ASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health Workers

要旨

Community health workers (CHWs) provide last-mile healthcare services but face challenges due to limited medical knowledge and training. This paper describes the design, deployment, and evaluation of ASHABot, an LLM-powered, experts-in-the-loop, WhatsApp-based chatbot to address the information needs of CHWs in India. Through interviews with CHWs and their supervisors and log analysis, we examine factors affecting their engagement with ASHABot, and ASHABot's role in addressing CHWs' informational needs. We found that ASHABot provided a private channel for CHWs to ask rudimentary and sensitive questions they hesitated to ask supervisors. CHWs trusted the information they received on ASHABot and treated it as an authoritative resource. CHWs' supervisors expanded their knowledge by contributing answers to questions ASHABot failed to answer, but were concerned about demands on their workload and increased accountability. We emphasize positioning LLMs as supplemental fallible resources within the community healthcare ecosystem, instead of as replacements for supervisor support.

著者
Pragnya Ramjee
Microsoft Research, Bangalore, India
Mehak Chhokar
Khushi Baby, Udaipur, India
Bhuvan Sachdeva
Microsoft Research India, Bangalore, India
Mahendra Meena
Khushi Baby, Udaipur, India
Hamid Abdullah
Khushi Baby, udaipur, India
Aditya Vashistha
Cornell University, Ithaca, New York, United States
Ruchit Nagar
Khushi Baby, Udaipur, India
Mohit Jain
Microsoft Research, Bangalore, Karnataka, India
DOI

10.1145/3706598.3713680

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713680

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Medical Contexts

G316+G317
7 件の発表
2025-04-30 23:10:00
2025-05-01 00:40:00
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