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Record W2585592635 · doi:10.1111/tme.12391

Audit of provincial <scp>IVIG</scp> Request Forms and efficacy documentation in four Ontario tertiary care centres

2017· article· en· W2585592635 on OpenAlexaffabout
Andrew W. Shih, Erin Jamula, Calvin Diep, Yulia Lin, Chantal Armali, Nancy M. Heddle, Aissata Doucoure Traore, Jordan Doherty, Nyah Shah, Christopher Hillis

Bibliographic record

VenueTransfusion Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoMcMaster UniversityCanadian Blood ServicesHealth Sciences CentreMcMaster University Medical Centre
Fundersnot available
KeywordsDocumentationMedicineAuditTertiary careSpecialtyMedical recordRetrospective cohort studyPediatricsFamily medicineEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Retrospective audit of IVIG Request Forms in four Ontario tertiary care centres: to determine the case mix of new IVIG requests, to authenticate information provided, and to determine documentation of clinical efficacy. AIMS: To understand contributors to increases in IVIG utilisation and to determine whether IVIG is being used and monitored appropriately. INTRODUCTION: Intravenous immunoglobulin (IVIG) use in Canada is high compared with other developed countries. We performed a retrospective audit of new IVIG Request Forms across four tertiary care centres in Ontario, one with an active surveillance programme, to determine the case mix, authenticate information provided and assess documentation of efficacy. METHODS: Consecutive adult patients with a first-time IVIG request in 2014 were included. The ordering physician specialty, form completeness, documentation of diagnostic criteria for the medical condition and indication for IVIG use and documentation of efficacy were assessed by form and chart review. RESULTS: Of 178 patients, the most common indications for IVIG were immune thrombocytopenia (24.2%) and secondary immune deficiency (20.2%). The most frequent prescribers were haematologists (37.6%) and neurologists (10.7%). Other conditions not listed on the form represented 24.2% of cases, with most not indicated in current guidelines. A total of 32.6% of cases overall lacked verification of diagnostic criteria and 51.7% lacked verification for IVIG utilisation criteria, with the number of cases meeting criteria based on documentation being higher at the active surveillance site (P = 0.005). A total of 19.1% of cases had a discrepancy between the indication written on the form and the documented clinical diagnosis. A total of 18.7% of clinic notes following IVIG had no mention of efficacy. CONCLUSION: Our audit demonstrates a lack of compliance with IVIG Request Form requirements, a lack of documentation of diagnostic criteria and efficacy, and suggests inappropriate use of IVIG. Current implementation of the form may not be sufficient as a strategy for improving appropriate IVIG use.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.106
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.276
Teacher spread0.264 · 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".

Quick stats

Citations10
Published2017
Admission routes2
Has abstractyes

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