No more unimplementable nurse workforce planning

IF 1.2 4区 医学 Q3 NURSING Contemporary Nurse Pub Date : 2022-03-20 DOI:10.1080/10376178.2022.2056067
C. Park, M. Kabak, H. Kim, Sangmin Lee, G. Cummings
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引用次数: 2

Abstract

Objective: This paper aims to spur thought-provoking practical debates on current nurse workforce staffing and scheduling systems in relation to a critical review of Ang and colleagues’ (2018) article entitled “Nurse workforce scheduling in the emergency department: A sequential decision support system considering multiple objectives.” Design: Discussion paper on a practical discourse in connection with the aforementioned published article. Discussion: Mathematical Programming (optimisation) (MP)-based nursing research has been published for nearly thirty years almost exclusively in industrial engineering or health business administration journals, demonstrating a widening gap between nursing research and practice. Nurse scientists’ knowledge and skill of MP is insufficient, as are their interdisciplinary collaborations, setting back the advancement of nursing science. Above all, nurse scientists skilled in decision science are desperately needed for that analytic intellection which is rooted in the ‘intrinsic nature and value of nursing care.’ It is imperative that nurse scientists be well-prepared for the new age of the Fourth Industrial Revolution through both an education in MP and interdisciplinary collaboration with decision science experts in order to prevent potential stereotyped MP-based algorithm-driven destructive influences. Conclusions: The current global nursing shortage makes optimal nursing workforce staffing and scheduling more important. MP helps nurse executives and leaders to ensure the most efficient number of nurses with the most effective composition of nurse staffing at the right time for a reasonable cost. Nurse scientists urgently need to produce a new nursing knowledge base that is directly implementable in nursing practice. Impact Statement: Nurse scientists should take the leading role in producing the mathematical programming-integrated knowledge base that is directly implementable in practice.
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不再有无法实施的护士人力规划
目的:本文旨在通过对Ang及其同事(2018)题为“急诊科护士人力调度:考虑多目标的顺序决策支持系统”的文章的批判性回顾,引发有关当前护士人力配备和调度系统的发人深思的实践辩论。设计:与上述已发表的文章有关的一篇实际论述的讨论论文。讨论:基于数学规划(优化)(MP)的护理研究已经发表了近30年,几乎全部发表在工业工程或卫生工商管理期刊上,这表明护理研究与实践之间的差距越来越大。护理科学家对MP的知识和技能不足,他们的跨学科合作也不足,阻碍了护理科学的发展。最重要的是,精通决策科学的护士科学家迫切需要这种根植于护理的内在本质和价值的分析性思考。“护士科学家必须通过MP教育和与决策科学专家的跨学科合作,为第四次工业革命的新时代做好充分准备,以防止潜在的刻板的基于MP的算法驱动的破坏性影响。”结论:当前全球护理人员短缺使得优化护理人员配备和调度变得更加重要。MP帮助护士管理人员和领导确保在适当的时间以合理的成本获得最有效的护士人数和最有效的护士人员组成。护理科学家迫切需要产生一种新的护理知识库,可以直接应用于护理实践。影响陈述:护理科学家应该在生产数学规划方面发挥主导作用,即在实践中直接实施的集成知识库。
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来源期刊
Contemporary Nurse
Contemporary Nurse 医学-护理
CiteScore
2.00
自引率
6.20%
发文量
38
审稿时长
6-12 weeks
期刊介绍: Contemporary Nurse is an international peer-reviewed journal designed to increase nursing skills, knowledge and communication, assist in professional development and to enhance educational standards by publishing stimulating, informative and useful articles on a range of issues influencing professional nursing research, teaching and practice. Contemporary Nurse is a forum for nursing educators, researchers and professionals who require high-quality, peer-reviewed research on emerging research fronts, perspectives and protocols, community and family health, cross-cultural research, recruitment, retention, education, training and practitioner perspectives. Contemporary Nurse publishes original research articles, reviews and discussion papers.
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