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Exploring the science, practice, and business of medicine.
Exploring the science, practice, and business of medicine.
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HealthSpark Episode 2: Yuri Quintana, Chief of the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and Assistant Professor of Medicine at Harvard Medical School, examines how fragmented patient data and rapidly evolving AI tools create powerful opportunities for patient engagement but also serious risks when health decisions are made using incomplete or misleading information.
HealthSpark Episode 1: Rifat Atun, Professor of Global Health Systems at Harvard University, discusses how data, digital tools, and AI could support more integrated, personalized care models in health systems facing rapid demographic and epidemiological change.
In an era of rampant online misinformation, improving health literacy and access to credible digital health content is critical.
Quick, relevant insights for business professionals, clinicians, scientists, and health care professionals who want to lead change—no matter their role.
As data, omics, and AI converge, precision medicine is enabling clinicians to predict disease earlier and deliver truly individualized, preventive, and more effective care.
Effective AI leadership in health care centers on people, trust, and systems—requiring leaders who pair clinical insight and ethical judgment with the ability to integrate technology thoughtfully into real-world workflows.
Strategic AI adoption in health care depends less on the technology itself and more on evidence-based decision-making, thoughtful leadership, and cultures that align innovation with real clinical workflows.
AI is reshaping medicine by enhancing care, safety, and education. Experts stress thoughtful use, equity, and human judgment to ensure technology augments, not replaces, clinicians.
Custom corporate learning programs are becoming essential for health care organizations, offering education that aligns with strategic priorities, clinical realities, and cultural nuances while directly impacting patient outcomes and system-wide efficiency.
Jamie Roberston says it is critical for people who are interacting with AI as part of clinical studies to be knowledgeable about the right and wrong applications.