Presentation
Beyond the Algorithm: Designing Human-AI Partnerships in Healthcare
DescriptionArtificial Intelligence (AI) is revolutionizing how we live, work, and interact with technology. From chatbots that answer questions to algorithms that power medical diagnostics and clinical decision support, AI is embedded in many facets of modern life and becoming an integral part of healthcare. Despite its widespread use and potential to solve complex problems, a crucial aspect of AI development lies in how humans interact with it, especially in healthcare.
The objectives of this panel are to engage participants in an exploration of the fundamentals of AI use in healthcare, operationalization of AI implementation, identify key challenges in human-AI interaction, and opportunities in evolving human factors testing methods used to evaluate and improve these systems. By the end of the session, attendees will have an increased understanding of what makes human-AI interaction complex within the context of healthcare and how it can be optimized to improve provider and staff workload burden, and patient care and safety.
The panel is comprised of experts in human factors, AI in nursing, and Informatics and each will provide their unique perspectives on the topic.
Tamara Winden from Ben Allegretti Consulting will bring her expertise as a biomedical informaticist and cognitive scientist with over two decades of experience spanning clinical informatics, governance, analytics, research, and user-centered design. She will address the challenges of integrating AI tools into healthcare IT operations and workflows, with an emphasis on ensuring governance compliance, transparency, usability, and efficiency. Dr. Winden will highlight strategies to leverage AI for optimizing patient care, reducing provider and staff burden, and advancing translational research. Her perspective bridges operational healthcare IT management and human factors science, providing a practical lens for aligning technology with real-world clinical needs.
Prithima Reddy Mosaly from UNC Chapel Hill will talk about her current work focusing on human-centered AI and some of the key human factors challenges. She will elaborate on "human-centered AI" in the context of healthcare, and what makes it essential for successful clinical implementation. She will also share lesson learned about balancing the "promise" of AI in reducing provider workload with the operational realities of a human-centered implementation, and how to measure that balance ensuring a seamless and safe integration of AI into a clinical workflow.
Kristen Miller from the MedStar Health National Center for Human Factors in Healthcare will talk about the challenges and opportunities of ambient digital scribes through the lens of the patient experience. She will highlight how ADS have the potential not only to reduce clinician documentation burden but also to fundamentally reshape the diagnostic conversation. By capturing the full encounter, these tools could provide new opportunities to analyze communication patterns, generate actionable feedback for clinicians, and support safer, clearer diagnostic reasoning. Importantly, ADS could also produce patient-friendly summaries that help individuals understand their care plan, remember key instructions, and feel more engaged in shared decision making. At the same time, Dr. Miller will underscore the risks, such as errors, over-reliance on transcripts, and unintended inequities, that must be addressed to ensure these technologies enhance rather than undermine patient trust. Her remarks will emphasize how human factors methods can guide the safe, equitable, and patient-centered design and implementation of ambient digital scribes in healthcare.
Lisianne Pruinelli from the Department of Biobehavioral Nursing Science at the University of Florida College of Nursing and the Department of Surgery, College of Medicine will share her unique perspective as a nurse informatician and clinical scientist leading multi-site research on AI-enabled decision support in liver transplantation and complex chronic disease. Drawing on her work integrating EHR and registry data with text-mining and explainable machine learning, she will highlight the opportunities and challenges of embedding AI into clinical workflows. Her contributions will focus on governance, safety, equity, and clinician-patient communication, offering a frontline nursing perspective on human-AI teaming. In addition, Dr. Pruinelli will discuss her ongoing leadership in AI curriculum development, governance, and collaborative health-system partnerships, illustrating how thoughtful evaluation and federated learning approaches can advance both patient outcomes and workforce well-being.
Onur Asan will share his perspective on advancing the safe, equitable, and human-centered adoption of AI in healthcare through the lens of human factors and socio-technical systems design. Drawing from his research at Stevens Institute of Technology on clinician–AI teaming, explainability and fairness, and patient-centered care, he will highlight how AI tools can be thoughtfully integrated into complex clinical environments without eroding trust, increasing cognitive burden, or amplifying inequities. Dr. Asan will discuss strategies to incorporate trustworthiness and explainability into AI systems, methods to evaluate their impact on clinician workload and decision-making, and the importance of engaging frontline clinicians and patients in participatory design. His remarks will emphasize building organizational capacity and governance structures that align technological innovation with human well-being, thereby enabling AI to enhance, rather than disrupt, safe and compassionate care delivery.
Each panelist will address these questions as well as questions posed by the attendees:
1. From your perspective please provide a brief overview of the landscape of Human Factors practice and Artificial Intelligence use in healthcare delivery?
2. What do you believe are the key challenges we face as human factors practitioners in incorporating AI tools into healthcare workflows?
3. What do you believe are the key opportunities that AI presents to assist in reducing provider/staff workload burden and in improving patient care?
4. Looking to the future, how should human factors practitioners and health care organizations position themselves for success in the rapidly changing landscape of AI?
Key Takeaways and Learning Objectives:
After this session, attendees will be able to:
• Describe the current landscape of AI applications in healthcare and their implications for clinicians, patients, and health systems.
• Analyze how AI recommendations can be integrated into clinical workflows to support, rather than disrupt, care delivery.
• Apply human factors principles to the testing, design, and evaluation of AI interfaces in healthcare.
• Evaluate the potential risks, benefits, and equity considerations of AI use in healthcare, with attention to patient safety and provider workload.
• Identify future opportunities for human factors practitioners to shape safe, effective, and human-centered AI implementation.
The objectives of this panel are to engage participants in an exploration of the fundamentals of AI use in healthcare, operationalization of AI implementation, identify key challenges in human-AI interaction, and opportunities in evolving human factors testing methods used to evaluate and improve these systems. By the end of the session, attendees will have an increased understanding of what makes human-AI interaction complex within the context of healthcare and how it can be optimized to improve provider and staff workload burden, and patient care and safety.
The panel is comprised of experts in human factors, AI in nursing, and Informatics and each will provide their unique perspectives on the topic.
Tamara Winden from Ben Allegretti Consulting will bring her expertise as a biomedical informaticist and cognitive scientist with over two decades of experience spanning clinical informatics, governance, analytics, research, and user-centered design. She will address the challenges of integrating AI tools into healthcare IT operations and workflows, with an emphasis on ensuring governance compliance, transparency, usability, and efficiency. Dr. Winden will highlight strategies to leverage AI for optimizing patient care, reducing provider and staff burden, and advancing translational research. Her perspective bridges operational healthcare IT management and human factors science, providing a practical lens for aligning technology with real-world clinical needs.
Prithima Reddy Mosaly from UNC Chapel Hill will talk about her current work focusing on human-centered AI and some of the key human factors challenges. She will elaborate on "human-centered AI" in the context of healthcare, and what makes it essential for successful clinical implementation. She will also share lesson learned about balancing the "promise" of AI in reducing provider workload with the operational realities of a human-centered implementation, and how to measure that balance ensuring a seamless and safe integration of AI into a clinical workflow.
Kristen Miller from the MedStar Health National Center for Human Factors in Healthcare will talk about the challenges and opportunities of ambient digital scribes through the lens of the patient experience. She will highlight how ADS have the potential not only to reduce clinician documentation burden but also to fundamentally reshape the diagnostic conversation. By capturing the full encounter, these tools could provide new opportunities to analyze communication patterns, generate actionable feedback for clinicians, and support safer, clearer diagnostic reasoning. Importantly, ADS could also produce patient-friendly summaries that help individuals understand their care plan, remember key instructions, and feel more engaged in shared decision making. At the same time, Dr. Miller will underscore the risks, such as errors, over-reliance on transcripts, and unintended inequities, that must be addressed to ensure these technologies enhance rather than undermine patient trust. Her remarks will emphasize how human factors methods can guide the safe, equitable, and patient-centered design and implementation of ambient digital scribes in healthcare.
Lisianne Pruinelli from the Department of Biobehavioral Nursing Science at the University of Florida College of Nursing and the Department of Surgery, College of Medicine will share her unique perspective as a nurse informatician and clinical scientist leading multi-site research on AI-enabled decision support in liver transplantation and complex chronic disease. Drawing on her work integrating EHR and registry data with text-mining and explainable machine learning, she will highlight the opportunities and challenges of embedding AI into clinical workflows. Her contributions will focus on governance, safety, equity, and clinician-patient communication, offering a frontline nursing perspective on human-AI teaming. In addition, Dr. Pruinelli will discuss her ongoing leadership in AI curriculum development, governance, and collaborative health-system partnerships, illustrating how thoughtful evaluation and federated learning approaches can advance both patient outcomes and workforce well-being.
Onur Asan will share his perspective on advancing the safe, equitable, and human-centered adoption of AI in healthcare through the lens of human factors and socio-technical systems design. Drawing from his research at Stevens Institute of Technology on clinician–AI teaming, explainability and fairness, and patient-centered care, he will highlight how AI tools can be thoughtfully integrated into complex clinical environments without eroding trust, increasing cognitive burden, or amplifying inequities. Dr. Asan will discuss strategies to incorporate trustworthiness and explainability into AI systems, methods to evaluate their impact on clinician workload and decision-making, and the importance of engaging frontline clinicians and patients in participatory design. His remarks will emphasize building organizational capacity and governance structures that align technological innovation with human well-being, thereby enabling AI to enhance, rather than disrupt, safe and compassionate care delivery.
Each panelist will address these questions as well as questions posed by the attendees:
1. From your perspective please provide a brief overview of the landscape of Human Factors practice and Artificial Intelligence use in healthcare delivery?
2. What do you believe are the key challenges we face as human factors practitioners in incorporating AI tools into healthcare workflows?
3. What do you believe are the key opportunities that AI presents to assist in reducing provider/staff workload burden and in improving patient care?
4. Looking to the future, how should human factors practitioners and health care organizations position themselves for success in the rapidly changing landscape of AI?
Key Takeaways and Learning Objectives:
After this session, attendees will be able to:
• Describe the current landscape of AI applications in healthcare and their implications for clinicians, patients, and health systems.
• Analyze how AI recommendations can be integrated into clinical workflows to support, rather than disrupt, care delivery.
• Apply human factors principles to the testing, design, and evaluation of AI interfaces in healthcare.
• Evaluate the potential risks, benefits, and equity considerations of AI use in healthcare, with attention to patient safety and provider workload.
• Identify future opportunities for human factors practitioners to shape safe, effective, and human-centered AI implementation.
Moderator
Panelist
Event Type
Discussion Panel
TimeTuesday, March 241:30pm - 3:00pm EDT
LocationNassau
Digital Health