ChatBot and Activity Monitoring in Patients Undergoing Chemoradiotherapy

Study Overview
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Brief Summary
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Evaluate the feasibility of using a chatbot combined with continuous activity monitoring to proactively identify, appropriately triage and help manage patients' symptoms during cancer treatment Determine whether such an early outpatient clinic-based intervention can decrease rates of excess triage visits Correlate changes in activity and early symptom management to emergency department visits, unplanned inpatient hospitalizations and treatment breaks

Official Title
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Use of Natural Language Processing ChatBot and Automated Continuous Activity Monitoring Via Mobile Phones for Early Detection and Management of Symptoms in Patients Undergoing Cancer Treatment

Conditions
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Lung Cancer, Gastrointestinal Cancer, Head and Neck Cancer

Intervention / Treatment
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* Device: ChatBot


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Adults (age >18 years) with a diagnosis of a head and neck, lung, gastrointestinal cancer, that are receiving concurrent chemotherapy and radiation treatment. Possession of a mobile device that can receive SMS texts and can deliver FitBit data wirelessly Ability read and respond in English Ability to provide informed consent to participate in the study Exclusion Criteria: Patients who are bed bound at baseline (ECOG 4) Patients who rely on a wheelchair for ambulation

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Other
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Activity Monitoring and ChatBot<br>Patients will receive standard of care chemotherapy and radiation therapy regimens, activity monitoring and utilize a ChatBot | Device: ChatBot<br>* The automated chatbot will check in with the patient on two pre-specified days between scheduled outpatient visits. The chatbot will follow pre-specified symptom algorithms and classify symptoms as requiring high, intermediate and low risk follow ups. High risk symptoms will trigger a same day nursing/physician visit or telemedicine call/video. Intermediate risk symptoms will trigger a nursing triage visit or telemedicine call/video on the next day or treatment day. Low risk symptoms will notify the treating physician to address the symptoms at the next scheduled on treatment visit (OTV). If adjustments are needed in the chat bot triage algorithms, they will be updated in real time to decrease risk for adverse patient events.<br>|
| No Intervention: Activity Monitoring without ChatBot<br>Patients will receive standard of care chemotherapy and radiation therapy regimens, activity monitoring alone | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of triage visits | Difference between Poisson event rates of triage visits between intervention and control arms | 13 weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Count of unplanned inpatient hospitalization |  | 13 weeks | 
| Count of treatment breaks |  | 13 weeks | 
| Count of emergency department visits |  | 13 weeks | 
| Quality of Life scores |  | 13 weeks |