MoHIMA | Artificial Intelligence in Health Care: A Cure for Data Pains

Overview:

Healthcare effectiveness and efficiency is at the forefront of conversations on a daily basis be it from the patient, the physician or the C Suite perspective. The US healthcare system is expensive and wasteful and ranked near the bottom of the Bloomberg list of Healthcare Efficiency Scores in 56 economies *. So, what can we do about it? The answer is simple. Introduce AI and Machine Learning to streamline complex and inefficient processes to bolster physician productivity, increase patient satisfaction and improve your bottom line.  This presentation will provide a high-level overview of Artificial Intelligence and Machine Learning and practical uses to achieve organizational efficiency as well as financial and quality outcomes.

Learning Objectives

This session is for healthcare leaders (both business and tech), who want to learn basics of Machine Learning and how it can be implemented in business to improve revenue cycle processes.

As leaders we are often dependent on our technical resources, data scientists, vendors, and marketing spiel to learn about machine learning solutions. In this session, we will go beyond the buzz to understand how this remarkable technology works and learn to ask the right questions from our teams, leadership, and vendors. Along the way, we will learn how we can use Machine Learning to combat denials.

Session Outline:

• Machine Learning
  • Machine Learning terms every leader should know
  • How Machine Learning works & common solutions
  • Machine Learning Vs. Robotic Process Automation
• Denials Management
  • Cost of Denials, Industry Trends, Rate of Appeal
• Combating Denials with Machine Learning
  • Use Cases
  • Where can you use Machine learning in your organization
• Machine Learning: Implementation in Business
  • Implementation challenges
  • How to Identify a good Machine Learning problem

Published:

March 1, 2020

CEU:

CEU: 1.0 – Data Structure, Content and Information Governance

Speaker:

Ankit Sharma
Vice President, Analytics, Data & AI

Ankit Sharma is the Vice President, Analytics – leading Big Data Architecture, Business Intelligence, Machine learning & AI for nThrive. He heads nThrive Analytics’ development, leading a global team of 50+ Engineers, Analysts, Architects, data scientists and tech leadership.

Sharma began his career in healthcare as consultant with a tech startup, specializing in data driven healthcare management and economics. Unique blend of technology and healthcare consulting background have helped him to innovate industry leading analytics solutions. After a successful startup exit in 2016, he stayed in healthcare with a vision of using technology to reduce the cost of healthcare. His work today is focused on solving that very problem through analytics, innovation and automation of revenue cycle processes.

Sharma is a Microsoft Certified professional and holds MBA in Information Systems Management.