Exploring the Benefits of Healthcare Data Analytics

Exploring the Benefits of Healthcare Data Analytics

Healthcare data analytics has become a game-changer in the healthcare industry, offering valuable insights and opportunities for improving patient outcomes, operational efficiency, cost-effectiveness, and overall quality of care. A daylong seminar presented by the Department of Biomedical Informatics and Long Island Network for Clinical and Translational Science (LINCATS) aims to provide participants with enhanced knowledge, skill development, informed decision-making, collaboration, networking, and addressing challenges.

The conference, scheduled for Thursday, October 19 at the Charles B. Wang Center, is exclusively open to faculty, staff, and students of Stony Brook University. While the main focus of the event is healthcare data analytics, it is designed to help attendees understand the benefits of utilizing real-world data to guide decision-making in healthcare. Moreover, the seminar aims to enhance expertise in healthcare data analysis and interpretation and create awareness of the various sources/interfaces available to explore this data both within and outside of Stony Brook.

Registering for the seminar provides an opportunity for professionals to dive deeper into healthcare data analytics and unlock its potential for their organizations. By attending the seminar, participants will gain a comprehensive understanding of the power of data-driven decision-making, which can lead to improved patient care, increased operational efficiency, and reduced costs. Furthermore, attendees will have the chance to network and collaborate with industry professionals and experts, fostering professional growth and furthering their knowledge in this rapidly evolving field.

For more information about the seminar, interested individuals can contact Joseph Cesaria at [email protected] or Mary Saltz at [email protected].

Sources:
– Department of Biomedical Informatics, Stony Brook Medicine
– Long Island Network for Clinical and Translational Science (LINCATS)

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