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Pharmacy Information Systems in Canada

2009· article· en· W117176287 on OpenAlexaffabout
Jeff Barnett, Heather Jennings

Bibliographic record

VenueStudies in health technology and informatics · 2009
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsPharmacyInteroperabilityInformaticseHealthHealth informaticsDrugMedicineInformation systemElectronic prescribingElectronic health recordMedical emergencyHealth careComputer scienceFamily medicineNursingWorld Wide WebPharmacologyPublic healthEngineering

Abstract

fetched live from OpenAlex

The goal of Canada Health Infoway is to provide at least 50% of all Canadians with an electronic health record (EHR) by 2010. The goal of the Infoway Drug Information Systems Program is to develop an interoperable drug information system that will keep each patient's medication history: prescribed and dispensed drugs, allergies, ongoing drug treatment, etc. Drug and drug-interaction checks will be performed automatically and added to the patients' drug profiles. Physicians and pharmacists will be supplied with data to support appropriate and accurate prescribing and dispensing, thereby avoiding adverse drug interactions and drug-related deaths [1]. This paper describes Canadian developments in pharmacy eHealth. It presents the results of the Pharmacy Informatics Pharmacy Special Networks (PSN) survey about computer systems used in hospital pharmacies across Canada including information concerning Computerized Provider Order Entry (CPOE) systems deployed; which may reduce the number of errors in orders.

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.841
Threshold uncertainty score0.976

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.013
Science and technology studies0.0110.002
Scholarly communication0.0080.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0270.002

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 head0.072
GPT teacher head0.456
Teacher spread0.384 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2009
Admission routes2
Has abstractyes

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