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A Retrospective Evaluation of the Quality of Referrals to IBD Specialist Care and Its Influence on Patient Outcomes

2018· article· en· W2977772671 on OpenAlexaboutno aff
Mathias Holly, Heisler Courtney, Julia Morrison, Jones Jennifer

Bibliographic record

VenueThe American Journal of Gastroenterology · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReferralSpecialtyFamily medicineTriageRetrospective cohort studyDiseaseInflammatory bowel diseaseCohortHealth carePediatricsEmergency medicineInternal medicine

Abstract

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BACKGROUND: IBD is an immune-mediated disease, which includes Crohn's Disease and Ulcerative Colitis. Because of the health and socioeconomic burden associated with IBD, timely access to specialist care is important. In Canada, specialty gastroenterology (GI) care is accessed only by referral. In order to receive timely care, the referral needs to include key disease-related clinical information. Two-thirds of Canadian specialist physicians surveyed reported a lack of basic information on the initial referral (CMA, 2014). Referrals are often returned to the referring physicians for more information, which is inefficient and costly for patients and physicians. Past GI research has examined the quality of referrals, yet no research has measured how the quality of referrals influences patient outcomes. The main objective was to determine if referrals to the Nova Scotia Collaborative Inflammatory Bowel Disease (NSCIBD) program contain sufficient information to allow accurate triage for timely access to care. Our secondary objective was to determine how the quality of initial referrals to the NSCIBD program inform wait times and disease-related outcomes (e.g. disease flare, hospitalization). METHODS: This study was a retrospective cohort review of patient referrals for NSCIBD program appointments between August 2016 and June 2017. Inclusion criteria included 1) patient's first visit to the NSCIBD program for 2) confirmed or suspected IBD. Referrals were excluded if they were for a non-IBD-related concern, an endoscopic test, or a follow up visit. Referrals were evaluated using a data abstraction form containing evidence-based, clinical risk-stratification variables, developed with a luminal gastroenterologist and two IBD nurse practitioners. Based on the provided information, referrals were classified as either low, moderate, or high-quality. 136 referrals were provided a power of 0.8 (P=0.05) to detect a difference in wait times between classifications. Logistic regression was used to determine factors that influenced referral quality. Mann Whitney U was used to compare mean differences in wait times, disease flares, and hospitalizations between high/moderate-quality and low-quality referral from the time of initial referral to first IBD consultation. Spearman's rho was used to find correlations between patient outcomes and relevant patient factors for both classifications. RESULTS: In total, there were 9 high-quality referrals (6.6%), 23 moderate-quality referrals (16.9%) and 104 low-quality referrals (76.5%). Quality of referral was significantly influenced by several key factors, including referring provider and legibility of referral. Average wait time for patients with a high/moderate-quality referral (14.1 weeks) was significantly lower than wait time for patients with a low-quality referral (31.9 weeks) (U=1458.00, P=0.042). Wait times for patients with a low-quality referral were associated with hospitalization, disease flare, additional referrals, age, sex, diagnosis, duration of disease, phenotype, past and current medication. CONCLUSION(S): The majority of referrals received by the NSCIBD program were low-quality and have resulted in a significantly longer wait time for patients referred to the program. Prolonged wait time is concerning given its negative impact on disease-related outcomes. The results of this study suggest that referring physicians require education regarding risk-stratification in IBD and that standardized referral forms would allow for more accurate risk-stratification and triage of patients referred to IBD specialty programs.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.340
Teacher spread0.297 · 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.

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".

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Citations2
Published2018
Admission routes1
Has abstractyes

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