BIG DATA & HEALTHCARE ANALYTICS: A HIMSS EVENT
SAN FRANCISCO, CA - MAY 15-16, 2017
Breakfast will be served in the Grand Ballroom so make sure to stop by the sponsor tables.
After decades of lagging behind other industries in the use of data, healthcare is poised for its own data-driven transformation. Journalists describe a not-too-distant future where patients, phones, Fitbits, and physicians march hand-in-hand toward a healthier tomorrow.
But not everyone is jumping for joy.
Some healthcare organizations are so frustrated with the state of health IT that the American Medical Association’s CEO James Madara, MD, last year called digital health the “snake oil of the early 21st century.” Rather than improving care and boosting professional satisfaction, many digital tools, he wrote, don’t work that well, and actually impede care, confuse patients, and waste everyone’s time.
And then there’s machine learning. Or is it artificial intelligence? Or cognitive computing? Which is which or what is what?
In his keynote, Harvard Medical School professor Leonard D’Avolio, who previously led informatics at the VA, gets to the bottom of all this confusion and disgruntlement and examines what’s hype and what’s not. And how together, once a few very real barriers are eliminated, big data and machine learning will better serve doctors, patients and families, and contribute to improved healthcare.
In today's healthcare climate, monetizing your data is critical to success. Healthcare data organizations need to start putting the hard-won data trapped in their systems to use in decision making. The demand for real time data means more and more health systems are putting big data technology behind all of their reports and analytics, allowing them to combine sources to create actionable insights that help improve service line operations, advance clinical performance, identify new markets and opportunities, and drive patient and provider satisfaction. In this Executive Spotlight, learn how high performance data platforms can help make your health system more competitive.
Key takeaways include:
The U.S health care systems broad adoption of EHRs has dramatically increased the quantity of clinical data available electronically. Simultaneously, rapid progress has been made in clinical analytics—techniques for analyzing large quantities of data and gleaning new insights from that analysis. This is all part of the big data “revolution.” As a result, there are unprecedented opportunities to use big data to reduce the costs of health care in the United States.
But what exactly are those opportunities, and how are big data and analytics changing the delivery of care as we know it?
In this opening leadership discussion, our distinguished panel of healthcare data experts discuss the insights likely to emerge from clinical analytics, the types of data needed to obtain such insights, and the infrastructure—analytics, algorithms, registries, assessment scores, monitoring devices, and so forth—that organizations will need to perform the necessary analyses and to implement changes that will improve care while reducing costs
Take this opportunity to mingle with your peers in a relaxed setting to build relationships and establish future partnerships. Coffee will be served and make sure to stop by our sponsor tables.
The MetroHealth System became the first public, essential health system ever with the Epic EHR to achieve Stage 7 in the HIMSS electronic medical record adoption model (EMRAM) in both its inpatient hospital and all of its ambulatory clinics.
Not staying static though, MetroHealth recognized the need to leverage its investments in analytics and technology to improve the quality of care and financial outcomes by forming a new department known as DORA - the Department of Operational Research and Analytics. DORA is about finding new ideas in data and becoming a best-in-class user of data. It has begun to enable MetroHealth to progress from data to information to knowledge to wisdom. MetroHealth’s Department of Operational Research and Analytics (DORA) has introduced new technologies to help administrators and clinicians better understand the forces that drive their business. The data gleaned from this intelligence is being used to implement changes that aid in better overall operations.
The road to healthcare transformation is a far cry from a smoothly-paved highway. With interoperability potholes, regulatory detours and reimbursement construction, healthcare organizations often struggle to know the best route forward. A proper data strategy and analytics roadmap is essential for successful navigation along the changing healthcare landscape.
In this session you will learn what is needed to develop an effective roadmap to value-based care. Common pitfalls will be identified and strategies for success will be presented. While healthcare transformation won’t be easy, today’s technology will make it possible.
Creating and deploying powerful information through technology and analytics is essential in the journey to value-based care. Yet, ensuring an organization has the right supporting tools, processes, technology, people, organizational structure, critical source systems and advanced analytics capabilities to support value-based care is no easy task; it also requires leadership adoption, readiness, accountability, incentive alignment, and a data-driven decision making culture.
This session will highlight one organization’s applied analytics journey as they developed a scalable, effective, and efficient analytics roadmap for a multi-hospital’s analytics programs, development of a data governance model and moving to value-based care. This will include experiences from the Medicare capitated model in the Maryland reimbursement market.
Take this opportunity to mingle with your peers in a relaxed setting to build relationships and establish future partnerships. Coffee will be served in the exhibit area so make sure to stop by our sponsor tables.
A recent study by the Healthcare Center for Excellence revealed that lack of leadership was the greatest challenge to implementing healthcare analytics and now more than ever, we need leaders who are well-versed in all aspects of leadership. Unfortunately, the skills that made healthcare leaders successful in the past may not be enough to be successful in the future. Managing change requires a very special set of skills.
What is billed as leadership skill development today is usually missing key components that could limit the leader’s effectiveness. This presentation will examine why most current leadership development models fail and what is needed to create “professional” leaders. It will explain why leadership is a process that must be prescribed like a maintenance drug and practiced every day using the same approach taken by professional athletes worldwide for decades.
The post-acute world is becoming fundamental to a hospital’s success in creating a patient-centered, longitudinal network of care. Like the rest of the industry, these organizations are under scrutiny to drive quality outcomes. And in a changing competitive landscape, skilled nursing facilities, home health, assisted living and long term care organizations are looking for ways to differentiate themselves, drive better care, and reduce the number of adverse events within their patient populations.
In this session, Terry Sullivan, MD, the chief medical officer for OnPointe, a large provider of post-acute care services, examines the roll that predictive and artificial intelligence driven solutions play in driving market differentiation and care quality for post-acute providers. Dr. Sullivan will examine the predictive use cases that best support quality goals and how AI applications can drive better investment and operational decisions to enable greater market share. We will also discuss the challenges with predictive analytic adoption within a market that is lagging in HIT adoption.
List the major changes that are impacting the post-acute provider segment including increased competition, mandates, payment models.
Discuss the key ways in which predictive analytics can drive value for post-acute providers in terms of competitive advantage.
Summarize the points along the post-acute care continuum where predictive analytics are most relevant and effective.
Siemens Healthineers is a leader in imaging and lab diagnostic equipment and associated services. Data-driven analytics and solutions in these areas offer great opportunities to positively impact the health of populations, and to optimize the cost of delivery of health care, both at the health system level, and the departmental level. Siemens Healthineers offers a digital ecosystem providing application developers with secure, compliant access to providers and their data, through which solutions can be offered to standardize care delivery, removing unwarranted variability, and through which care gaps related to diagnostic errors or oversights can be uncovered and closed.
Take this opportunity to mingle with your peers in a relaxed setting to build relationships and establish future partnerships. Coffee will be served in the ballroom so make sure to stop by our sponsor tables.
According to the Agency for Healthcare Research and Quality, nearly 1,000,000 patients in the U.S. fall in the hospital each year. The Joint Commission Center for Transforming Healthcare also indicates that patients who sustain an injury from a fall add 6.3 days to the hospital stay and cost around $14,000.
Fall prevention methodology is reactive in nature – most fall assessments lack patient context in real time. However, prescriptive analytics represents a true solution by enabling proactive care management based on key patient-centered factors– including historical falls data, fall risk assessment, and bed exit alarms.
Cheryl Reinking, CNO, will detail how El Camino Hospital, a 420-bed California hospital, transformed its fall prevention program and used prescriptive analytics to ensure patients were being proactively and optimally managed. Reinking will also explore the need to go beyond traditional “predictive analytics” into action-focused insights that allow providers to immediately respond and impact patient safety.
Through analytics, the care team was able to predict exactly which patients were at risk for an imminent fall, and alerted case managers of at-risk patients in real-time, which resulted in a 39% reduction in falls within 6 months.
All eyes these days are on technology as the means to drive down costs and improve efficiency, and, especially, to enable physicians to deliver care in a way that realizes the vision of a healthier planet.
Of course, this is easier said than done. The transition from the traditional focus on acute care to the quality and data-driven organizations of tomorrow requires incredible effort and collaboration between all members of the healthcare community. And physician engagement with the whole community has never been more important.
In this session, health IT thought-leader Leigh Williams, administrator for business systems at the University of Virginia Health System, distills valuable best practices from her book (co-written with physician informaticist John Showalter), Mastering Physician Engagement: A Practical Guide to Achieving Shared Outcomes.
In her engaging and informative style, Leigh will explore strategies and tactics for engaging physicians in a meaningful way in a broad spectrum of change initiatives. Using proven techniques to create alignment with physicians, Leigh will deliver practical approaches for effectively:
There are two main approaches to machine learning – supervised and unsupervised – and each has specific applications in the context of healthcare. And even though their impact has not yet sent shockwaves through the industry, the potential of each is enormous.
At its basic level, machine learning involves looking at data, and from that data finding information that is not readily visible. Example: Applying machine learning to data about patients infected with Zika or another virus and using what we can learn about what happens to those people to inform care decisions regarding the best ways to treat people who get infected in the future.
As healthcare entities continually ramp up their analytics and big data efforts and gird for precision medicine and population health, machine learning as well as artificial intelligence and cognitive computing are poised to become even more valuable.
After a day of informative and incisive presentations, enjoy a drink and hors d'oeuvres in the Grand Ballroom with your fellow attendees, speakers and sponsors.