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Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

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Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot:

Akanksha Singh¹, Benjamin Schooley², Nitin Patel³

¹Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.

JMIR Mhealth and Uhealth

|December 14, 2023

Summary

AI chatbots helped patients during COVID-19 by providing information and care referrals. High-risk individuals and those using multiple features found the chatbot most helpful for health system engagement.

Keywords:

COVID-19 chatbot conversational recommender systems design factors health recommender systems patient engagement population health

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Area of Science:

Health Informatics
Artificial Intelligence
Public Health

Background:

The COVID-19 pandemic highlighted the need for reduced human contact and support for healthcare workers.
Conversational agents (chatbots) offer potential solutions for user interaction, easing healthcare burdens and improving satisfaction.

Purpose of the Study:

To evaluate user perceptions of an AI chatbot's helpfulness in response to COVID-19.
To assess the chatbot's role in providing education, symptom reporting, risk assessment, and care referrals.

Main Methods:

A cross-sectional study analyzed 82,222 chats from patients in South Carolina.
Chi-square tests and logistic regression assessed risk factors and perceived helpfulness.
Data collected from April 2020 to April 2022.

Main Results:

Patients over 65, with comorbidities, or recent COVID-19 contact were more likely to find the chatbot helpful.
Users engaging with multiple chatbot features (information, appointments, vaccination) reported higher helpfulness.
High-risk individuals were 1.8 times more likely to find the chat helpful.

Conclusions:

Targeted chatbots offering actionable items can improve early health system contact for communicable disease assessment.
Key design factors include identifying high-risk users and providing relevant, actionable choices.
Chatbots can facilitate symptom assessment and follow-up care, complementing traditional healthcare interactions.