Artificial intelligence in the healthcare industry is predicted to save $150 billion annually for the US. As such, AI is being rapidly deployed in many areas of the healthcare landscape. This event will primarily focus on the Providers, attracting CIOs,
CDOs, CTOs, VPs of IT and Informatics along with senior Physicians and Clinicians from leading US hospitals who will assess the business value outcomes of AI and share experiences of implementation in clinical care and hospital operations.
Thursday, October 24
7:45 am Registration Opens
8:00 Continental Breakfast (Harborview Foyer)
9:00 – 12:25 pm Keynote Session (Harborview)
12:25 pm Networking, Coffee & Dessert in the Expo (Commonwealth Hall)
1:30 pm Opening Remarks
Lynne Dunbrack, Group Vice President, IDC
1:35 Catch a Fraudster: How AI and Advanced Analytics find the Needle in the Haystack
Jo-Ellen Abou Nader, Vice President, FWA & Supply Chain Optimization, Prime Therapeutics
Steve Kearney, Medical Director, SAS
Fraud tactics in health care have evolved significantly over the past few years. As bad actors deploy even more evasive schemes, those who want to mitigate fraud, waste and abuse need analytics to proactively combat criminals and unintentional negligence. Hear Prime Therapeutics and SAS share real examples of case investigations which include telemedicine, opioid abuse, foot bath schemes and patient safety issues. This presentation will cover how artificial intelligence (AI) and other advanced analytic techniques have enabled Prime Therapeutics to combat the complexities of health care fraud with SAS, the “art of the possible” with fraud analytics, and how PBMs and health plans are realizing the benefits.
2:05 KEYNOTE: Creating a Robust Data Ecosystem to Support the Spectrum of Analytics from Basic Descriptive to Advanced ML/AI
John W. Pyhtila,
PhD, Chief Data and Analytics Officer, Partners HealthCare System
Demand for basic and advanced analytics is growing exponentially in healthcare. Building a robust data ecosystem to support the spectrum of analytics, from descriptive analytics to support efficient operations to advanced ML / AI analytics to drive
differentiated outcomes is a critical enabler for provider systems. This talk will highlight the path Partners HealthCare is on to evolve the data ecosystem to support the wide range and analytic needs.
2:25 KEYNOTE: Voice and The Future of Precision Care
Brownstein, PhD, Chief Innovation Officer, Boston Children's Hospital; Professor, Harvard Medical School
Since Boston Children’s Hospital launched KidsMD, the first healthcare skill on the Amazon Alexa platform, in early 2016, we have believed in the opportunity for voice technologies to transform the delivery of healthcare. As a pioneer among
healthcare providers experimenting with voice assistants, the organization has continued to seek out and deploy voice technology across the patient journey. By understanding how and where voice technology can have the most impact for healthcare
organizations, we continue to explore the potential for this technology to disrupt the current state of healthcare technology.
2:45 PANEL: Interaction Between Payers, PBMs, VCs and Service Providers: Assessing Recent M&As and Streamlining AI Across all Sectors
- Assessing current and future M&As between PBMs, payers and providers
- How to make big data intelligent and actionable for healthcare providers
- Examining AI applications in fraud, waste and abuse and data security
Charles Jaffe, MD, PhD, CEO, Health Level 7 International
John Mattison, MD, CMIO, Kaiser Permanente
Beth Griffin, Vice President, Healthcare Cyber & Intelligence, Mastercard
Karim Botros, Managing Partner, Echo Health Ventures
Uzair Rashid, Consultant, Healthcare Strategy & Innovation Leader
3:20 Networking Break in the Expo (Commonwealth Hall)
4:05 AI and Advanced Algorithms in Healthcare from the Investor’s Perspective
Co-Founder and Managing Partner, Analytics Ventures
We are only beginning to enter into an era where life sciences and data science are merging. As the ability to collect data accelerates, so will the demand for data science applications that can help us process it. The vast amounts of data on the
human genome alone are far more than the human brain can effectively process. To be able to analyze and make recommendations based on this data, we need AI. This opens up opportunities for an entirely new sector in life sciences and healthcare.
But there are significant hurdles to be overcome when launching a new company or a new initiative within a company that seeks to apply AI to life sciences, especially when it deals with human health and welfare. To start with, finding both domain
experts, as well as talented data scientists, is not easy. There may be regulatory hurdles that vary across different geographies, differing data protection laws, and various insurance companies or other payers with their own agendas. This presentation
will address these and other considerations around when and how to invest in AI within the healthcare and life sciences industry.
4:25 PANEL: Emerging Business Models for AI within Healthcare
- Case studies: Success and failures
- Partnership model: The leaders and followers
- Roadmap: Today’s white paper
Moderator: Albine Martin, Executive in Residence, Johns Hopkins University
Katherine Andriole, PhD, Director of Research Strategy and Operations, MGH & BWH Center for Clinical Data Science; Associate Professor of Radiology, Harvard Medical School
Neil Carpenter, Senior Advisor, Pivotal
Senthil Kumaran, CIO, virtuwell by Healthpartners
5:05 Networking Reception in the Expo (Commonwealth Hall)
6:30 Meetup Groups (Cityview)
7:30 Close of Day 2
Friday, October 25
7:45 am Registration Opens
8:00 Continental Breakfast (Harborview Foyer)
8:15 am – 12:30 pm Keynote Session (Harborview)
12:30 Networking, Coffee & Dessert in the Expo – Last Chance for Viewing (Commonwealth Hall)
1:45 Opening Remarks
Cynthia Burghard, Research Director, Value-Based Healthcare IT Transformation Strategies, IDC Health Insights
1:50 From an Algorithm to an Enterprise Imaging Product
Phillippe Raffy, PhD, Executive Director, Artificial Intelligence, Change Healthcare
The increased availability of a new generation of powerful open-source AI algorithms presents tremendous opportunities in healthcare, creating market expectations as well as fears among healthcare professionals. Developing an AI-based medical imaging product in this context requires paying close attention to the IT ecosystem as well as the clinical workflow. This presentation will address these considerations in the context of enterprise imaging.
2:20 KEYNOTE: Processes and Infrastructure for Maximizing the Potential of Algorithmically Directed Care
Executive Director of IT, Partners HealthCare Personalized Medicine
AI has the potential to transform care delivery processes in ways that could simultaneously make them more efficient, effective and accessible. However, reaching this potential will require clinical and application infrastructure advancements that
extend well beyond the algorithms themselves. This will provide perspectives on the required changes and examples of how the needed infrastructure is developing.
2:45 AI in the Healthcare Enterprise
MD, Executive Director, Center for Clinical Data Science, Mass General Hospital and Brigham and Women’s Hospital
The application of machine learning has shown tremendous promise across a broad array of applications within medicine. From diagnostics to population health, hospital operations to clinical informatics, machine learning promises to make significant
impacts throughout healthcare. However, the development of machine learning solutions for patient care requires deep integration with clinical experts in the context of existing provider systems, along with significant investment in developing
the talent, tools, and training needed for implementation. During this talk, we discuss recent advances in machine learning that are driving innovation in medicine, leveraging own experience at two major academic medical centers in bringing machine
learning to the healthcare enterprise. We will describe recent successes, challenges, and future directions that will be required for the successful implementation of machine learning for medicine.
3:10 Networking Break (Plaza & Harbor Level Atriums)
3:25 Deep Learning for Clinical Natural Language Processing
Sadid Hasan, PhD,
Senior Scientist and Technical Lead, Artificial Intelligence Group, Philips Research
The ever-increasing amount of Electronic Health Record (EHR) clinical-free text documents has urged the need to build novel clinical natural language processing (NLP) solutions towards optimizing the patient outcomes across the care continuum. In
this talk, I will discuss some of the recent deep learning-based clinical NLP algorithms developed in the Artificial Intelligence Lab at Philips Research, such as radiology report classification, clinical paraphrase generation and text simplification,
and disease-named entity recognition, etc.
3:45 DigitalMe™: Patients Driving Discovery
Dean Cerrato, Director, Data Engineering, PatientsLikeMe
PatientsLikeMe is expanding beyond patient experience with the creation of DigitalMe, a program that activates our members to share not only their subjective health experiences, but also blood samples for multi-omic analysis over time. This rich set
of diverse and longitudinal, patient-centric data fuels an advanced machine learning platform for accelerating and automating biological discovery, enabling better diagnosis, quantification of health risk, and more personalized interventions.
4:05 PANEL: Data Scientists are from Mars, Clinicians are From Venus: Bridging AI Communication Between the Two Teams
- How to expose data scientists to the clinical world
- How to expose clinicians to data science
- How to foster a culture of collaboration
David Ledbetter, Data Scientist, Children’s Hospital Los Angeles
Anthony Chang, MD, Chief Intelligence and Innovation Officer, Medical Intelligence and Innovation Institute, CHOC
Chertok, PhD, Senior Data Scientist, Clinical Analytics Team, NorthShore University HealthSystem
John Miller, MD, Assistant Professor, Ophthalmology, Harvard Medical School; Director, Retinal Imaging, Massachusetts Eye and Ear Infirmary
4:45 Close of AI World 2019