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Record W4407560647 · doi:10.4212/cjhp.3648

Reducing Sugammadex Expenditure through Educational Initiatives in an Urban Tertiary Care Hospital System: A Cost-Reduction Study

2025· article· en· W4407560647 on OpenAlexaffvenueabout
Erin M. Ingoldsby, Eric Romeril, Aixin Liu, Tal Levit, Ekta Khemani

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2025
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsMcMaster Divinity CollegeHamilton Health SciencesMcMaster University
Fundersnot available
KeywordsSugammadexTertiary careReduction (mathematics)Cost reductionMedicineBusinessEmergency medicineAnesthesiaRocuronium

Abstract

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Background: Sugammadex, a selective relaxant binding agent, works by encapsulating rocuronium or vecuronium to reverse neuromuscular blockade. It is an asset in emergencies requiring expedient reversal of neuromuscular blockade, such as situations involving difficult airways. A prevalent concern relating to sugammadex use is its higher cost compared with traditional reversal agents, contributing to more than 20% of operating room drug expenditures at Hamilton Health Sciences (Hamilton, Ontario) in 2019/20. Objective: To use iterative Plan-Do-Study-Act cycles to reduce annual sugammadex expenditure at Hamilton Health Sciences by 50% from costs in the 2020/21 fiscal year. Methods: Five Plan-Do-Study-Act cycles were implemented (January to April 2021) to increase awareness about the cost of sugammadex and appropriate indications for its use. The organization’s Department of Pharmacy supplied data regarding acquisition of sugammadex before, during, and after the Plan-Do-Study-Act cycles, which were analyzed quantitatively. A data set regarding difficult airways at Hamilton Health Sciences was analyzed alongside the sugammadex data to aid in understanding the need for accessibility of this drug. Results: Use of sugammadex in fiscal year 2021/22 at Hamilton Health Sciences decreased by 75% from the previous fiscal year, without compromising patient safety or drug availability. Analysis of the difficult airway data revealed that both anticipated and unanticipated cases of difficult airway were still prevalent across all hospitals, which highlights the importance of maintaining access to and knowledge of how to use sugammadex in the setting of difficult airways. Conclusions: This cost-reduction project showed that user-based program designs can have a meaningful impact on resource utilization. Additionally, the difficult airway data set emphasized the clear need to maintain availability of and capabilities for administering sugammadex, given the prevalence of emergency airway situations. Keywords: cost reduction, anesthesia, resources, patient safety, drug utilization review, sugammadex, hospital pharmacy service RÉSUMÉ Contexte : Le sugammadex, un agent de liaison sélectif des relaxants, agit en encapsulant le rocuronium ou le vécuronium pour inverser le blocage neuromusculaire. Il constitue un atout précieux en cas d’urgence nécessitant une inversion rapide du blocage neuromusculaire, comme dans les situations impliquant une gestion difficile des voies aériennes. Une préoccupation courante liée à l’utilisation du sugammadex est son coût plus élevé par rapport aux agents d’inversion traditionnels. Il représentait plus de 20 % des dépenses en médicaments des salles d’opération de l’autorité sanitaire Hamilton Health Sciences (à Hamilton, en Ontario) en 2019-2020. Objectif : Utiliser des cycles itératifs Planifier-Faire-Vérifier-Agir (PFVA) pour réduire de 50 % les dépenses annuelles de sugammadex de l’autorité sanitaire Hamilton Health Sciences par rapport aux coûts de l’exercice 2020-2021. Méthodologie : Cinq cycles PFVA ont été mis en œuvre (de janvier jusqu’en avril 2021) pour sensibiliser le personnel au coût du sugammadex et aux indications appropriées relatives à son utilisation. Le département de pharmacie de l’organisme a fourni des données sur l’acquisition de sugammadex avant, pendant et à la fin de la série de cycles PFVA, qui ont été analysées quantitativement. Un ensemble de données concernant la gestion difficile des voies aériennes à l’autorité sanitaire Hamilton Health Sciences a été analysé en parallèle avec les données sur le sugammadex afin de mieux comprendre la nécessité d’assurer l’accessibilité de ce médicament. Résultats : L’utilisation du sugammadex à l’autorité sanitaire Hamilton Health Sciences pendant l’exercice 2021-2022 a diminué de 75 % par rapport à l’exercice précédent, sans compromettre la sécurité des patients ni la disponibilité du médicament. L’analyse des données portant sur la gestion difficile des voies aériennes a révélé que les cas anticipés et non anticipés de gestion difficile demeuraient fréquents dans tous les hôpitaux, ce qui souligne l’importance de maintenir l’accès au sugammadex et de maîtriser son utilisation dans le contexte de la gestion difficile des voies aériennes. Conclusions : Ce projet de réduction des coûts a démontré que des approches centrées sur les utilisateurs peuvent avoir des conséquences importantes sur l’utilisation des ressources. Par ailleurs, l’analyse des données relatives à la gestion difficile des voies aériennes a mis en évidence la nécessité indéniable de maintenir la disponibilité du sugammadex et les compétences pour son administration, compte tenu de la fréquence des situations d’urgence impliquant des voies aériennes. Mots-clés : réduction des coûts, anesthésie, ressources, sécurité des patients, examen de l’utilisation des médicaments, sugammadex, service de pharmacie hospitalière

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)0.009
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 score0.155
Threshold uncertainty score0.308

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.330
Teacher spread0.312 · 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".

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Citations0
Published2025
Admission routes3
Has abstractyes

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