Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model Article Swipe
Xuhai Xu
,
Bingsheng Yao
,
Ziqi Yang
,
Shao Zhang
,
Ethan M. Rogers
,
Stephen Intille
,
Nawar Shara
,
Guodong Gao
,
Dakuo Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1609/aaaiss.v4i1.31785
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1609/aaaiss.v4i1.31785
Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, information loss, and process inefficiencies. One promising solution to facilitate patient-provider communication is to leverage large language models (LLMs) with their powerful natural conversation and summarization capability. However, there is a limited understanding of LLMs' role during the communication. We first conducted two interview studies with both older adults (N=10) and healthcare providers (N=9) to understand their needs and opportunities for LLMs in patient-provider asynchronous communication. Based on the insights, we built an LLM-powered communication system, Talk2Care, and designed interactive components for both groups: (1) For older adults, we leveraged the convenience and accessibility of voice assistants (VAs) and built an LLM-powered conversational interface for effective information collection. (2) For health providers, we built an LLM-based dashboard to summarize and present important health information based on older adults' conversations with the VA. We further conducted two user studies with older adults and providers to evaluate the usability of the system. The results showed that Talk2Care could facilitate the communication process, enrich the health information collected from older adults, and considerably save providers' efforts and time. We envision our work as an initial exploration of LLMs' capability in the intersection of healthcare and interpersonal communication.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaaiss.v4i1.31785
- https://ojs.aaai.org/index.php/AAAI-SS/article/download/31785/33952
- OA Status
- diamond
- Cited By
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4404187989Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1609/aaaiss.v4i1.31785Digital Object Identifier
- Title
-
Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-ModelWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-11-08Full publication date if available
- Authors
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Xuhai Xu, Bingsheng Yao, Ziqi Yang, Shao Zhang, Ethan M. Rogers, Stephen Intille, Nawar Shara, Guodong Gao, Dakuo WangList of authors in order
- Landing page
-
https://doi.org/10.1609/aaaiss.v4i1.31785Publisher landing page
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https://ojs.aaai.org/index.php/AAAI-SS/article/download/31785/33952Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI-SS/article/download/31785/33952Direct OA link when available
- Concepts
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Asynchronous communication, Computer science, Computer networkTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(N=10) | 80 |
| abstract_inverted_index.adults | 10, 79, 171 |
| abstract_inverted_index.assist | 7 |
| abstract_inverted_index.common | 23 |
| abstract_inverted_index.during | 67 |
| abstract_inverted_index.enrich | 191 |
| abstract_inverted_index.health | 141, 153, 193 |
| abstract_inverted_index.models | 48 |
| abstract_inverted_index.showed | 183 |
| abstract_inverted_index.suffer | 27 |
| abstract_inverted_index.Despite | 0 |
| abstract_inverted_index.adults' | 158 |
| abstract_inverted_index.adults, | 118, 198 |
| abstract_inverted_index.efforts | 203 |
| abstract_inverted_index.further | 164 |
| abstract_inverted_index.groups: | 114 |
| abstract_inverted_index.initial | 212 |
| abstract_inverted_index.limited | 29, 62 |
| abstract_inverted_index.natural | 53 |
| abstract_inverted_index.present | 151 |
| abstract_inverted_index.process | 34 |
| abstract_inverted_index.results | 182 |
| abstract_inverted_index.studies | 75, 168 |
| abstract_inverted_index.system, | 106 |
| abstract_inverted_index.system. | 180 |
| abstract_inverted_index.However, | 58 |
| abstract_inverted_index.designed | 109 |
| abstract_inverted_index.envision | 207 |
| abstract_inverted_index.evaluate | 175 |
| abstract_inverted_index.language | 47 |
| abstract_inverted_index.leverage | 45 |
| abstract_inverted_index.methods, | 25 |
| abstract_inverted_index.plethora | 2 |
| abstract_inverted_index.powerful | 52 |
| abstract_inverted_index.process, | 190 |
| abstract_inverted_index.solution | 38 |
| abstract_inverted_index.LLM-based | 146 |
| abstract_inverted_index.Talk2Care | 185 |
| abstract_inverted_index.collected | 195 |
| abstract_inverted_index.conducted | 72, 165 |
| abstract_inverted_index.dashboard | 147 |
| abstract_inverted_index.effective | 136 |
| abstract_inverted_index.important | 152 |
| abstract_inverted_index.insights, | 100 |
| abstract_inverted_index.interface | 134 |
| abstract_inverted_index.interview | 74 |
| abstract_inverted_index.leveraged | 120 |
| abstract_inverted_index.messaging | 15 |
| abstract_inverted_index.promising | 37 |
| abstract_inverted_index.providers | 83, 173 |
| abstract_inverted_index.summarize | 149 |
| abstract_inverted_index.usability | 177 |
| abstract_inverted_index.Talk2Care, | 107 |
| abstract_inverted_index.assistants | 127 |
| abstract_inverted_index.capability | 216 |
| abstract_inverted_index.components | 111 |
| abstract_inverted_index.facilitate | 40, 187 |
| abstract_inverted_index.healthcare | 12, 82, 221 |
| abstract_inverted_index.home-based | 8 |
| abstract_inverted_index.providers' | 202 |
| abstract_inverted_index.providers, | 13, 142 |
| abstract_inverted_index.telehealth | 4 |
| abstract_inverted_index.understand | 86 |
| abstract_inverted_index.LLM-powered | 104, 132 |
| abstract_inverted_index.capability. | 57 |
| abstract_inverted_index.collection. | 138 |
| abstract_inverted_index.convenience | 122 |
| abstract_inverted_index.exploration | 213 |
| abstract_inverted_index.information | 31, 137, 154, 194 |
| abstract_inverted_index.interactive | 110 |
| abstract_inverted_index.applications | 5 |
| abstract_inverted_index.asynchronous | 95 |
| abstract_inverted_index.considerably | 200 |
| abstract_inverted_index.conversation | 54 |
| abstract_inverted_index.intersection | 219 |
| abstract_inverted_index.accessibility | 124 |
| abstract_inverted_index.availability, | 30 |
| abstract_inverted_index.communication | 24, 42, 105, 189 |
| abstract_inverted_index.conversations | 159 |
| abstract_inverted_index.interpersonal | 223 |
| abstract_inverted_index.opportunities | 90 |
| abstract_inverted_index.summarization | 56 |
| abstract_inverted_index.understanding | 63 |
| abstract_inverted_index.communication. | 69, 96, 224 |
| abstract_inverted_index.conversational | 133 |
| abstract_inverted_index.inefficiencies. | 35 |
| abstract_inverted_index.patient-provider | 41, 94 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 9 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.90205719 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |