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Why are investigations not recommended by practice guidelines ordered at the periodic health examination?

2000· article· en· W1522901517 on OpenAlexafffundabout
Carl van Walraven, Vivek Goel, Peter C. Austin

Bibliographic record

VenueJournal of Evaluation in Clinical Practice · 2000
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsUniversity of Ottawa
FundersHealth Canada
KeywordsMedicineFamily medicinePsychological interventionTest (biology)SpecialtyMultivariate analysisHealth careInternal medicineNursing

Abstract

fetched live from OpenAlex

Evidence-based guidelines recommend few routine investigations for healthy adults at the periodic health examination (PHE). However, small studies indicate that laboratory tests are commonly ordered at the PHE. This study examined PHE laboratory testing that is not recommended by recognized guidelines ('discretionary'). Using administrative data from the universal health care system in Ontario, Canada, we studied 792,844 adults having a PHE in 1996 and the 3,727 physicians who administered them. We measured the number of discretionary laboratory tests per PHE along with the patient and physician factors potentially influencing laboratory testing. A multilevel, multivariate model was used to examine the association between the number of discretionary laboratory tests at the PHE with patient and physician characteristics. A mean of 7.1 discretionary tests (SD 7.1) was ordered per PHE. Renal, haematological, glucose and lipid tests each were conducted in more than a third of PHEs. Testing varied extensively between physicians and was more common in healthy patients. With the exception of age, patient factors had little effect on discretionary testing. However, each physician factor we examined was independently associated with the number of discretionary tests. Physician specialty, practice volume and previous testing patterns had the strongest influence on discretionary testing. Discretionary investigations are common at the PHE. Testing varies extensively between physicians and seems to be driven more by physician than by patient factors. Interventions to modify discretionary test utilization at the PHE should consider these physician factors.

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)0.014
metaresearch head score (Gemma)0.109
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 score0.274
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.109
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.250
GPT teacher head0.556
Teacher spread0.306 · 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

Citations23
Published2000
Admission routes3
Has abstractyes

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