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Grant Details

Grant Number: 5R21CA258200-02 Interpret this number
Primary Investigator: Wen, Kuang-Yi
Organization: Thomas Jefferson University
Project Title: A Chatbot-Powered G8 Screening Intervention to Facilitate Referrals to a Comprehensive Geriatric Assessment Among Older Adults with Cancer
Fiscal Year: 2022


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.


Process evaluation of a G8 screening tool implementation in an outpatient oncology center.
Authors: Swartz K. , Chapman A. , Zhan T. , Wen K.Y. .
Source: Journal of geriatric oncology, 2024 Jan; 15(1), p. 101605.
EPub date: 2023-08-24.
PMID: 37633778
Related Citations

The association of the G8 questionnaire with treatment side effects and unscheduled care among older adults with breast cancer: A retrospective cohort study.
Authors: Gomaa S. , Cappelli L. , Swartz K. , Zhan T. , Chapman A. , Lopez A.M. , Lombardo J. , Wen K.Y. .
Source: Journal of geriatric oncology, 2023 Sep; 14(7), p. 101566.
EPub date: 2023-06-29.
PMID: 37392563
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