University of Iowa Stead Family Children's Hospital, Iowa City, Iowa; University of Iowa Hospitals and Clinics, Iowa City, Iowa.
University of Iowa Stead Family Children's Hospital, Iowa City, Iowa.
Pain Manag Nurs. 2021 Jun;22(3):260-267. doi: 10.1016/j.pmn.2020.10.005. Epub 2020 Dec 4.
Conducting an adequate pain assessment in the Pediatric Intensive Care Unit (PICU) is multifactorial and complex due to the diversity of the population. It is critical that validated pain assessment methods are used appropriately and consistently to aid in evaluation of pain and pain management interventions.
The aim of this evidence-based practice project was to improve pain assessment practices in the PICU through a decision-support algorithm.
DESIGN & METHODS: The Iowa Model-Revised was used to guide the development and implementation of an evidence-based decision algorithm. Pre- and postdata were collected via surveys (nursing knowledge and confidence) and documentation audits (nursing pain assessments). Various implementation strategies were used to facilitate the integration and sustainability of the algorithm in practice.
The majority of survey items showed an increase in nursing knowledge and confidence. Audits of pain assessment documentation displayed an increase in appropriate pain assessment documentation related to a child's communicative ability. However, there is a need for reinfusion related to the documentation of sedation assessments.
The use of an algorithm supported the ability of PICU nurses to critically consider and choose the pain assessment method most appropriate for the patient's condition. The algorithm promotes nursing clinical judgement, prioritizes pain management, and includes patients receiving sedation. The algorithm supports a comprehensive pain assessment in a difficult pediatric patient population. Future research is needed to strengthen and standardize the usage of terms "assume pain present" and "assume pain managed," and to also improve the overall feasibility and effectiveness of the algorithm.
儿科重症监护病房（PICU）的疼痛评估是多方面且复杂的，因为其患者群体具有多样性。因此，至关重要的是，要正确且一致地使用经过验证的疼痛评估方法，以帮助评估疼痛和疼痛管理干预措施。
本循证实践项目旨在通过决策支持算法来改善 PICU 的疼痛评估实践。
爱荷华模型修订版被用于指导基于证据的决策算法的开发和实施。通过问卷调查（护理知识和信心）和文件审核（护理疼痛评估）收集了前后数据。采用了各种实施策略来促进算法在实践中的整合和可持续性。
大多数调查项目都显示护理知识和信心有所提高。疼痛评估文件的审核显示，与儿童沟通能力相关的适当疼痛评估文件有所增加。然而，在镇静评估文件记录方面仍需要进一步改进。
使用算法支持了 PICU 护士批判性地考虑并选择最适合患者病情的疼痛评估方法的能力。该算法促进了护理临床判断，优先考虑疼痛管理，并包括接受镇静治疗的患者。该算法支持对困难儿科患者群体进行全面的疼痛评估。需要进一步的研究来加强和规范术语“假设疼痛存在”和“假设疼痛得到管理”的使用，并提高算法的整体可行性和有效性。
