Savor Health LLC, New York, NY.
Perelman School of Medicine, Philadelphia, PA.
JCO Clin Cancer Inform. 2024 Jun;8:e2400085. doi: 10.1200/CCI.24.00085.
Nutritional status is an established driver of cancer outcomes, but there is an insufficient workforce of registered dietitians to meet patient needs for nutritional counseling. Artificial intelligence (AI) and machine learning (ML) afford the opportunity to expand access to guideline-based nutritional support.
An AI-based nutrition assistant called Ina was developed on the basis of a learning data set of >100,000 expert-curated interventions, peer-reviewed literature, and clinical guidelines, and provides a conversational text message-based patient interface to guide dietary habits and answer questions. Ina was implemented nationally in partnership with 25 advocacy organizations. Data on demographics, patient-reported outcomes, and utilization were systematically collected.
Between July 2019 and August 2023, 3,310 users from all 50 states registered to use Ina. Users were 73% female; median age was 57 (range, 18-91) years; most common cancer types were genitourinary (22%), breast (21%), gynecologic (19%), GI (14%), and lung (12%). Users were medically complex, with 50% reporting Stage III to IV disease, 37% with metastases, and 50% with 2+ chronic conditions. Nutritional challenges were highly prevalent: 58% had overweight/obese BMIs, 83% reported barriers to good nutrition, and 42% had food allergies/intolerances. Levels of engagement were high: 68% texted questions to Ina; 79% completed surveys; median user retention was 8.8 months; 94% were satisfied with the platform; and 98% found the guidance helpful. In an evaluation of outcomes, 84% used the advice to guide diet; 47% used recommended recipes, 82% felt the program improved quality of life (QoL), and 88% reported improved symptom management.
Implementation of an evidence-based AI virtual dietitian is feasible and is reported by patients to be beneficial on diet, QoL, and symptom management. Ongoing evaluations are assessing impact on other outcomes.
营养状况是癌症结局的既定驱动因素，但注册营养师的劳动力不足，无法满足患者对营养咨询的需求。人工智能 (AI) 和机器学习 (ML) 为扩大基于指南的营养支持提供了机会。
基于超过 10 万个专家策划干预措施、同行评议文献和临床指南的学习数据集，开发了一种名为 Ina 的基于 AI 的营养助手，并提供基于对话短信的患者界面来指导饮食习惯和回答问题。Ina 与 25 个倡导组织合作在全国范围内实施。系统收集人口统计学、患者报告的结果和利用情况的数据。
2019 年 7 月至 2023 年 8 月，来自全美 50 个州的 3310 名用户注册使用 Ina。用户中 73%为女性；中位年龄为 57 岁（范围，18-91 岁）；最常见的癌症类型是泌尿生殖系统（22%）、乳房（21%）、妇科（19%）、胃肠道（14%）和肺部（12%）。用户病情复杂，50%报告疾病处于 III 期至 IV 期，37%有转移，50%有 2 种以上慢性疾病。营养挑战非常普遍：58%的人体重指数超重/肥胖，83%报告存在良好营养的障碍，42%有食物过敏/不耐受。参与度很高：68%向 Ina 发送问题短信；79%完成了调查；用户中位保留时间为 8.8 个月；94%对平台满意；98%认为指导很有帮助。在对结果的评估中，84%使用建议指导饮食；47%使用推荐食谱，82%认为该计划提高了生活质量（QoL），88%报告改善了症状管理。
实施基于证据的 AI 虚拟营养师是可行的，并且患者报告在饮食、生活质量和症状管理方面受益。正在进行的评估正在评估对其他结果的影响。
