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Record W4414774455 · doi:10.1136/bmjoq-2024-002774

Altering physician referral practices is challenging, but not impossible: spine assessment clinic quality improvement study

2025· article· en· W4414774455 on OpenAlexaff
Aaron Varga, Florence Slomp, Vanessa Ritchie, Linda Slater-MacLean, Emily Thiessen, Aaron Hockley

Bibliographic record

VenueBMJ Open Quality · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsReferralQuality managementPrimary carePsychological interventionQuality (philosophy)Patient referralMEDLINE

Abstract

fetched live from OpenAlex

INTRODUCTION: Access to medical specialists is a persistent challenge, with neurosurgical spine services reporting some of the longest waits across all fields. Inappropriate and incomplete referrals contribute to delayed access to these providers. Referral guidelines and physician education have been shown to decrease such inefficiencies. Therefore, the goal of this study was to address inappropriate referrals directed to the neurosurgical spine assessment clinic via implementation of a quality improvement initiative. We hypothesised that appropriate referrals, which included patients with potential surgical pathology and fulfilled referral criteria, would increase by 25% following referral guideline distribution. METHODS: A three-phase study was implemented: (1) baseline data were collected from preintervention referrals by noting the reason for consultation and if certain information, deemed relevant for an appropriate referral, was included; (2) a referral guideline, outlining when and how to refer, was distributed to family physicians in the region; and (3) postintervention referrals were collected and analysed as in phase I. RESULTS: A total of 404 referrals were collected (161 pre-intervention and 243 post-intervention). A 36% increase in patients who were deemed appropriate surgical candidates was reported post-intervention (p=0.044), with an escalation in the proportion of patients requiring neurosurgeon assessment observed over time. Limited improvements were appreciated in the presence of the criteria indicated for inclusion in a referral document. CONCLUSION: While challenges remain when attempting to modify the referring behaviours of primary care physicians, this research has demonstrated that guidelines aimed at enhancing specialist directed referrals can lead to improvements in their performance. Nonetheless, translating guidelines into practice is a recognised issue, often requiring time and multiple exposures. Active forms of medical education and multifaceted interventions have been demonstrated to be the most effective means of implementing guidelines into practice, an approach that could further address referral inadequacies in the future.

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0000.001
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 head0.276
GPT teacher head0.547
Teacher spread0.271 · 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.

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
Published2025
Admission routes1
Has abstractyes

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