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Enregistrement W2322421614 · doi:10.1097/01.sih.0000441489.48756.95

Board 224 - Program Innovations Abstract Improving Outcomes in Perioperative Nursing - Improving Curriculum, Meeting Staffing Shortages and Building Innovative Partnerships (Submission #485)

2013· article· en· W2322421614 sur OpenAlexaboutno aff
Nichole Oocumma, Richard Latham, Jason Zigmont

Notice bibliographique

RevueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2013
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Workforce Issues
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPerioperativePerioperative nursingStaffingNursing shortageCurriculumSpecialtyMedicineNursingMedical educationGeneral partnershipNurse educationBusinessPsychologyFamily medicinePedagogySurgery

Résumé

récupéré en direct d'OpenAlex

Introduction/Background The professional literature is well documented with citations that predict a future perioperative nursing shortage not only in the United States, but throughout the world. Only a small percentage of all nurses are perioperative and it is estimated that nearly 20% of those employed will retire in the next five years. This shortage is compounded by the absence of a perioperative curriculum in most nursing programs. Because of the amount of information included in both ADN and BSN programs, courses in clinical specialty areas are offered less often. In addition, clinical rotations in perioperative settings have been eliminated form most baccalaureate nursing curricula. This absence of perioperative courses in nursing programs also reduces new graduate interests in this specialty area and awareness of employment opportunities in the operating room environment. Finally, the cost of recruiting, hiring and orienting nurses to a medical specialty is difficult to calculate. According to the literature, the cost is estimated from $59-64,000. The difficulty includes application, recruitment, interviewing and hiring process. Further costs are associated with the extensive length and experience requirement to orient a new perioperative nurse to be a productive member of the surgical team. In order to proactively plan for this shortage, a private University’s Undergraduate Nursing Program and a large, mid-western Hospital system entered into an innovative partnership. Assembled in April 2012 to explore, develop and implement a perioperative course, the team included faculty from Otterbein University and staff from three OhioHealth hospital campuses, Organizational Development and Experiential Learning. Traditionally, undergraduate nursing education has not emphasized process or experiential learning groups as a way to facilitate students learning the skills required to understand group processes and to function effectively in teams. These learning environments are critical for successful perioperative staff. In response, a curriculum applying experiential learning theory and using simulation instead of traditional learning Methods was designed. The hands-on course, offered in a condensed semester called a J-term, incorporated online activities, lecture, simulation and clinical experiences in a small group setting. Methods The innovative elective course developed by the cross-disciplinary team resulted in positive outcomes. The course was added to the undergraduate nursing curriculum for a second J-term in 2014 and a full semester in 2015 at the University. Additionally, the University intends to use this planning model to pilot other elective courses for alternate specialty areas. Most notable outcome was OhioHealth hired three of the four senior nursing students completing the elective course as perioperative nurses. Hiring these nursing students reduced the human resource costs of recruiting and hiring specialty nurses. In each case, the hiring managers indicated a reduced orientation length of two months for these new hires. This reduction in orientation time is equivalent to approximately $30,000. Further outcomes include opportunities to offer senior practicum and nursing electives in various specialty areas within the hospital system and improved communication among and within perioperative areas across the participating hospital campuses. Results: Conclusion The collaboration between multiple OhioHealth hospital campuses, experiential learning, organizational development and academic partnership staff was new to the system. The success of the collaboration demonstrates the need, opportunity and quality of further cross-disciplinary partnerships, not only in management of academic opportunities but in creatively meeting staffing needs. This model can provide a system approach to ensure the future of staffing for our operating rooms as well as serve as a model to reduce orientation time in specialty areas where orientation is often extensive. References 1. Kinyon, J., Keith, C. B., Pistole, M. C. 2009. A collaborative approach to group experiential learning with undergraduate nursing students. Journal of Nursing Education. 48.3:165-6. 2. Lisko, S. A., O’Dell, V.
2010. Integration of theory and practice: experiential learning theory and nursing education. Nursing Education Perspectives. 31.2:106-8. 3. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall. 4. Bambini, D., Washburn, J., Perkins, R. 2009. Outcomes of clinical simulation for novice nursing students: communication, confidence, clinical judgment. Nursing Education Perspectives. 30.2: 79-82. 5. Pugsley, K.E., Clayton, L. H. (2003) Traditional lecture or experiential learning: Changing student attitudes. Journal of Nursing Education 42.11:520-3. 6. Scherer, Y.K., Bruce, S.A., Graves, B.T., Erdley, W. S. (DATE). Acute care nurse practitioner education: enhancing performance through the use of clinical simulation. Buffalo, The State University of New York, School of Nursing, Buffalo, NY. CONFIRM CITATION. 7. Holmes, S.P. 2004. Implementing a perioperative nursing elective in a baccalaureate curriculum. AORN Jour. 80:5. 902-910. 8. Happell, B. 2000. Student interest in perioperative nursing practice as a career. AORN Journ 71. 600-605. 9. Kinyon, J., Keith, C.B., Pistole, M.C. 2009. A collaborative approach to group experiential learning with undergraduate nursing students. Jour of Nurs Education 48.3:165-6. 10. Bambini, D. Washburn, J., Perkins, R. (2009). Outcomes of clinical simulation for novice nursing students: Communication, confidence and clinical judgment. Nursing Educ Perspectives 30.2: 79-82. 11. Pugsley, K.E. and Clayton, L.H. (2003). Traditional lecture or experiential learning: changing student attitudes. Jour of Nurs Educ 42.11:520-523. 12. Mullen, L. and Byrd, D. (2013). Using simulation training to improve perioperative patient safety. AORN Jour. 97.4: 419-427. 13. Messina, B.M., Ianniciello, J.M. and Escallier, L.A. 2011. Opening the doors to the OR: Providing students with perioperative clinical experiences. AORN Jour 94.2: 180-188. 14. New Zealand Nurses Organisation. 2010. Shortage of perioperative nurses predicted. Kai Tiaki Nursing New Zealand. 16.9: 9. 15. Storen, I. and Hanssen, I. 2011. Why do nurses choose to work in the perioperative field? AORN Jour 94.6: 578-589 16. Wilson, G. 2012. Redesigning OR Orientation. AORN Journal. 95.4: 453-462. 17. Claridge, S. 2012. Reintroducing nursing students to the perioperative environment. The Dissector. 40.3: 40-42. 18. Willemsen-McBride, T. 2010. Preceptorship planning is essential to perioperative nursing retention: Matching teaching and learning styles. Canadian Operating Room Nursing Journal. 28:1. 10-11, 16, 18-21. Disclosures None.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,324
Score d'incertitude au seuil0,965

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,013
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0040,002
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,3240,101

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.

Tête enseignante Opus0,076
Tête enseignante GPT0,464
Écart entre enseignants0,388 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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