrals and from referral date to GI triage were compared 6 months pre and post-implementation. In the first 10 months following the transition to GICAT, 7940 referrals were received with 18% per cent immediately cancelled or redirected via GICAT. Immediate triage facilitated requests for information and testing prior to consult in 29% of cases and changes to urgency in 62%. Time-to-triage was on average 22 weeks shorter for IBD referrals (24.3 vs. 2.2 weeks; p < 0.001) post-implementation. Wait times for urgent IBD consults were 2.4 weeks shorter in the post implementation audit (3.9 vs. 6.3; p = 0.044). The transition to a novel triage management system decreased both time-to-triage and urgent wait times for IBD referrals. This process also expedited proactive testing, changes to urgency, and cancellation of inappropriate referrals. Centralised electronic tiered referral systems show great potential as innovative platforms for the rapid adaptive triage of IBD referrals in high volume centres.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".