American Cancer Society, Washington, DC.
National Cancer Institute, Bethesda, MD.
JCO Clin Cancer Inform. 2020 Jun;4:539-546. doi: 10.1200/CCI.20.00046.
Cancer in the United States accounts for $600 billion in health care costs, lost work time and productivity, reduced quality of life, and premature mortality. The future of oncology delivery must mend disconnects to equitably improve patient outcomes while constraining costs and burden on patients, caregivers, and care teams. Embedding learning health systems into oncology can connect care, engaging patients and providers in fully interoperable data systems that remotely monitor patients; generate predictive and prescriptive analytics to facilitate appropriate, timely referrals; and extend the reach of clinicians beyond clinic walls. Incorporating functional learning systems into the future of oncology and follow-up care requires coordinated national attention to 4 synergistic strategies: (1) galvanize and shape public discourse to develop and adopt these systems, (2) demonstrate their value, (3) test and evaluate their use, and (4) reform policy to incentivize and regulate their use.
在美国，癌症导致的医疗保健成本、工作时间和生产力损失、生活质量下降以及过早死亡等问题耗费了 6000 亿美元。肿瘤学治疗的未来必须弥合脱节，在控制成本和患者负担的同时，公平地改善患者的预后。将学习型医疗系统嵌入肿瘤学领域可以将护理联系起来，让患者和提供者参与到完全可互操作的数据系统中，该系统可以远程监测患者；生成预测和规定性分析，以促进适当、及时的转介；并将临床医生的工作范围扩展到诊所之外。在肿瘤学和后续护理的未来中纳入功能学习系统需要协调国家层面的注意力，以实现以下 4 个协同策略：（1）激发并塑造公众舆论，以开发和采用这些系统；（2）展示其价值；（3）测试和评估其使用；（4）改革政策以激励和规范其使用。
