A chatbot-powered G8 screening intervention to facilitate referrals to a comprehensive geriatric assessment among older adults with cancer

由聊天机器人驱动的 G8 筛查干预措施，有助于将患有癌症的老年人转介到进行全面的老年评估

• 批准号: 10179033
• 负责人: Kuang-Yi Wen
• 金额: $ 21.88万
• 依托单位: THOMAS JEFFERSON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10179033
• 关键词: Activities of Daily Living; Address; Adopted; Adult; Aging; Algorithms; American Society of Clinical Oncology; Cancer Patient; Caring; Clinical; Clinical Oncology; Decision Making; Dependence; Education; Educational Materials; Elderly; Enrollment; Geriatric Assessment; Goals; Guidelines; Health Personnel; Heterogeneity; Incidence; International; Intervention; Interview; Knowledge; Language; Life; Malignant Neoplasms; Measures; Mediating; Medical Care Team; Modeling; Morbidity - disease rate; National Comprehensive Cancer Network; Nurses; Oncologist; Oncology; Outcome; Participant; Patient Noncompliance; Patient Self-Report; Patients; Polypharmacy; Predictive Value; Process; Questionnaires; Readiness; Recommendation; Reporting; Resources; Schedule; Screening procedure; Selection for Treatments; Self Assessment; Societies; Specific qualifier value; Structure; Subgroup; Syndrome; System; Technology; Testing; Text Messaging; Time; Training; Treatment outcome; Triage; Work; acceptability and feasibility; age group; brief screening; cancer diagnosis; cancer therapy; care coordination; chatbot; chemotherapy; clinical practice; communication behavior; comorbidity; data sharing; design; digital health; evidence base; experience; follow-up; frailty; health belief; health communication; health information technology; human old age (65+); implementation intervention; improved; innovation; older patient; patient engagement; patient subsets; prototype; remote consent; risk perception; satisfaction; screening; therapy design; tool; treatment optimization; uptake; usability

The majority of cancer diagnoses and morbidity occurs in patients age 65 and over. This age group has increased incidence of by multiple co-morbid conditions, geriatric syndromes, dependence in instrumental activities and activities of daily living, and polypharmacy reflecting the heterogeneity of aging and influence the treatment outcomes for older adults. Clinical guidelines recommend the routine use of a Comprehensive Geriatric Assessment (CGA) for older cancer patients with the potentials to identify and optimize nononcologic issues and alter chemotherapy decision and improve treatment tolerance. However, a CGA is time intensive and it is not feasible for every older adult with cancer to be seen by a geriatrician given the shortage of geriatricians. G8, an eight-item questionnaire, has been recommended as a brief screening tool which is usually administered by a health care provider with good sensitivity to identify patients who are most likely to be benefit from a CGA. However, the implementation of the G8 in routine oncology clinical practice has mixed results with sub optimal uptake due to clinical and system barriers. To fill the void, we propose using a patient- mediated implementation approach, specifically adopting the Chatbot technology to delivering a structured set of G8 screening questions that can simulate the content experienced by real-life conversation such as with a health care provider. Our proposed Chatbot application, JeffSeniorChat, will facilitate G8 screening with supportive and educational content to explain the purpose and benefit of the G8 tool, each question with examples and probes to help with recall, and next steps after the G8 assessment is completed and how the results might impact their cancer treatments. Guided by the Health Belief Model, health communication best practices and our preliminary formative work, JeffSeniorChat will be iteratively developed and refined through a rapid prototyping process using patient-stakeholder inputs and plain-language evidence-based content and usability testing to finalize the intervention. We will examine the feasibility and acceptability of the JeffSeniorChat intervention targeting G8 self-assessment completion and CGA attendance in 150 older adult with cancer. Overall G8 score will be automatically calculated by the JeffSeniorChat backend algorithm and patients with G8 scores ≤ 14 will be prompted to schedule a CGA at Jefferson’s Senior Adult Oncology Center. Feasibility will be determined by pre-specified enrollment and G8 completion rate. Acceptability will be measured by participant reported intervention credibility and satisfaction. Among patients with G8 scores ≤ 14 referred to a CGA, exploratory outcomes will examine CGA attendance compliance, predictive value of the JeffSeniorChat collected G8 score with the final frailty designation determined by the CGA, and perceived barriers among CGA non-adherent patients via follow-up interviews. Streamlining G8-triage process to a CGA through the Chatbot-enabled patient self-reported assessment and intervention should improve clinical efficiency and improve CGA attendance rate, ultimately optimizing treatment selection and outcomes.

大多数癌症的诊断和发病发生在65岁及以上的患者中。这个年龄段的人