Artificial Intelligence in Healthcare Summit
June 23-24, 2022 * Bellagio * Las Vegas, NV

2022 Artificial Intelligence in Healthcare Summit

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COVID-19 Advisory: BRI Network holds above all else, the health & safety of our attendees and their families. Currently this event is scheduled as an in-person event. We will however, continue to monitor and follow recommendations regarding capacity from CDC and other health agencies.

About the Conference:

Healthcare is one of the greatest success stories of our times. Medical science has improved rapidly, increasing life expectancy around the world, but as longevity increases, hospitals and healthsystems face growing demand for their services, rising costs and a workforce that is struggling to meet the needs of its patients. Demand is driven by a combination of unstoppable forces: a shift in lifestyle choices, changing patient expectations, and the never-ending cycle of innovation being but a few. Of these, the implications from an aging population stand out. By 2050, one in four people in Europe and North America will be over the age of 65—this means the health systems will have to deal with more patients with complex needs. Managing such patients is expensive and requires systems to shift from an episodic care-based philosophy to one that is much more proactive and focused on long-term care management. Healthcare spending is simply not keeping up. Without major structural and transformational change, healthcare systems will struggle to remain sustainable. Health systems also need a larger workforce, but although the global economy could create 40 million new health-sector jobs by 2030, there is still a projected shortfall of 9.9 million physicians and nurses globally over the same period. We need not only to attract, train and retain more healthcare professionals, but we also need to ensure their time is used where it adds most value—caring for patients.

 

Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. AI can lead to better care outcomes and improve the productivity and efficiency of care delivery. It can also improve the day-to-day life of healthcare practitioners, letting them spend more time looking after patients and in so doing, raise staff morale and improve retention. It can even get life-saving treatments to market faster.

 

This event will focus on healthcare providers, attracting physicians, clinicians and IT leaders from hospitals across the country that are applying AI to solve problems, create opportunities, and leveraging it to deliver new value. They will share their experiences using AI in the clinical care and hospital operations settings. You will come away with a wealth of practical tips and actionable insights that will enable you and your organization to become a leader in AI’s imminent transformation of healthcare. The program is focused on helping you along on your AI journey, at whatever stage you may be. Hear case studies and real-world applications of AI in healthcare and its impact on future jobs.

 

Who Should Attend?

From Employers/Health Plans/Health Systems/Hospitals:

CEO’s/CIO’s/CTO’s
Chief Data Officers
Business & Technology Executives
IT Decision Makers
Heads of Innovation
IT Operations
Data Management
Medical Records
Director of Artificial Intelligence
Product Development
Data Architects
Scientists and Engineers
Telemedicine
Virtual Care Executives
Business Intelligence
Telehealth
Innovation Officer
Medical Directors

Also of Interest to:

Venture Capitalists
Investors
AI Consultants & Service Providers
R&D
Solution Providers
Robotics

Conference Agenda

Day One - Thursday, June 23, 2022

7:15am – 8:00am
Conference Registration & Networking Breakfast 

8:00am – 8:15am
Chairperson’s Opening Remarks  

8:15am – 9:00am
Opus 2, No. 1: AI in Healthcare Delivers on the Triple Aim of Care, Health and Cost

AI in healthcare is preparing Opus 2. In Opus 1, the research community galvanized to show the promise of AI in healthcare through an exponential rise in publications and investigations involving machine learning since the early 2000s. In Opus 2, AI will demonstrate the value of AI in driving the triple aim of improved population health, improved quality of care and patient experience, and lowered cost of care. In this talk, we will describe how we, at NYU Langone health, are fulfilling the vision of an AI enabled healthcare system. We will describe a framework for success, deployed and live applications in clinical (both inpatient and outpatient) and non-clinical spaces, evaluation efforts of AI models, how the workers supporting the healthcare system and delivering care at all levels of the institution have changed, and challenges that remain.

Yin Aphinyanaphongs, MD, PhD
Director, Operational Data Science and Machine Learning for NYU Langone Health
Assistant Professor
Center for Healthcare Innovation and Delivery Science
Department of Population Health
NYU Langone Health

9:00am – 9:45am
Ethical Implications of Artificial Intelligence/Machine Learning in Healthcare

This interactive talk highlights and dives deep into the ethical issues and controversies surrounding the implementation of artificial intelligence/machine learning in healthcare. It includes such important topics as algorithmic/model bias, medical error and liability in the setting of AI, trust, explainability and transparency, effects on the patient-clinician relationship, data privacy, and erosion of clinician skill. Attendees will learn to identify major ethical issues regarding AI implementation and discuss the current and future mitigation strategies for these problematic issues.

Hamilton Baker, MD
Associate Professor of Pediatrics and Public Health
Medical University of South Carolina
Director
Clemson-MUSC AI Hub
Medical University of South Carolina 

9:45am – 10:15am
Networking & Refreshments Break

10:15am – 11:00am
From AI Winter to AI Spring in Radiology Service

The radiology community began to develop computer-aided diagnosis (CAD) software systems in the 90s as soon as radiological images became digital. A convolution neural network (CNN) became a popular concept for pattern recognition research among medical imaging scientists. Their interests then were in computers aiding the radiologists in diagnosis. Then the public’s fascination and hype of artificial intelligence (AI) change the conversation of AI replacing radiologists. There have been more than 100 FDA-approved AI imaging products. However, clinical adoption of these AI products has been limited to a handful of cases disappointing the developers. Some wonder if we are facing "AI winter" similar to the situation the AI technical community faced in the 1980s. As AI is a vast collection of powerful capabilities, as we just began to experiment with a small portion of AI tools, most of us believe the AI winter will turn to “AI spring" when we can match AI tools to solve the meaningful problems of end users. One of the critical factors of AI adoption in radiology community will be productivity improvement to address persistent financial pressure from the payers as a part of the health care payment reform in the US. We envision two pathways of AI spring. The current AI science and technology are not optimized for medical images. More basic research will be required to deal with subtleties of medical diagnosis with the context of nature of disease that may not be visible. Advances in radiomics also known as quantitative imaging will help improve the performance of AI products.  Integration of emerging AI products for diagnosis and productivity improvement to radiology workflow will require a new IT infrastructure. The current IT platform of radiology, the picture archiving and communication system (PACS), is a centralized architecture of past generations. We need a distributed intelligence management system (IMS) with similar functionalities to edge computing. This evolution of digital transformation in radiology will require collaboration between academia for better solutions and industry for IMS.

Seong K. Mun, PhD
Professor and Director
Arlington Innovation Center: Health Research

Virginia Tech

11:00am – 11:45am
Healthcare Cybersecurity – The Impact of AI, IoT-Related Threats and Recommended Approaches

Artificial intelligence (AI) applications in healthcare are all the rage now, and so are cybersecurity threats, given the frequency and intensity of healthcare-related incidents. In particular, some of the cyberattacks have become more sophisticated through the use of AI to get past cyber defenses. On the medical devices front, AI is also being used to constantly manage and secure the rising number of healthcare IoT devices as they connect and disconnect from hospital networks. I will be presenting the application of AI in healthcare cybersecurity and what it will be like in the next few years.

Michael Archuleta
Chief Information Officer
HIPAA and Information Security Officer
Mt. San Rafael Hospital 

11:45am – 12:30pm
AI in Medicine is Not Optional – Solutions Through Challenges

AI and machine learning have been through several summers and winters.  The current cycle had some experts predicting the obsolescence of certain specialties within five years.  These predictions underestimated the complexity of the practice of medicine and patient care and, of course, have not been realized.  Issues such as data quality, bias, inequity, the opaque box problem still drive skepticism. On the other side, an increasing volume of health data is being generated and presented to providers every day, leading to data overload and waste.  Millions of medical errors occur annually in the US alone, resulting in an estimated 250000 deaths per year.  These problems are even more pronounced globally. While overpromises of AI have not been fully delivered, and ethical challenges remain, a practical pathway in the middle must be sought and followed for improved care. From a technology viewed with suspicion as claims touted it as the replacement for medical professionals, AI has evolved to become a human-machine partnership.   Its potential is beginning to be realized, albeit slowly.  Some AI tools are starting to help diagnose stroke and cancer, triaging critical findings in medical imaging, flagging acute abnormalities and prioritizing life-threatening cases, predicting risk of future cardiac arrhythmias, and helping with the management of chronic diseases.  This session will explore how artificial intelligence in medical diagnosis (despite challenges) has shown promise for improving medical care by potentially helping manage data overload and reducing data waste and errors.  It can also help minimize provider fatigue and increase efficiency.

Aalpen A. Patel, MD, MBA
Chair, Department of Radiology
Medical Director of AI
Geisinger and Steele Institute for Health Innovation 

12:30pm – 1:30pm
Luncheon

1:30pm – 2:15pm
Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity

The introduction of new, disruptive technologies and innovations may bring significant benefits for patients including enhanced quality of life and more efficient care. Innovations in clinical practice give healthcare providers the opportunity to improve the effectiveness and quality of the care they provide and to apply safer treatment while at the same time improving their job satisfaction. Healthcare and technology innovators are collaborating and trying to change our current reality by experimenting with artificial intelligence and machine learning technologies. Computers and the algorithms they run can scrub colossal amounts of data—much faster and more accurately than human scientists or medical professionals—to unearth patterns and predictions to enhance disease diagnosis, inform treatment plans and enhance public health and safety. This session will explore the expectations of the health sector toward the use of AI and machine learning with the risks that should be mitigated for its responsible deployment. A systematic approach to the evaluation of technology, AI and Machine learning in healthcare is needed if we are to reliably discriminate between useful innovation and clever marketing. This session will provide guidance to any individual or organization wishing to take control of the conversation and to objectively evaluate a technology on their own terms.

Vitaly Herasevich, MD, PhD
Professor Anesthesiology and Medicine
Department of Anesthesiology and Perioperative Medicine, Division of Critical Care
Mayo Clinic 

2:15pm – 3:15pm
Panel: Smart Use of AI in Healthcare

Artificial intelligence is already delivering on making aspects of healthcare more efficient. Over time it will likely be essential to supporting clinical and other applications that result in more insightful and effective care and operations. AI has multiple use cases throughout health plan, pharmacy benefit manager, and health system enterprises today, and with more interoperable and secure data, it is likely to be a critical engine behind analytics, insights, and the decision-making process. Enterprises that lean into adoption are likely to gain immediate returns through cost reduction and gain competitive advantage over the longer term as they use AI to transform their products and services to better engage with consumers. AI-enabled solutions can provide immediate returns through cost reduction, help with new product development, and lead to better consumer engagement. This session will explore how healthcare organizations can scale up their AI investments by pairing with a robust security and data governance strategy.

Panelists:

David Ledbetter
Principal Data Scientist and Manager, Virtual Pediatric Intensive Care Unit
Children's Hospital of Los Angeles 

Justin Smith, PhD
Senior Director Advanced Analytics
St. Luke’s Health System 

Additional panelist TBA

3:15pm – 3:45pm
Networking & Refreshments Break 

3:45pm – 4:30pm
Data Scientists are from Mars, Clinicians are from Venus
There are astronomical distances dividing the clinical and data science teams. Most importantly, the languages spoken by either group is barely recognizable to the other. Pressors or fluids or Lasix, oh my. Clinicians think about solving problems in terms of how solutions fit into a clinical workflow and ease of use (how many clicks do i need to make in the EMR?) whereas data scientists are often concerned about esoteric error functions like ROCs or the technical novelty of an algorithm (will I be able to submit this to NeurIPS?). Without the ability to communicate with each other there is a world of problems which cannot be overcome. Approaching these problems will require both mindsets working together.

David Ledbetter
Principal Data Scientist and Manager, Virtual Pediatric Intensive Care Unit
Children's Hospital of Los Angeles 

4:30pm – 5:15pm
Shifting the Paradigm Toward Delivering Value with AI in Healthcare

Healthcare providers everywhere are put under unprecedented pressure by the pandemic to make sense of their work in ways that put patients and members first, at scale, while working within already challenging and complex work environments. Healthcare workers are currently facing two pivotal systemic developments: COVID has rapidly accelerated the global digital transformation toward a digitized, data-driven future of work, and there is an ever-increasing adoption of value-based models of care. The pivot to a proactive approach with COVID allowed vulnerable members to be outreached first and establish an operationalized process to meet the needs of members. Thousands of members have been part of outreach programs that have identified member needs with loneliness and isolation, medication access, meeting basic needs and managing health conditions where interventions and programs have been established to meet those member needs.  This session will explore how having all the facets of AI baked into health systems and processes from the outset and not as an afterthought is a pivotal driver of positive change and action.

Sam Garas
Associate Vice President | Information Technology
Healthcare Services
Humana

5:15pm
End of Day One

Day Two – Friday, , June 24, 2022

7:15am – 8:00am
Networking Breakfast 

8:00am – 8:10am
Chairperson’s Remarks 

8:10am – 8:50am
In AI We Trust: Navigating the Chasm Among Administrators, Nursing and Innovation
In order to facilitate trust and successful adaptation, we must bridge the gap between the language of AI and the clinical language of our nursing and administrative colleagues. The concepts and terminology that pepper conversations regarding the technological potential of artificial intelligence for the future of patient care are a foreign language to the very individuals that invest in and implement them. We must translate the language of machine learning, artificial, surgical and augmented intelligence, robotics, and automation, to a common or clinical language that resonates with the language of caring. Caring intelligently allows AI to become a trusted partner in solving real-world problems faced by clinicians today.

Karen B. Seagraves, PhD, MPH, NEA-BC, APRN, FAHA
Enterprise Vice President, Neurosciences
Atrium Health 

8:50am – 9:30am
AI and COVID-19
Current healthcare delivery uses the newer technologies of Artificial Intelligence (AI), Big Data and Machine Learning to predict, analyze, prepare and prevent pandemics. Commercial clinical artificial intelligence platforms are being used in the war on Covid-19. The Covid-19 pandemic has affected many systems of care. Time sensitive conditions such as stroke, and coagulopathy (high coagulation assay results on patients) remain poorly quantified. We evaluated the impact of Covid-19 in the screening of patients with Coagulopathy and stroke where commercial clinical artificial platforms were used. We looked specifically at PCR assays and their Cycle Threshold Ratios for Covid-19 and computerized tomography (CT) scans for clots leading to strokes.

Ghazala Nathu, MD, MS, PhD, FACB
Medical/Molecular Laboratory Director of Clinical Pathology
Director of Point of Care
Blood Bank/Tissue Compliance Officer
Bassett Healthcare Network – Cobleskill Regional Hospital

9:30am – 10:00am
Networking & Refreshments Break 

10:00am – 10:40am

Anthony C. Chang, MD, MBA, MPH, MS
Chief Intelligence and Innovation Officer
Medical Director, The Sharon Disney Lund Medical Intelligence and Innovation Institute (MI3)
Children's Hospital of Orange County

10:40am – 11:20am
Computer Vision Machine Learning for Patient Safety in the ICU
Preventable harm in healthcare delivery is a major source of human suffering, death, disability, and cost. Two decades of focused effort have failed to yield adequate progress. One challenge is that humans are relatively poor at tasks which require sustained vigilance in order to detect developing problems and intervene in time to prevent an adverse outcome. Electronic alarms and informatics-based alerts are incomplete solutions. An emerging solution is the application of computer vision to support vigilance-intensive tasks. The intermediate step of pairing computer vision with human intelligence has become well established but this is difficult to scale. The next step of pairing computer vision with artificial intelligence is becoming established. I will discuss the basis of this technology and describe its application to address preventable harm in a critical care environment. I will then discuss the potential to scale this technology and apply it to other clinical challenges.

Bill Beninati, MD, FCCM
Critical Care – Intermountain LDS Hospital
Senior Medical Director for Intermountain
TeleHealth Services
Patient Placement and Transfer
Life Flight/Classic Air Medical
Intermountain Healthcare 

11:20am – 12:00pm
How the Combination of AI and RPM Is Driving Patient Outcomes
Remote patient monitoring (RPM) is quickly establishing itself as one of the most effective tools for chronic disease management. RPM is the collection and transmission of patient health data to providers via connected devices outside of a conventional care setting. With the combination of RPM and AI, a care team can identify a chronic disease patient’s increase in risk and accurately anticipate potential complications. AI can also help identify potential care pathways in combination with technology and bring better health outcomes for patients.

Rahul Goyal
Senior Director
UnitedHealth Group 

12:00pm – 12:45pm
Luncheon 

12:45pm – 1:25pm
Key Challenges for Delivering Clinical Impact with Artificial Intelligence
AI in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed into clinical practice. This session will explore the main challenges and limitations of AI in healthcare, and considerations of the steps required to translate these potentially transformative technologies from research to clinical practice.

GQ Zhang, PhD
VP & Chief Data Scientist, Office of Data Science (ODS)
Co-Director, Texas Institute for Restorative Neurotechnologies (TIRN)
Professor of Medicine, Biomedical Informatics, Public Health
The University of Texas Health Science Center at Houston  

1:25pm – 2:25pm
Panel: Transforming Healthcare with AI
Artificial intelligence has the potential to transform how healthcare is delivered. This session will explore how it can support improvements in care outcomes, patient experience and access to healthcare services. It can increase productivity and the efficiency of care delivery and allow healthcare systems to provide more and better care to more people. AI can help improve the experience of healthcare practitioners, enabling them to spend more time in direct patient care and reducing burnout.

Panelists:

Michael Archuleta
Chief Information Officer
HIPAA and Information Security Officer
Mt. San Rafael Hospital 

Devang Sanghavi, MD, MHA, FCCP
Vice Chair of Practice, Critical Care Medicine
Director, Medical Intensive Care Unit
Chair, Sepsis Work Group
Assistant Professor of Medicine
Mayo Clinic 

Karen B. Seagraves, PhD, MPH, NEA-BC, APRN, FAHA
Enterprise Vice President, Neurosciences
Atrium Health 

Abhay Shukla
Senior Director, Advanced Analytics Solutions
UnitedHealth Group 

2:25pm – 3:10pm
Considerations for Pediatric Patients in the Use of Artificial Intelligence in Healthcare
Pediatric patients are recognized having unique needs in healthcare. Currently, Artificial Intelligence applications are rapidly being developed. Specifically, in medical imaging, there are now multiple tools in use, but nearly all have been designed exclusively for use in adults. Here, the objectives are to describe why AI tools developed for adults may not perform well in children, to list reasons why developing AI for use in children is challenging, and to illustrate use cases where health equity could be improved if AI is developed for pediatric applications.

Marla Sammer, MD, MHA, FAAP
Vice Chair of Clinical Affairs, Department of Radiology
Texas Children’s Hospital

3:15pm
Conference Concludes

Workshop - Friday, June 24, 2022

12:45pm – 2:45pm
Cybersecurity Incidents: Automation and AI to the Rescue
This workshop will cover how an entity, such as any healthcare provider, can leverage the benefits of incident-response automation. Cybersecurity incidents are one of the most common risks and one of the most devastating. Learn how automation can join privacy, cybersecurity, and investigations teams into a coherent, defensible, and efficient response to these critical events. We will also cover how AI can be used, ethically and responsibly, as a part of every cybersecurity program. 

Paul Starrett
CEO
Starrett Consulting, Inc.

Featured Speakers

Hamilton Baker, MD

Hamilton Baker, MD

Associate Professor of Pediatrics and Public Health

Medical University of South Carolina
Director
Clemson-MUSC AI Hub
Medical University of South Carolina

Michael Archuleta

Michael Archuleta

Chief Information Officer

HIPAA and Information Security Officer
Mt. San Rafael Hospital

Aalpen A. Patel, MD, MBA

Aalpen A. Patel, MD, MBA

Chair, Department of Radiology

Medical Director of AI
Geisinger and Steele Institute for Health Innovation

Vitaly Herasevich, MD, PhD

Vitaly Herasevich, MD, PhD

Professor Anesthesiology and Medicine

Department of Anesthesiology and Perioperative Medicine, Division of Critical Care
Mayo Clinic

Yin Aphinyanaphongs, MD, PhD

Yin Aphinyanaphongs, MD, PhD

Director, Operational Data Science and Machine Learning for NYU Langone Health

Assistant Professor
Center for Healthcare Innovation and Delivery Science
Department of Population Health
NYU Langone Health

Ghazala Nathu, MD, MS, PhD, FACB

Ghazala Nathu, MD, MS, PhD, FACB

Medical/Molecular Laboratory Director of Clinical Pathology

Director of Point of Care
Blood Bank/Tissue Compliance Officer NYSDOH
Bassett Healthcare Network – Cobleskill Regional Hospital

GQ Zhang, PhD

GQ Zhang, PhD

VP & Chief Data Scientist, Office of Data Science (ODS)

Co-Director, Texas Institute for Restorative Neurotechnologies (TIRN)
Professor of Medicine, Biomedical Informatics, Public Health
The University of Texas Health Science Center at Houston

 

Rahul Goyal

Rahul Goyal

Senior Director

UnitedHealth Group

Bill Beninati, MD, FCCM

Bill Beninati, MD, FCCM

Critical Care – Intermountain LDS Hospital

Senior Medical Director for Intermountain 
TeleHealth Services
Patient Placement and Transfer
Life Flight/Classic Air Medical
Intermountain Healthcare

Marla Sammer, MD, MHA, FAAP

Marla Sammer, MD, MHA, FAAP

Vice Chair of Clinical Affairs, Department of Radiology

Texas Children’s Hospital

Seong K. Mun, PhD

Seong K. Mun, PhD

Professor and Director

Arlington Innovation Center: Health Research
Virginia Tech

David Ledbetter

David Ledbetter

Principal Data Scientist and Manager, Virtual Pediatric Intensive Care Unit

Children's Hospital of Los Angeles

Justin Smith

Justin Smith

Senior Director Advanced Analytics

St. Luke's Health System

Sam Garas

Sam Garas

Associate Vice President | Information Technology

Healthcare Services
Humana

Karen B. Seagraves, PhD, MPH, NEA-BC, APRN, FAHA

Karen B. Seagraves, PhD, MPH, NEA-BC, APRN, FAHA

Enterprise Vice President, Neurosciences

Atrium Health

Anthony C. Chang, MD, MBA, MPH, MS

Anthony C. Chang, MD, MBA, MPH, MS

Chief Intelligence and Innovation Officer

Medical Director, The Sharon Disney Lund Medical Intelligence and Innovation Institute (MI3)
Children's Hospital of Orange County

Devang Sanghavi, MD, MHA

Devang Sanghavi, MD, MHA

Vice Chairman, Clinical Practice, Critical Care

Mayo Clinic

Abhay Shukla

Abhay Shukla

Senior Director, Advanced Analytics Solutions

UnitedHealth Group

Paul Starrett

Paul Starrett

CEO

Starrett Consulting, Inc.

Venue

or Bellagio
3600 Las Vegas Blvd. S
Las Vegas, NV 89109
702-693-7111

Mention BRI Network to get the discounted rate of $169/night or use link below:

https://book.passkey.com/go/SBRI0622BE

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FAQ

Are there group discounts available?

  • Yes – Register a group of 3 or more at the same time and receive an additional 10% off the registration fee

Are there discounts for Non-Profit/Government Organizations?

  • Yes – please call us at 800-743-8490 for special pricing

What is the cancellation policy?

  • Cancellations received 4 weeks prior to the event will receive a refund minus the administration fee of $225. Cancellation received less than 4 weeks prior to the event will receive a credit to a future event valid for one year.

Can the registration be transferred to a colleague?

  • Yes – please email us in writing at info@brinetwork.com with the colleague’s name and title

Where can I find information on the venue/accommodations?

  • Along with your registration receipt you will receive information on how to make your hotel reservations. You can also visit individual event page for specific hotel information. The conference fee does not include the cost of accommodations.

What is the suggested dress code?

  • Business casual. Meeting rooms can sometimes be cold so we recommend a sweater or light jacket
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