School of Health Sciences, University of Southampton, Southampton, Hampshire, UK
University of Exeter Medical School, University of Exeter, Exeter, Devon, UK.
BMJ Qual Saf. 2021 Jan;30(1):7-16. doi: 10.1136/bmjqs-2019-010569. Epub 2020 Mar 26.
Planning numbers of nursing staff allocated to each hospital ward (the 'staffing establishment') is challenging because both demand for and supply of staff vary. Having low numbers of registered nurses working on a shift is associated with worse quality of care and adverse patient outcomes, including higher risk of patient safety incidents. Most nurse staffing tools recommend setting staffing levels at the average needed but modelling studies suggest that this may not lead to optimal levels.
Using computer simulation to estimate the costs and understaffing/overstaffing rates delivered/caused by different approaches to setting staffing establishments.
We used patient and roster data from 81 inpatient wards in four English hospital Trusts to develop a simulation of nurse staffing. Outcome measures were understaffed/overstaffed patient shifts and the cost per patient-day. We compared staffing establishments based on average demand with higher and lower baseline levels, using an evidence-based tool to assess daily demand and to guide flexible staff redeployments and temporary staffing hires to make up any shortfalls.
When baseline staffing was set to meet the average demand, 32% of patient shifts were understaffed by more than 15% after redeployment and hiring from a limited pool of temporary staff. Higher baseline staffing reduced understaffing rates to 21% of patient shifts. Flexible staffing reduced both overstaffing and understaffing but when used with low staffing establishments, the risk of critical understaffing was high, unless temporary staff were unlimited, which was associated with high costs.
While it is common practice to base staffing establishments on average demand, our results suggest that this may lead to more understaffing than setting establishments at higher levels. Flexible staffing, while an important adjunct to the baseline staffing, was most effective at avoiding understaffing when high numbers of permanent staff were employed. Low staffing establishments with flexible staffing saved money because shifts were unfilled rather than due to efficiencies. Thus, employing low numbers of permanent staff (and relying on temporary staff and redeployments) risks quality of care and patient safety.
规划分配给每个医院病房的护理人员数量（即“人员配置”）具有挑战性，因为人员的需求和供应都在变化。在轮班时，注册护士人数较少与护理质量下降和患者预后不良有关，包括患者安全事件风险增加。大多数护士人员配备工具建议按照平均需求量设定人员配备水平，但建模研究表明，这可能无法达到最佳水平。
使用计算机模拟来估计不同人员配置方法设定人员编制所产生的成本和人员不足/人员过剩率。
我们使用来自英格兰四家医院信托机构的 81 个住院病房的患者和人员名单数据来开发护士人员配置模拟。结果衡量标准是人员不足/人员过剩的患者轮班以及每位患者每天的成本。我们比较了基于平均需求的人员编制与较高和较低的基线水平，使用基于证据的工具来评估每日需求，并指导灵活的人员重新部署和临时人员招聘，以弥补任何人员短缺。
当基线人员编制设定为满足平均需求时，在进行重新部署和从有限的临时人员库中招聘人员后，有 32%的患者轮班人员不足 15%。较高的基线人员编制将人员不足率降低至 21%的患者轮班。灵活的人员配置减少了人员过剩和人员不足，但当与低人员编制一起使用时，如果临时人员数量不受限制，那么人员严重不足的风险很高，这会导致成本增加。
虽然基于平均需求设定人员编制是常见做法，但我们的结果表明，这可能会导致比设定较高水平的人员编制更多的人员不足。虽然灵活的人员配置是人员编制的重要辅助手段，但在雇用大量固定员工时，它最能有效地避免人员不足。采用灵活人员编制的低人员编制节省了成本，因为空缺的班次而不是由于效率提高而导致人员不足。因此，雇用少量固定员工（并依赖临时员工和重新部署）会影响护理质量和患者安全。
