Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis
Abstract BackgroundThere is growing interest in applying generative artificial intelligence (GenAI) to respond to electronic patient portal messages, particularly in primary care where message volumes are highest. However, evaluations of GenAI as an inbox communication tool ar...
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| Format: | Article |
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JMIR Publications
2025-07-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e71966 |
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| author | Natalie S Lee Nathan Richards Jodi Grandominico Robert M Cronin Amanda K Hendricks Ravi S Tripathi Daniel E Jonas |
| author_facet | Natalie S Lee Nathan Richards Jodi Grandominico Robert M Cronin Amanda K Hendricks Ravi S Tripathi Daniel E Jonas |
| author_sort | Natalie S Lee |
| collection | DOAJ |
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Abstract
BackgroundThere is growing interest in applying generative artificial intelligence (GenAI) to respond to electronic patient portal messages, particularly in primary care where message volumes are highest. However, evaluations of GenAI as an inbox communication tool are limited. Qualitative analysis of when and how often GenAI responses achieve communication goals can inform estimates of impact and guide continuous improvement.
ObjectiveThis study aims to evaluate GenAI responses to primary care messages using a medical communication framework.
MethodsThis was a descriptive quality improvement study of 201 GenAI replies to a purposively sampled, diverse pool of real primary care patient messages in a large midwestern academic medical center. Two physician reviewers (NSL and NR) used a hybrid deductive-inductive approach to qualitatively identify and define themes, guided by constructs from the “best practice” medical communication framework. After achieving thematic saturation, the reviewers assessed the presence or absence of identified communication themes, both independently and collaboratively. Discrepant observations were reconciled via discussion. Frequencies of identified themes were tallied.
ResultsThemes in strengths and limitations emerged across 5 communication domains. In the domain of rapport buildinginformation gatheringinformation deliveryfacilitate next stepsresponding to emotionrapport buildingfacilitating next stepsinformation deliveryinformation gatheringresponding to emotion
ConclusionsGenAI response quality on behalf of primary care physicians and advanced practice providers may vary by communication function. Expressions of respect or descriptions of common next steps may be appropriate, but gathering and delivering appropriate information, or responding to emotion, may be limited. While communication standards were often met, they were also often compromised. Understanding these strengths and limitations can inform decisions about whether, when, and how to apply GenAI as a tool for primary care inbox communication. |
| format | Article |
| id | doaj-art-e6ce8a1960f74f9f822f98268af36551 |
| institution | DOAJ |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj-art-e6ce8a1960f74f9f822f98268af365512025-08-20T02:58:21ZengJMIR PublicationsJMIR Formative Research2561-326X2025-07-019e71966e7196610.2196/71966Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content AnalysisNatalie S Leehttp://orcid.org/0000-0002-6335-7934Nathan Richardshttp://orcid.org/0009-0003-0687-6791Jodi Grandominicohttp://orcid.org/0009-0000-1746-4731Robert M Croninhttp://orcid.org/0000-0003-1916-6521Amanda K Hendrickshttp://orcid.org/0009-0007-6027-0458Ravi S Tripathihttp://orcid.org/0000-0003-1873-6836Daniel E Jonashttp://orcid.org/0000-0003-1964-8731 Abstract BackgroundThere is growing interest in applying generative artificial intelligence (GenAI) to respond to electronic patient portal messages, particularly in primary care where message volumes are highest. However, evaluations of GenAI as an inbox communication tool are limited. Qualitative analysis of when and how often GenAI responses achieve communication goals can inform estimates of impact and guide continuous improvement. ObjectiveThis study aims to evaluate GenAI responses to primary care messages using a medical communication framework. MethodsThis was a descriptive quality improvement study of 201 GenAI replies to a purposively sampled, diverse pool of real primary care patient messages in a large midwestern academic medical center. Two physician reviewers (NSL and NR) used a hybrid deductive-inductive approach to qualitatively identify and define themes, guided by constructs from the “best practice” medical communication framework. After achieving thematic saturation, the reviewers assessed the presence or absence of identified communication themes, both independently and collaboratively. Discrepant observations were reconciled via discussion. Frequencies of identified themes were tallied. ResultsThemes in strengths and limitations emerged across 5 communication domains. In the domain of rapport buildinginformation gatheringinformation deliveryfacilitate next stepsresponding to emotionrapport buildingfacilitating next stepsinformation deliveryinformation gatheringresponding to emotion ConclusionsGenAI response quality on behalf of primary care physicians and advanced practice providers may vary by communication function. Expressions of respect or descriptions of common next steps may be appropriate, but gathering and delivering appropriate information, or responding to emotion, may be limited. While communication standards were often met, they were also often compromised. Understanding these strengths and limitations can inform decisions about whether, when, and how to apply GenAI as a tool for primary care inbox communication.https://formative.jmir.org/2025/1/e71966 |
| spellingShingle | Natalie S Lee Nathan Richards Jodi Grandominico Robert M Cronin Amanda K Hendricks Ravi S Tripathi Daniel E Jonas Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis JMIR Formative Research |
| title | Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis |
| title_full | Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis |
| title_fullStr | Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis |
| title_full_unstemmed | Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis |
| title_short | Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis |
| title_sort | use of a medical communication framework to assess the quality of generative artificial intelligence replies to primary care patient portal messages content analysis |
| url | https://formative.jmir.org/2025/1/e71966 |
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