Assessing Cardiologists' User Experience with Electronic Medical Records and Generative Artificial Intelligence Visualization
Abstract
Cardiovascular Diseases (CVDs) are a leading cause of death worldwide, accounting for 17.3 million deaths per year. Artificial intelligence has gained prominence in recent years, and there is a significant interest in exploring how artificial intelligence can improve patient outcomes and decrease hospitalization rates. This study will identify the most critical values that cardiologists consider when evaluating patients’ charts, including factors such as medical history, diagnostic results, and current medications. Additionally, the study explores cardiologists' attitudes towards the integration of AI-generated imagery based on these critical values to enhance the efficiency and quality of patient care. A comprehensive survey will be distributed to certified cardiologists, inquiring about the importance of various patient chart values, such as age, past medical history, and ECG findings (e.g., rhythm, QT interval). The survey will also assess cardiologists' openness to utilizing AI-generated imagery that encapsulates the most critical values for a succinct and informative overview of the patient's medical record. The study will analyze the survey responses to rank the values in importance as perceived by cardiologists. Also, it will evaluate the level of interest and potential concerns among cardiologists regarding AI-generated imagery in clinical practice. The findings of this study will provide insights into the key factors that cardiologists prioritize when reviewing patient charts, which can inform the development of more targeted and efficient diagnostic tools. Furthermore, the study will gauge the readiness of cardiology professionals to embrace AI technologies that could revolutionize patient record management and decision-making processes in cardiac care.
Faculty Sponsors
Dr. Michelle Ramim
Project Type
Event
Location
Alvin Sherman Library
Start Date
4-3-2024 12:30 PM
End Date
4-4-2024 1:30 PM
Assessing Cardiologists' User Experience with Electronic Medical Records and Generative Artificial Intelligence Visualization
Alvin Sherman Library
Cardiovascular Diseases (CVDs) are a leading cause of death worldwide, accounting for 17.3 million deaths per year. Artificial intelligence has gained prominence in recent years, and there is a significant interest in exploring how artificial intelligence can improve patient outcomes and decrease hospitalization rates. This study will identify the most critical values that cardiologists consider when evaluating patients’ charts, including factors such as medical history, diagnostic results, and current medications. Additionally, the study explores cardiologists' attitudes towards the integration of AI-generated imagery based on these critical values to enhance the efficiency and quality of patient care. A comprehensive survey will be distributed to certified cardiologists, inquiring about the importance of various patient chart values, such as age, past medical history, and ECG findings (e.g., rhythm, QT interval). The survey will also assess cardiologists' openness to utilizing AI-generated imagery that encapsulates the most critical values for a succinct and informative overview of the patient's medical record. The study will analyze the survey responses to rank the values in importance as perceived by cardiologists. Also, it will evaluate the level of interest and potential concerns among cardiologists regarding AI-generated imagery in clinical practice. The findings of this study will provide insights into the key factors that cardiologists prioritize when reviewing patient charts, which can inform the development of more targeted and efficient diagnostic tools. Furthermore, the study will gauge the readiness of cardiology professionals to embrace AI technologies that could revolutionize patient record management and decision-making processes in cardiac care.
