Graduate School of Comprehensive Human Sciences, University of Tsukuba, Ibaraki, Japan.
Health Services Research and Development Center, University of Tsukuba, Ibaraki, Japan.
BMC Prim Care. 2022 May 26;23(1):132. doi: 10.1186/s12875-022-01742-7.
The demand for home healthcare is increasing in Japan, and a 24-hour on-call system could be a burden for primary care physicians. Identifying high-risk patients who need frequent emergency house calls could help physicians prepare and allocate medical resources. The aim of the present study was to develop a risk score to predict the frequent emergency house calls in patients who receive regular home visits.
We conducted a retrospective cohort study with linked medical and long-term care claims data from two Japanese cities. Participants were ≥ 65 years of age and had newly started regular home visits between July 2014 and March 2018 in Tsukuba city and between July 2012 and March 2017 in Kashiwa city. We followed up with patients a year after they began the regular home visits or until the month following the end of the regular home visits if this was completed within 1 year. We calculated the average number of emergency house calls per month by dividing the total number of emergency house calls by the number of months that each person received regular home visits (1-13 months). The primary outcome was the "frequent" emergency house calls, defined as its use once per month or more, on average, during the observation period. We used the least absolute shrinkage and selection operator (LASSO) logistic regression with 10-fold cross-validation to build the model from 19 candidate variables. The predictive performance was assessed with the area under the curve (AUC).
Among 4888 eligible patients, frequent emergency house calls were observed in 13.0% of participants (634/4888). The risk score included three variables with the following point assignments: home oxygen therapy (3 points); long-term care need level 4-5 (1 point); cancer (4 points). While the AUC of a model that included all candidate variables was 0.734, the AUC of the 3-risk score model was 0.707, suggesting good discrimination.
This easy-to-use risk score would be useful for assessing high-risk patients and would allow the burden on primary care physicians to be reduced through measures such as clustering high-risk patients in well-equipped medical facilities.
在日本，对家庭医疗保健的需求正在增加，24 小时随叫随到的系统可能会给初级保健医生带来负担。确定需要频繁急诊上门的高风险患者，有助于医生做好准备并分配医疗资源。本研究旨在开发一种风险评分，以预测接受定期上门访视的患者中频繁急诊上门的情况。
我们进行了一项回顾性队列研究，使用了来自日本两个城市的医疗和长期护理索赔数据进行了关联。参与者年龄均≥65 岁，在 2014 年 7 月至 2018 年 3 月期间在筑波市和 2012 年 7 月至 2017 年 3 月期间在柏市新开始定期上门访视。我们对患者进行了为期一年的随访，或者在定期上门访视结束后的一个月内进行随访，如果在一年内完成了定期上门访视。我们通过将总急诊上门次数除以每个人接受定期上门访视的月数（1-13 个月）来计算每月平均急诊上门次数。主要结局是“频繁”急诊上门，定义为在观察期间平均每月使用一次或更多次。我们使用 10 折交叉验证的最小绝对收缩和选择算子（LASSO）逻辑回归从 19 个候选变量中构建模型。使用曲线下面积（AUC）评估预测性能。
在 4888 名符合条件的患者中，有 13.0%的患者（634/4888）出现了频繁的急诊上门。风险评分包括三个变量，其赋值如下：家庭氧疗（3 分）；长期护理需求等级 4-5（1 分）；癌症（4 分）。虽然包含所有候选变量的模型的 AUC 为 0.734，但 3 分风险评分模型的 AUC 为 0.707，表明具有良好的区分度。
这种易于使用的风险评分将有助于评估高风险患者，并通过将高风险患者集中在设备齐全的医疗机构等措施，减轻初级保健医生的负担。
