Improving management of hypersensitivity reactions: A BC Cancer-Victoria quality improvement initiative.
Notice bibliographique
Résumé
230 Background: Hypersensitivity reactions (HSR) are a documented, predictable side effect of multiple chemotherapy agents. Reactions negatively affect the patient experience, increase the amount of chair time, nursing and physician resources, may result in the omission of a potentially effective cancer management tool from a patient’s treatment plan and could potentially result in death. BC Cancer is a Health Care Organization with 6 cancer centres across British Columbia, Canada. Guideline(GL)s have been developed at BC Cancer to support clinicians to manage reactions acutely and reduce the risk of reactions with subsequent cycles. A recent audit identified that the GLs were not always being followed at the Victoria Centre. Our goal was to encourage physician and nursing staff to follow GLs, which we hypothesized would result in decreased rates of HSR. Methods: Our aim was to decrease HSR to < 5% of doses delivered within 1 year at BC Cancer-Victoria. We engaged stakeholders (nursing, physicians, pharmacy, clerical staff and administration). Our change ideas improved adherence to GLs by focusing on: physician attendance and documentation, written orders for rescue medication, and rate of infusion of the chemotherapy drug rechallenge. Our interventions included: two physician-education sessions, one nursing education session, daily huddles, pre-printed order development for management of the reaction (PPOA) and prophylaxis for subsequent cycles (PPOB), and a modified clinic flow. All interventions were introduced and underwent modifications through PDSA cycles. Our family of measures were: Outcome: number of reactions, percent of reactions per dose given. Process: percent of PPO use per reaction, physician attendance and notes dictated per reaction. Balancing: physician and nursing satisfaction. We analyzed the data using quality improvement run charts and control charts. Results: After the start of our initiative, our total number of reactions displayed special cause variation, and a shift in the baseline from a mean of 11.27 HSR per month to 7.526. This change was reflected in the percentage of reactions per doses given which fell from 3.1% to 1.9%. Average percentage of dictated notes per reaction increased from 55% to 64%. Physician attendance per reaction also showed special cause variation with the average increasing from 57% to 90%. PPOA and PPOB use both increased over time. Nursing and Physician satisfaction data will also be presented. Conclusions: Our successful initiative has resulted in HSR management which more closely reflects GLs, including increased physician attendance and notes, and clear consistent written orders detailed on PPO A and B. This has led to decreased HSRs at our site, resulting in decreased resource use and increased patient safety and quality. This has provincial implications as there is the potential to spread this initiative to other BC Cancer sites.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».