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OpenTrials
Active, Not Recruiting

NCT Number: NCT05318027

ChatBot and Activity Monitoring in Patients Undergoing Chemoradiotherapy

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

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Lung Cancer Digestive System Diseases Digestive System Neoplasms Gastrointestinal Cancer Gastrointestinal Diseases Gastrointestinal Neoplasms Head and Neck Cancer Head and Neck Neoplasms Lung Diseases Lung Neoplasms Neoplasms Neoplasms by Site Respiratory Tract Diseases Respiratory Tract Neoplasms Thoracic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Phase 2

Primary location

Abramson Cancer Center of the University of Pennsylvania

Philadelphia, Pennsylvania, 19104, United States

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Chatbot

Device

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.

Primary outcomes

  1. Number of triage visits

    Time frame: 13 weeks

    Difference between Poisson event rates of triage visits between intervention and control arms

Secondary outcomes

  1. Count of unplanned inpatient hospitalization

    Time frame: 13 weeks

  2. Count of treatment breaks

    Time frame: 13 weeks

  3. Count of emergency department visits

    Time frame: 13 weeks

  4. Quality of Life scores

    Time frame: 13 weeks

Sponsors and collaborators

Lead sponsor

Abramson Cancer Center at Penn Medicine

Other

Registry information

Official study title

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

Important dates

Study start
2023
Primary completion
2026
Study completion
2026
First posted
Apr 8, 2022
Registry last updated
Apr 1, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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