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Record W4416130362 · doi:10.1093/ajcp/aqaf121.493

66 Evaluating the Impact of an Expanded Trainee-Led Miscellaneous Test Request Review Process on Laboratory Stewardship

2025· article· en· W4416130362 on OpenAlexaboutno aff
Preejith Vachali, Grace Kroner

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Stewardship (theology)Process (computing)Flexibility (engineering)Medical laboratoryQuarter (Canadian coin)Diagnostic test

Abstract

fetched live from OpenAlex

Abstract Clinicians at our institution can request esoteric tests not included in the standard test menu through a miscellaneous order process. While this flexibility allows access to specialized testing, it also introduces possibilities of errors. To address these challenges, a trainee-led review process of miscellaneous requests for chemistry tests was established to systematically assess these requests. Since beginning the process, we have slowly expanded the review to include other disciplines of testing. With now over thirty months of data, we evaluated the effectiveness of the program and how it is changed since initialization. We conducted a retrospective analysis of miscellaneous test request reviews over thirty months. The review process was conducted using our laboratory information system (Epic Beaker) to flag tests for review after specimen collection. Pathology residents reviewed the flagged tests daily and logged them into a shared, secure Excel-based tracker. Residents consulted with medical directors from the relevant laboratory sections for guidance as needed, and a medical director conducted a final daily review to complete the process. Additionally, residents met with a medical director weekly to discuss test requests and evaluate the review workflow. Since establishment of the review process, 4,766 tests requests have been reviewed, increasing from 312 in the first quarter of the program to 569 in the most recent completed quarter due to gradual expansion of the review into non-chemistry disciplines. Requests originate from internal (61.3%) and external/client providers (38.7%). As expected, chemistry tests account for 89.4% of requests; the two next largest categories are microbiology (6.4%) and immunology (3.6%). Of all reviewed requests, 80.6% were approved without modification, while 5.2% were canceled due to redundancy or inappropriateness. An additional 11.7% were converted to a defined in-house test, 1.7% were redirected to an alternative reference laboratory, and 0.8% required modifications to the test ordered. Interventions in all categories except approvals increased over time, reflecting improved recognition of inappropriate or misrouted tests. The median time spent per review was 1 minute, with complex interventions, such as order modifications and redirections, requiring additional time (∼30 minutes). Expanding the scope of the review provided further insights into provider ordering patterns and opportunities for test stewardship initiatives. This review highlights the continued effectiveness of a trainee-led miscellaneous test request review process in optimizing test selection and utilization. The findings support ongoing efforts to engage trainees in laboratory stewardship initiatives to enhance efficiency, reduce inappropriate testing, and improve patient care. Additionally, this process has served as an educational tool, improving residents’ knowledge of esoteric testing and its appropriate use. To further strengthen this initiative, we plan to continue to expand this review process to other laboratory discipline, allowing residents to develop specialized expertise and contribute more effectively to test stewardship.

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)0.017
metaresearch head score (Gemma)0.079
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.079
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.097
GPT teacher head0.555
Teacher spread0.458 · 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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