Cardinal Health Specialty Solutions, Dublin, OH 43017, USA.
Jvion, Inc., Suwanee, GA 30024, USA.
Future Oncol. 2021 Oct;17(29):3797-3807. doi: 10.2217/fon-2021-0302. Epub 2021 Jun 30.
An augmented intelligence tool to predict short-term mortality risk among patients with cancer could help identify those in need of actionable interventions or palliative care services. An algorithm to predict 30-day mortality risk was developed using socioeconomic and clinical data from patients in a large community hematology/oncology practice. Patients were scored weekly; algorithm performance was assessed using dates of death in patients' electronic health records. For patients scored as highest risk for 30-day mortality, the event rate was 4.9% (vs 0.7% in patients scored as low risk; a 7.4-times greater risk). The development and validation of a decision tool to accurately identify patients with cancer who are at risk for short-term mortality is feasible.
一种用于预测癌症患者短期死亡风险的增强型人工智能工具，可以帮助识别那些需要采取行动的干预措施或姑息治疗服务的患者。该算法使用来自大型社区血液学/肿瘤学实践中的患者的社会经济和临床数据来预测 30 天死亡率。患者每周进行评分；通过患者电子健康记录中的死亡日期来评估算法性能。对于评分最高的 30 天死亡率的患者，事件发生率为 4.9%（而评分最低的患者为 0.7%；风险高 7.4 倍）。开发和验证一种决策工具来准确识别有短期死亡风险的癌症患者是可行的。
