Evaluation of an Automated Pressure Ulcer Risk Assessment Model
Evaluation of an Automated Pressure Ulcer Risk Assessment Model
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DOI：
10.1177/1084822307303566
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发表时间：
2007-06-01
影响因子：
1.1
通讯作者：
Hripcsak, George
中科院分区：
文献类型：
--
作者：
Borlawsky, Tara;Hripcsak, George
及时干预和减少可避免的发病率的关键是早期识别有发生压疮风险的患者。为了能够自动检测此类患者并通知急性护理跨学科提供者，将使用启发式统计方法的过滤器特征模型应用于回顾性患者数据的关系数据库，包括人口统计学、药物和临床访视详情。这些属性作为C4.5决策树归纳算法的输入，用于对患者风险进行分类。使用四重交叉验证来评估所得到的分类模型电子压力溃疡预测（ePUP）的有效性。目前的结果表明，这种朴素的分类算法用于自动化压疮风险评估的应用有限。在ePUP的预测足以用于一般临床使用和改善急性护理环境中的患者安全性之前，以及在从医院到家庭的过渡期间，还需要进行额外的改进。
The key to timely interventions and reducing avoidable incidence is the early identification of patients at risk for developing pressure ulcers. To enable the automatic detection of such patients and inform acute care interdisciplinary providers, a filter feature model using heuristic statistical methods was applied to a relational database of retrospective patient data including demographics, medications, and clinical visit details. These attributes served as input for the C4.5 decision tree induction algorithm, which was used to classify patient risk. The validity of the resulting classification model, Electronic Pressure Ulcer Prediction (ePUP), was assessed using a fourfold cross-validation. The current results show a limited application of such a naive classification algorithm for automating pressure ulcer risk assessments. Additional refinements will be necessary before the predictions of ePUP are sufficient for general clinical use and the improvement of patient safety in acute care settings, and during the transition from hospital to home.