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Record W2128772904 · doi:10.1371/journal.pone.0039737

Potential Savings of Harmonising Hospital and Community Formularies for Chronic Disease Medications Initiated in Hospital

2012· article· en· W2128772904 on OpenAlexafffundabout
Lauren Lapointe‐Shaw, Hadas D. Fischer, Alice Newman, Ava John‐Baptiste, George Anderson, Paula A. Rochon, Chaim M. Bell

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsSt. Michael's HospitalInstitute for Clinical Evaluative SciencesWomen's College HospitalUniversity of Toronto
FundersInstitute of Nutrition, Metabolism and DiabetesCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsFormularyMedicineMedical prescriptionEmergency medicinePharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: Hospitals in Canada manage their formularies independently, yet many inpatients are discharged on medications which will be purchased through publicly-funded programs. We sought to determine how much public money could be saved on chronic medications if hospitals promoted the initiation of agents with the lowest outpatient formulary prices. METHODS: We used administrative databases for the province of Ontario to identify patients initiated on a proton pump inhibitor (PPI), angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) following hospital admission from April 1(st) 2008-March 31(st) 2009. We assessed the cost to the Ontario Drug Benefit Program (ODB) over the year following initiation and determined the cost savings if prescriptions were substituted with the least expensive agent in each class. RESULTS: The cost for filling all PPI, ACE inhibitor and ARB prescriptions was $ 2.48 million, $968 thousand and $325 thousand respectively. Substituting the least expensive agent could have saved $1.16 million (47%) for PPIs, $162 thousand (17%) for ACE inhibitors and $14 thousand (4%) for ARBs over the year following discharge. INTERPRETATION: In a setting where outpatient prescriptions are publicly funded, harmonising outpatient formularies with inpatient therapeutic substitution resulted in modest cost savings and may be one way to control rising pharmaceutical 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 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 score0.160
Threshold uncertainty score0.467

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 head0.101
GPT teacher head0.283
Teacher spread0.182 · 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

Citations14
Published2012
Admission routes3
Has abstractyes

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