Ono Takao, Watase Hiroko, Ishihara Takuma, Watase Taketo, Kang Kiho, Iwata Mitsunaga
Department of Emergency Medicine and General Internal Medicine Fujita Health University School of Medicine Toyoake Aichi Japan.
Midori Homon Clinic Nagoya Aichi Japan.
J Gen Fam Med. 2024 Nov 20;26(1):85-91. doi: 10.1002/jgf2.738. eCollection 2025 Jan.
The Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) scale, the Community Assessment Risk Screen (CARS), and the Emergency Admission Risk Likelihood Index (EARLI) are scales that assess the risk of emergency department (ED) visits among home health care patients. This study validated these scales and explored factors that could improve their predictive accuracy among Japanese home health care patients.
This was a single-center retrospective cohort study. The primary outcome of unplanned ED visits was used to assess the validity of the DIVERT scale, CARS, and EARLI. Additionally, we examined whether the addition of patient age and receipt of advance care planning as variables on these assessments could enhance their precision.
Altogether, 40 (17.8%) had at least one ED visit during the 6 months study period. In these patients, the DIVERT scale, CARS, and EARLI of the patients with ≥1 ED visit was superior compared with no ED visit (both < 0.05). The area under the curve (AUC) of the DIVERT scale, CARS, and EARLI were 0.62, 0.59, and 0.60, respectively. Adding patient age and receipt of advance care planning improved the AUC in all three scales.
Our findings suggest that these assessment scales could be applicable to home health care patients in Japan. Furthermore, adding age and receipt of advance care planning as variables was found to enhance the predictive accuracy of the scales.
急诊就诊指标与脆弱性检测（DIVERT）量表、社区评估风险筛查（CARS）和急诊入院风险可能性指数（EARLI）是用于评估居家医疗患者急诊就诊风险的量表。本研究对这些量表进行了验证，并探讨了可提高其在日本居家医疗患者中预测准确性的因素。
这是一项单中心回顾性队列研究。将非计划急诊就诊的主要结局用于评估DIVERT量表、CARS和EARLI的有效性。此外，我们检查了在这些评估中加入患者年龄和接受预先护理计划作为变量是否能提高其精确性。
在6个月的研究期间，共有40例（17.8%）患者至少有一次急诊就诊。在这些患者中，有≥1次急诊就诊的患者的DIVERT量表、CARS和EARLI均优于无急诊就诊的患者（均P<0.05）。DIVERT量表、CARS和EARLI的曲线下面积（AUC）分别为0.62、0.59和0.60。加入患者年龄和接受预先护理计划可提高所有三个量表的AUC。
我们的研究结果表明，这些评估量表可应用于日本的居家医疗患者。此外，发现加入年龄和接受预先护理计划作为变量可提高量表的预测准确性。
