Modeling Hospital-Acquired Pressure Ulcer Prevalence on Medical-Surgical Units: Nurse Workload, Expertise, and Clinical Processes of Care
Modeling Hospital-Acquired Pressure Ulcer Prevalence on Medical-Surgical Units: Nurse Workload, Expertise, and Clinical Processes of Care
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DOI：
10.1111/1475-6773.12244
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发表时间：
2015-04-01
影响因子：
3.4
通讯作者：
Brown, Diane Storer
中科院分区：
文献类型：
--
作者：
Aydin, Carolyn;Donaldson, Nancy;Brown, Diane Storer
目的本研究模拟了病房/患者特征、护士工作量、护士专业知识和医院获得性压疮 (HAPU) 预防性临床护理流程对 HAPU 病房水平患病率的预测能力。数据来源 2009 年 789 个医疗外科病房（215 家医院）。研究设计使用病房水平数据，使用零膨胀泊松回归对 HAPU 进行建模（由于 HAPU 患病率较低）数据收集/提取方法医院向 CALNOC 登记处提交了 NQF 认可的持续绩效衡量数据。主要发现通过综合考虑病房/患者特征（住院时间较短、有风险的患者较少、男性患者较少）、注册护士工作量（护理时间更长、患者[床位]周转率更高）、注册护士专业知识（经验年数更长、合同人员工作时间更少）和护理流程（更多风险评估）的组合，预测 HAPU 会减少。结论单位/患者特征是有效的 HAPU 预测因子，但通常不可修改。注册护士工作量、护士专业知识和护理流程（风险评估/干预措施）是重要的预测因素，可以通过解决这些因素来减少 HAPU。对于没有经验丰富的全职护士来预防 HAPU 的单位，可能需要支持策略。有必要进行进一步的研究，以在 HAPU 患病率较高的情况下检验这些发现。
ObjectiveThis study modeled the predictive power of unit/patient characteristics, nurse workload, nurse expertise, and hospital-acquired pressure ulcer (HAPU) preventive clinical processes of care on unit-level prevalence of HAPUs.Data SourcesSeven hundred and eighty-nine medical-surgical units (215 hospitals) in 2009.Study DesignUsing unit-level data, HAPUs were modeled with Poisson regression with zero-inflation (due to low prevalence of HAPUs) with significant covariates as predictors.Data Collection/Extraction MethodsHospitals submitted data on NQF endorsed ongoing performance measures to CALNOC registry.Principal FindingsFewer HAPUs were predicted by a combination of unit/patient characteristics (shorter length of stay, fewer patients at-risk, fewer male patients), RN workload (more hours of care, greater patient [bed] turnover), RN expertise (more years of experience, fewer contract staff hours), and processes of care (more risk assessment completed).ConclusionsUnit/patient characteristics were potent HAPU predictors yet generally are not modifiable. RN workload, nurse expertise, and processes of care (risk assessment/interventions) are significant predictors that can be addressed to reduce HAPU. Support strategies may be needed for units where experienced full-time nurses are not available for HAPU prevention. Further research is warranted to test these finding in the context of higher HAPU prevalence.