Kang Youjeong, McHugh Matthew D, Chittams Jesse, Bowles Kathryn H
Author Affiliations: University of Pennsylvania School of Nursing, Philadelphia.
Comput Inform Nurs. 2016 Apr;34(4):175-82. doi: 10.1097/CIN.0000000000000223.
Heart failure is a complex condition with a significant impact on patients' lives. A few studies have identified risk factors associated with rehospitalization among telehomecare patients with heart failure using logistic regression or survival analysis models. To date, there are no published studies that have used data mining techniques to detect associations with rehospitalizations among telehomecare patients with heart failure. This study is a secondary analysis of the home healthcare electronic medical record called the Outcome and Assessment Information Set-C for 552 telemonitored heart failure patients. Bivariate analyses using SAS and a decision tree technique using Waikato Environment for Knowledge Analysis were used. From the decision tree technique, the presence of skin issues was identified as the top predictor of rehospitalization that could be identified during the start of care assessment, followed by patient's living situation, patient's overall health status, severe pain experiences, frequency of activity-limiting pain, and total number of anticipated therapy visits combined. Examining risk factors for rehospitalization from the Outcome and Assessment Information Set-C database using a decision tree approach among a cohort of telehomecare patients provided a broad understanding of the characteristics of patients who are appropriate for the use of telehomecare or who need additional supports.
心力衰竭是一种复杂的病症，对患者的生活有重大影响。一些研究已经使用逻辑回归或生存分析模型，确定了心力衰竭远程家庭护理患者再次住院的相关风险因素。迄今为止，尚无已发表的研究使用数据挖掘技术来检测心力衰竭远程家庭护理患者再次住院的关联因素。本研究是对名为结局与评估信息集-C的家庭医疗电子病历进行的二次分析，该病历涉及552名接受远程监测的心力衰竭患者。使用SAS进行了双变量分析，并使用怀卡托知识分析环境的决策树技术。从决策树技术中可以看出，皮肤问题的存在被确定为在护理评估开始时能够识别的再次住院的首要预测因素，其次是患者的生活状况、患者的整体健康状况、严重疼痛经历、活动受限疼痛的频率以及预期治疗就诊的总数。在一组远程家庭护理患者中，使用决策树方法从结局与评估信息集-C数据库中检查再次住院的风险因素，有助于广泛了解适合使用远程家庭护理或需要额外支持的患者的特征。
