MétaCan
Menu
Back to cohort
Record W4398144941 · doi:10.1101/2024.05.20.24307611

Temporal trends and practice variation of paediatric diagnostic tests in primary care

2024· preprint· en· W4398144941 on OpenAlexaff
Elizabeth T Thomas, Diana R. Withrow, Peter J. Gill, Rafael Perera, Carl Heneghan

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsVariation (astronomy)Primary careDiagnostic testMedicinePediatricsFamily medicinePhysics

Abstract

fetched live from OpenAlex

Abstract Objective The primary objective was to investigate temporal trends and between-practice variability of paediatric test use in primary care. Methods and analysis This was a descriptive study of population-based data from primary care consultation records from January 1, 2007, to December 31, 2019. Children aged 0 to 15 who were registered to one of the 1,464 practices and had a diagnostic test code in their clinical record were included. The primary outcome measures were: 1) temporal changes in test rates measured by the average annual percent change (AAPC), stratified by test type, gender, age group, and deprivation level and 2) practice variability in test use, measured by the coefficient of variation (CoV). Results 14,299,598 diagnostic tests were requested over 27.8 million child-years of observation for 2,542,101 children. Overall test use increased by 3.6%/year (95% CI 3.4 to 3.8%) from 399/1,000-child-years to 608/1,000 child-years, driven by increases in blood tests (8.0%/year, 95% CI 7.7 to 8.4), females aged 11-15 (4.0%/year, 95% CI 3.7 to 4.3), and the most socioeconomically deprived group (4.4%/year, 95% CI 4.1 to 4.8). Tests subject to the greatest temporal increases were fecal calprotectin, fractional exhaled nitric oxide (FeNO), and vitamin D. Tests classified as high use and high practice variability were iron studies, vitamin D, vitamin B12, folate, and coeliac testing. Conclusions In this first nationwide study of paediatric test use in primary care, we observed significant temporal increases and practice variability in testing. This reflects inconsistency in practice and diagnosis rates, and a scarcity of evidence-based guidance. Increased test use generates more clinical activity with significant resource implications, but conversely may improve clinical outcomes. Future research should evaluate whether increased test use and variability is warranted by exploring test indications and test results, and directly examine how increased test use impacts on quality of care. Key Messages What is already known on this topic Previous research has shown that test use in adults within UK primary care sharply increased since 2000 and that there is a high degree of practice variation in test use. To date, no population-based studies have analysed paediatric test use in this setting. What this study adds In England between 2007 and 2019, diagnostic test use increased by 4% per year, from 399 tests/1,000 child-years to 608 tests/1000-child years. Test increases were driven blood tests, especially in females aged 11-15 years of age, and children in the most deprived socioeconomic group. Specific tests that increased by the greatest margin include faecal calprotectin, fractional exhaled nitric oxide (FeNO), and vitamin D testing. Tests subject to the greatest practice variation by 2019 were FeNO, hearing tests, and vitamin D levels. How this study might affect research, practice or policy Variability in test use highlights a lack of standardised guidance and evidence in pediatric diagnostics, which has significant implications for downstream diagnostic activity, treatment, referrals and healthcare costs.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.338
Teacher spread0.315 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuemedRxivSame topicClinical Reasoning and Diagnostic SkillsFrench-language works237,207