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Sherrill Kaplan

Chief Digital Officer
Planet Fitness

Sherrill Kaplan

Chief Digital Officer
Planet Fitness

Sherrill Kaplan

Chief Digital Officer
Planet Fitness
Frankie Cancino Spotlight
  • In healthcare to optimize skills, understanding, and expertise used to improve the value of products, it is essential to remove clinical and financial silos. Collaborating and aligning revenue teams with value analysis teams provide a platform to tell the entire business story in healthcare, decrease cost, and increase revenue.  Relationships in this arena generate opportunities to find billing and charging errors, and implement best practices into workflow, procedures, and buying trends. Collaboration benefits the teams by offering vital evidence that helps providers make judicious choices about the products they may want to bring into facilities.  A revenue cycle analyst can aid in the discovery of problems with processes or old ways of how and where procedures are performed. Using dashboards, reports, and charging and reimbursement data can be seamlessly be integrated into existing value analysis processes making it easy to collaborate on the best ways to achieve your revenue targets.

Author:

Lori Jensen

Director of Value Analysis
University of Utah Health

Lori Jensen

Director of Value Analysis
University of Utah Health
Alphawave Semi 'Leading the World in High-speed Connectivity Solutions'
 

Akhil Vaid

Instructor, Division of Data-Driven and Digital Medicine
Icahn School of Medicine Mt. Sinai

Akhil Vaid, MD, is a distinguished Instructor at the Division of Data Driven and Digital Medicine (D3M), Department of Medicine at the Icahn School of Medicine at Mount Sinai. Renowned for his expertise as a physician-scientist, Dr. Vaid's work navigates the intriguing intersection of medicine and technology, with a resolute commitment to foster democratized healthcare through the power of machine learning.

 

Akhil Vaid

Instructor, Division of Data-Driven and Digital Medicine
Icahn School of Medicine Mt. Sinai

Akhil Vaid

Instructor, Division of Data-Driven and Digital Medicine
Icahn School of Medicine Mt. Sinai

Akhil Vaid, MD, is a distinguished Instructor at the Division of Data Driven and Digital Medicine (D3M), Department of Medicine at the Icahn School of Medicine at Mount Sinai. Renowned for his expertise as a physician-scientist, Dr. Vaid's work navigates the intriguing intersection of medicine and technology, with a resolute commitment to foster democratized healthcare through the power of machine learning.

 

After obtaining his medical degree from one of India's eminent medical colleges, Dr. Vaid served patients across diverse socio-economic landscapes. This unique exposure catalyzed his conviction that true healthcare equity could only be achieved through machine learning and artificial intelligence. Consequently, he ventured into the intricate domains of multi-modal machine learning, specializing in deep learning with ECGs, federated learning, Natural Language Processing, and deriving valuable insights from the Electronic Healthcare Record.

 

Before his current role at the Icahn School of Medicine at Mount Sinai, Dr. Vaid honed his clinical skills and amassed a wealth of experience in the Indian healthcare system. His medical journey is punctuated by his relentless quest for innovation, illustrated by his extensive contributions to the rapidly evolving field of digital medicine.

 

Dr. Vaid is the author of 54 scientific publications, esteemed contributions to esteemed medical journals, including Nature Medicine, the Annals of Internal Medicine, and NPJ Digital Medicine. His work is reflective of his profound understanding of medicine and technology and their potential in transforming patient care. His projects, backed by significant grants, encompass multiple facets of informatics, data science, and machine learning in medicine.

 

Xinghai Hu

Head of US Algorithm
TikTok

Xinghai Hu is currently the head of TikTok US recommendation team. His team works on responsible recommendation system, improving general safety and trustability of content recommendations.

Xinghai Hu

Head of US Algorithm
TikTok

Xinghai Hu

Head of US Algorithm
TikTok

Xinghai Hu is currently the head of TikTok US recommendation team. His team works on responsible recommendation system, improving general safety and trustability of content recommendations.