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Record W3134728343 · doi:10.1093/jcag/gwab002.074

A76 CLINICAL OUTCOMES, HEALTHCARE UTILIZATION AND COSTS AVOIDED WHEN ROUTINE GASTROENTEROLOGY REFERRALS ARE MANAGED IN PRIMARY CARE SUPPORTED BY CO-DEVELOPED CLINICAL CARE PATHWAYS

2021· article· en· W3134728343 on OpenAlexaffabout
Aatif Qureshi, Paul J. Belletrutti, Matthew Mazurek, Susan Jelinski, Brooke Maracle, G S Heather, Gilaad G. Kaplan, Sander Veldhuyzen van Zanten, Mark G. Swain, Kerri L. Novak

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineReferralSpecialtyMedical homeTriageHealth careMedical recordManaged careEmergency medicineObservational studyFamily medicineInternal medicinePrimary care

Abstract

fetched live from OpenAlex

Abstract Background The demand for gastroenterology (GI) care in Canada outstrips the supply. In the Calgary Zone, a Central Access and Triage (CAT) model is used as a single point of entry for most GI referrals. In collaboration with primary care, clinical care pathways (CCP) were co-developed and implemented in CAT to support care for common GI referrals in the Primary Care Medical Home (PCMH), avoiding specialty consultation/endoscopy. Aims To evaluate the re-referral rate, health outcomes, health system utilization (emergency department (ED) visits and hospitalizations) and costs avoided for referrals managed in the PCMH. Methods A prospective observational cohort study of patient referrals declined (closed) by CAT for one of seven indications supported with CCPs: chronic abdominal pain, chronic constipation, chronic diarrhea, dyspepsia, reflux disease, Helicobacter pylori, and irritable bowel syndrome (IBS). Patient clinical records were linked to healthcare administrative databases to extract data: CAT, electronic medical records, discharge databases, and physician billing claims. The Pampalon Deprivation Index evaluated socioeconomic status and education level. Costs according to Canadian Institute for Health Information were estimated for healthcare utilization, consultation and endoscopy. Results A total of 3435 referrals were closed for 3274 patients during the study period (July 1, 2018 to May 31, 2020) with dyspepsia being the most common indication (34%). The median age was 45 years, 66% were women and 43% of higher socioeconomic status. Re-referral to GI occurred in 12% leading to 414 endoscopies performed in 348 patients, the majority were normal (93.6%). Two diagnoses of colorectal adenocarcinoma were identified: 1 originally referred for dyspepsia with subsequent colonoscopy for FIT positivity and 1 initially referred for chronic diarrhea but later presented with hematochezia. Over one year, 11% of patients visited an ED yet less than half for the same indication (42.7%, 263/616 visits) with abdominal pain, dyspepsia, and IBS as most common reasons. There were 52 patients with 68 hospitalizations, but only 24% related to GI referral (constipation and abdominal pain). Estimated total costs avoided was $(CA)2,275,344; and with estimated healthcare utilization of $1,440,281, the net costs avoided was $1,477,237. Conclusions Innovative, collaborative strategies aimed to better match supple-demand disparity and improve appropriateness of specialty GI referrals are critical to improving timely patient care. Use of CCPs to support care in the PCMH is safe and reduces costs. Continued development of such supports is important to reduce avoidable healthcare utilization. Funding Agencies Health Innovation Implementation and Spread (HIIS) Fund

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)0.001
metaresearch head score (Gemma)0.005
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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.165
GPT teacher head0.431
Teacher spread0.266 · 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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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