Harnessing ward-level administrative data and expert knowledge to improve staffing decisions: A multi-method case study.
diagnosis-related groups
major diagnostic categories
nursing
patient churn
ratios
resource intensity
staffing
work intensification
workforce
workloads
Journal
Journal of advanced nursing
ISSN: 1365-2648
Titre abrégé: J Adv Nurs
Pays: England
ID NLM: 7609811
Informations de publication
Date de publication:
Jan 2020
Jan 2020
Historique:
received:
29
04
2019
revised:
11
08
2019
accepted:
12
09
2019
pubmed:
1
10
2019
medline:
22
9
2020
entrez:
1
10
2019
Statut:
ppublish
Résumé
The aim of this study was to investigate the impact of changes to bed configuration and patient mix on nurses' workload in a single ward. Multi-method case study. The study was undertaken in an acute 28-bed ward in a tertiary referral public hospital in Queensland, Australia. Ward-level administrative data were obtained for a 2-year period, 12 months before bed configuration changes in October 2015 and 12 months after. These data included patient activity (bed occupancy, transfers, length of stay and casemix) and nurse staffing (budgeted and actual staffing levels, employment status and skillmix). Semi-structured interviews were conducted with ward nurses (N = 17) to explore the impact of the bed configuration changes on their workload. Administrative data showed that the bed configuration changes resulted in more complex and dependent patients, increased patient transfers and greater variability in casemix. The interview data found these changes to patient complexity and activity intensified workloads, which were further increased by staffing decisions that resulted in greater reliance on temporary staff. Hospitals already possess the data and expert knowledge needed to improve staffing and bed management decisions without the need for additional, costly workload systems. Determining appropriate nurse staffing in light of the complexities and variation of patient needs at the ward level remains a challenge. This study identified increases in patient complexity, dependency, variability and churn that increased workload. Staffing grew but hidden factors associated with temporary staffing and skillmix further intensified nurses' workload. Harnessing existing data and the expertise and experience of nursing unit managers (NUMs) would help staff wards more efficiently and effectively, providing reasonable workloads and appropriate skillmix that can enhance the safety and quality of patient care. To facilitate this, NUMs need access to accurate, timely, data and authority in staffing and bed management decisions. 目的: 本研究旨在调查病房内改变床位配置和病人组合对护士工作量的影响。 设计: 多方法案例研究。 方法: 本研究在澳大利亚昆士兰一家三级转诊公立医院的28床急症病房进行。收集病房管理数据的时间长达2年,即2015年10月床位配置改变之前和之后的12个月。数据包括病人活动(床位占用、转移、住院时间延长和病例组合)和护士人员配备(预算和实际人员配备、就业状况和技能组合)。我们还对病房护士进行了半结构式访谈(N = 17),以探讨床位配置变化对其工作量的影响。 结果: 管理性数据显示,床位配置变化导致更多的复杂和依赖的病人、病人转诊增加、病人在casemix的变化更大。访谈数据发现这些变化增加了病人的复杂性和工作量,而工作人员的决定又进一步加重了工作量,导致病人更加依赖临时工作人员。 结论: 医院已经拥有改善住院和病床管理决策所需的数据和专业知识,而不需要额外的昂贵的工作量系统。 影响: 根据病人在病房级的复杂性和多样性需求来决定合适的护士配置仍是一个挑战。研究发现患者的复杂性、依赖性、可变性和搅动性增加了工作量。尽管工作人员增加,但临时职工和技能组合相关的隐性因素也加重了护士的工作量。利用现有的数据和护理部门经理(NUMs)的专业知识和经验能够帮助病房工作人员高效工作,提供合理的工作量和适当的技能组合,从而提高病人护理的安全性和质量。为了促进这一点,护理部门需要在人员配备和床位管理决策方面获得准确、及时的数据和权威。.
Autres résumés
Type: Publisher
(chi)
目的: 本研究旨在调查病房内改变床位配置和病人组合对护士工作量的影响。 设计: 多方法案例研究。 方法: 本研究在澳大利亚昆士兰一家三级转诊公立医院的28床急症病房进行。收集病房管理数据的时间长达2年,即2015年10月床位配置改变之前和之后的12个月。数据包括病人活动(床位占用、转移、住院时间延长和病例组合)和护士人员配备(预算和实际人员配备、就业状况和技能组合)。我们还对病房护士进行了半结构式访谈(N = 17),以探讨床位配置变化对其工作量的影响。 结果: 管理性数据显示,床位配置变化导致更多的复杂和依赖的病人、病人转诊增加、病人在casemix的变化更大。访谈数据发现这些变化增加了病人的复杂性和工作量,而工作人员的决定又进一步加重了工作量,导致病人更加依赖临时工作人员。 结论: 医院已经拥有改善住院和病床管理决策所需的数据和专业知识,而不需要额外的昂贵的工作量系统。 影响: 根据病人在病房级的复杂性和多样性需求来决定合适的护士配置仍是一个挑战。研究发现患者的复杂性、依赖性、可变性和搅动性增加了工作量。尽管工作人员增加,但临时职工和技能组合相关的隐性因素也加重了护士的工作量。利用现有的数据和护理部门经理(NUMs)的专业知识和经验能够帮助病房工作人员高效工作,提供合理的工作量和适当的技能组合,从而提高病人护理的安全性和质量。为了促进这一点,护理部门需要在人员配备和床位管理决策方面获得准确、及时的数据和权威。.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
287-296Subventions
Organisme : Gold Coast University Hospital
Informations de copyright
© 2019 John Wiley & Sons Ltd.
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