AIMC Topic: Patient Portals

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Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2024
OBJECTIVES: The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring t...
Natural Language Processing Patient Portals Neural Networks, Computer Machine Learning Humans
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Comparing the quality of ChatGPT- and physician-generated responses to patients' dermatology questions in the electronic medical record.

Clinical and experimental dermatology Jun 25, 2024
BACKGROUND: ChatGPT is a free artificial intelligence (AI)-based natural language processing tool that generates complex responses to inputs from users.
Artificial Intelligence Physicians Humans Physician-Patient Relations Dermatology Electronic Health Records Natural Language Processing Patient Portals
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AI-Drafted Responses to Patients Reduced Clinician Burnout.

JAMA May 7, 2024
Patient Portals Communication Burnout, Professional United States Workload Artificial Intelligence Physicians Humans
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A scoping review of empathy recognition in text using natural language processing.

Journal of the American Medical Informatics Association : JAMIA Feb 16, 2024
OBJECTIVE: To provide a scoping review of studies on empathy recognition in text using natural language processing (NLP) that can inform an approach to identifying physician empathic communication over patient portal messages.
Empathy Communication Natural Language Processing Physician-Patient Relations Patient Portals Humans
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Development of a Flexible Chain of Thought Framework for Automated Routing of Patient Portal Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
The increase in utilization of patient portal messages has imposed a considerable burden on healthcare providers, contributing to an increased incidence of provider burnout. This study introduces a framework for leveraging Large Language Models (LLMs...
Natural Language Processing Humans Patient Portals Electronic Health Records
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Improving Emergency Department Visit Risk Prediction: Exploring the Operational Utility of Applied Patient Portal Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
Patient portal messages represent a unique source of clinical data due to how they represent the voice of the patient, provide a glimpse into care delivery between episodic synchronous appointments, and capture variations in patient behavior and heal...
Humans Risk Assessment Patient Portals Natural Language Processing Emergency Room Visits Emergency Service, Hospital
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Identifying Nonpatient Authors of Patient Portal Secure Messages in Oncology: A Proof-of-Concept Demonstration of Natural Language Processing Methods.

JCO clinical cancer informatics Dec 1, 2022
PURPOSE: Patient portal secure messages are not always authored by the patient account holder. Understanding who authored the message is particularly important in an oncology setting where symptom reporting is crucial to patient treatment. Natural la...
Humans Patient Portals Natural Language Processing Proof of Concept Study
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A systematic literature review of machine learning in online personal health data.

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2019
OBJECTIVE: User-generated content (UGC) in online environments provides opportunities to learn an individual's health status outside of clinical settings. However, the nature of UGC brings challenges in both data collecting and processing. The purpos...
Internet Patient Portals Patient Generated Health Data Machine Learning Social Media Humans
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Community-Acquired Pneumonia Case Validation in an Anonymized Electronic Medical Record-Linked Expert System.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America May 15, 2017
An electronic anonymized patient portal analysis using radiographic reports and admission and discharge diagnoses had sensitivity, specificity, positive predictive value, and negative predictive value of 84.7%, 78.2%, 75%, and 87%, respectively, for ...
Patient Portals Pneumonia Predictive Value of Tests Sensitivity and Specificity Anti-Bacterial Agents Female Radiography, Thoracic Young Adult Male Humans Electronic Health Records Hospitalization Community-Acquired Infections Adult Data Anonymization Algorithms Expert Systems
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