HAS 21 Virtual Agenda Overview

These are actual headlines from national Australian newspapers.  Learn how Marita Cheng went from a small-town girl living in government housing to conquering the globe as one of Forbes Top 50 Women in Tech in the World, and the second youngest person to become a Member of the Order of Australia (like a junior knighthood).  Noticing the limited number of girls in her engineering class, at the age of 19, Marita founded Robogals to inspire girls into robotics, growing the organization into an international movement.  She followed that up with artificial intelligence company Aipoly to help the blind identify objects in real-time, which resonated with millions of people.  And robotics company Aubot, making robots to help people in their everyday lives.  Hold on tight as pocket rocket Marita shares how she changed the world.

Key Takeaways:

• The only failure is failure to try
• Do your best at what’s in front of you, and more opportunities will present themselves
• Solve real problems
• Keep it really simple

What do you get when you combine rubber circles, x-ring metal segments, hub and spoke cylinders, hand levers, and highly flammable liquid? With the right combination of parts and expertise for functional design, the sum of the parts turns into something wholly novel: a Yamaha WR250f dirt bike.

Healthcare systems can benefit from a reconfiguration of data, tools, technology, and analytic skill to drive their organization into uncharted territory with confidence and agility. The result: data-driven, integrated systems of success.

Join us for another humorous, memorable, and insight-filled session where once again John Wadsworth uses a simple analogy to drive home salient points in how to systematize healthcare analytics.

In this session, you will:

• Rethink your tech (and other) investments around the quadruple aim.
• Better understand how to measure and derive value.
• Increase appreciation for the power of analytic integration in healthcare delivery.
• Have fun, learn, and remember at the same time.

As the number of employed physicians climbs, even exceeding those in private practice (2018 AMA), ambulatory practice management is an area of increasing difficulty at nearly every health system. Manual and siloed reporting and lack of governance can cause incredible waste.

Learn how CHNw, a health system with more than 200 sites of care and a $300M investment in physician practices, tackled this problem by developing a comprehensive practice management application comprising modules for each reporting area: panel management, access, productivity, quality, patient satisfaction, and staffing/practice services. Improvements included reduction of 2 FTEs (for manual reporting) and improved panel management with early identification of patients falling off panels.

Participants will discover:

• Why operational engagement is critical and why analytic insights are not intuitive to operational leaders.
• What takes the most time in application development for systemic improvement.
• Why mobile development is key to adoption and utilization of a management application.

As new value-based care models continue to be released by Medicare and CMMI, the ecosystem of innovation in the space continues to grow. Learn about one model that is delivering novel, home-based care to Medicare patients through full risk value-based care contracts. By delivering in-home medical and behavioral care, enhanced by proprietary care pathways, advanced analytics, and virtual care technology, this model has shown where the next generation of care delivery models are headed. This presentation will also touch on other care providers and technology offerings in the space that are changing the lives of Medicare patients, improving their outcomes, and lowering the cost of their care.

Participants will discover:

• The latest value-based care models being released by Medicare/CMMI.
• How to best leverage analytics to optimize the outcomes of Medicare patients.
• Lessons learned and how to apply them to your organization.

Failure to improve charge capture integrity can lead to millions in revenue leakage, compliance issues, incorrect billing, and frustrated patients. MultiCare Health System’s executive director of revenue integrity and charge description master will share how the organization is using charge capture analytics solutions to meet its revenue integrity goals. This session will review how revenue reconciliation efforts, workflow redesign, and audits result in the rapid identification and resolution of charge capture errors, ensuring compliance and accelerating revenue recognition.

Participants will learn:

• How to leverage analytics to build a robust charge audit program.
• How to detect and remedy charge compliance issues.
• How to decrease revenue leakage.

1. The Data Revolution:  aggregating and interpreting data and using machine learning and AI will allow for improved and targeted health offerings, bolstering wellness and retention
2. Behavior Change:  virtual care is here to stay with more frequent touchpoints, lower costs, and better care.
3. Productizing Healthcare Delivery:  at-home devices and diagnostics have shifted the product environment away from a singular focus on wellness to prevention.
4. Transforming Communications:  the consumption of health information is shifting from traditional vehicles to new vehicles like social media.  The way we communicate must adapt and change in parallel

A good predictive model alone won’t yield real-world outcomes. To achieve results, organizations must pair predictive models with effective interventions and delivery tools. In this session, representatives from Texas Children’s Hospital, the largest pediatric hospital in the U.S., will describe a framework for effective predictive model implementation in clinical practice, featuring the organization’s custom Pediatric Readmissions model. By accurately flagging 20 percent of patients as potential readmissions, Texas Children’s was able to apply early interventions and reduce potential readmissions by 5 percent.

Participants will learn:

• The value predictive models add to clinical decision making.
• The tools and interventions needed to maximize predictive models.
• How to effectively implement predictive models in clinical practice.

Facing unprecedented challenges related to the COVID pandemic, Texas Children’s Hospital leveraged patient-facing technology to pivot to a new definition of patient access. Discover how Texas Children’s enhanced the digital patient experience and journey, fostered a zero-touch care environment and ensured continuity of care across various care settings.
This session will detail the people, processes, and technology changes that led to:

• More than 100K appointments scheduled online.
• 68K unique patients with telemedicine visits.
• An 8% increase in patient satisfaction.
•  Nearly $1M in cost savings.

Participants will learn:

• What strategies are used to identify digital technology opportunities.
• How to address internal and external change management concerns to drive adoption of new digital technologies.
• How to ensure continuity of safe, high-quality patient care through virtual technology and in-clinic enhancements.

With limited resources and rapidly growing COVID-19 patient volumes, accurate and rapid identification of individuals at the highest risk of hospitalization is a top priority. To identify and target interventions towards high-risk patients, ChristianaCare leveraged a cloud-based data platform and analytics applications, including data science tools and predictive analytics, to generate a risk score for each patient testing positive for COVID-19. Join this session to learn how up-to-date risk identification helped the organization make data-informed resource allocation decisions and enroll patients in the appropriate care management program, avoiding 61 hospital admissions and 7 intensive care unit admissions and avoiding $1.8 million in cost.

Participants will learn:

• What risk prediction tools were used.
• How up-to-date risk identification helped the organization make timely, data-informed decisions.
• What interventions were used to avoid hospital and ICU admissions.

To effectively manage cost, healthcare leaders need the right data, provided to the right people, at the right time. UPMC first integrated patient- and physician-level analytics to gain better insight into operating costs and clinical variation across its provider footprint. More recently, they assessed their existing labor budget and productivity system, a decades-old, homegrown tool with outdated functionality and limited reporting on FTEs. Recognizing the opportunity for an improved solution, UPMC launched integrated department- and leader-level labor budget and productivity analytics, putting invaluable staffing and productivity information into the hands of operational leaders across its many hospitals.

Goals of this session:

• Understand the current challenges facing providers, including horizontal competition from large insurers and digital disrupters, headwinds from price transparency, and growth in managed care programs, like Medicare Advantage.
•  Introduce a new approach to cost transformation, utilizing existing EHR data to create patient- and physician-level costing, and measuring clinicians based on value and the “Triple Aim.”
• Identify the elements of an effective labor budgeting and productivity solution, including key functionality for finance and operational users.
• Describe how data at the right grain increases the accuracy of analytics—and results in actionable improvements.
• Articulate the keys to success for labor analytics, including in-depth analysis of historical operations and staffing, consistent training and documentation, and engagement of key operating teams across the organization.

AI-based virtual assistants are evolving quickly. Now, increasingly more effort and resources are being put toward making them emotionally intelligent – able to pick up on subtle cues in speech, inflection, or gesture and expression to assess a person’s health and well-being. Nurse avatars and social robots – such as Catalia Health’s Mabu, an emotion-aware personal care companion for terminally ill patients – are already proving their abilities to enhance patient-centered health care environments around the world, making routine processes more efficient, and improving experiences and outcomes. But their full potential is even more profound and far from realized, believes Dr. Rana el Kaliouby.

Emotion AI, she says, provides an opportunity to transform numerous aspects of health and well-being, from telemedicine and drug efficacy to mental health research and autism support. By reading into a vocal tone or detecting facial expressions, for example, emotion AI-enabled platforms could detect depression or even potentially underlying chronic conditions, such as heart disease. In telemedicine, mood-aware wearables could contribute to monitoring mental health and well-being, perhaps helping those with depression track their emotional state and share that data with their doctor.

Data governance often has negative connotations, such as contention, complexity, or tedium. In addition, the challenges associated with effective data governance, including breaking down long-existing data silos, a lack of trust in the data, and executive buy-in, can further thwart progress. There are, however, better ways to perform healthcare data governance. Join this session to learn how proven approaches and a shared vision for data governance allow health systems to maximize data, their greatest asset.

Participants will learn:

• The common pitfalls of data governance and how to address them.
• How to use the momentum from the data procurement stage to develop an effective data governance strategy.
• The positive results health systems can achieve from effective data governance.

While The University of Kansas Health System embarked on its data transformation journey in 2014, the health system needed to better leverage its data platform, analytics tools, and team to more rapidly improve their performance and the quality and speed of decision making in the organization. Specific objectives included understanding and improving the organization’s performance in safety, quality, effectiveness, efficiency, equity, access, and patient experience. Over three fiscal years, the organization has observed quality improvements in many areas, including a 0.69 O/E mortality rate for patients admitted to the hospital, $2.3 million in savings by reducing readmission rates, a 22.5 percent reduction in clostridioides difficile, and a 26 percent reduction in initial denials.

Participants will learn:

• How to improve the use of data and analytics.
• How to push data to the bleeding edges of the organization to achieve revenue, cost, and quality improvements.
• What tools, resources, and data team skills were used to achieve their improvement goals.

Hidden opportunities can be found among health systems and other risk-bearing entities to improve the quality and decrease the costs of providing healthcare to at-risk patient populations. Discover how Health Alliance, a vertically integrated health system with a health plan and population health organization, found and maximized these opportunities by breaking down the barriers between entities to accomplish two fundamental goals:

• Implement a system-wide structure to manage sustainable population health efforts.
• Develop and implement a population health care model that improves the quality and reduces costs associated with a fully at-risk (capitated) population.

Early reviews of the population data, even accounting for the impact of COVID-19, show a 30 to 40% reduction in ED utilization and 27% decrease in readmissions. Data supports a 2.8:1 return on investment.

Participants will learn:

• Where population health staff must be embedded to make the biggest difference.
• What goals matter most when creating scalable population health programs.
• How program value can be proven even during utilization changes (such as those caused by COVID).

Medical claims denials occur for myriad reasons – from a lack of supporting documentation to patient ineligibility under the billed insurance plan. Another significant factor is the lack of integrated data, which makes root cause analysis of denials extremely difficult and time-consuming on already heavily taxed finance resources. Denials result in delayed collections, increased administrative burden, and millions in lost revenue annually.

Join Albany Medical Center’s ReClaim Squad to learn how they are using their data platform and analytic applications to quickly identify and rectify denial issues, ensuring maximum reimbursement. The ReClaim Squad has managed 149 claims denial cases and recovered nearly $3M in revenue in just one year.

Participants will learn:

• What comprises the visit to claims payment cycle.
•  How to integrate data and analytics into denials manage management projects.
•  How integrating data into the workflow can improve revenue cycle performance.

Providers and pharma have traditionally looked at each other as transactional partners, but that is all changing. There is a new spectrum of opportunities available with what providers already do every day to enhance the quality of care, improve operational outcomes, and drive innovation. Hospital systems are currently the most stressed healthcare pillar—providers are feeling the effects of COVID-19 across outcomes, patient experience, finances, and the well-being of the care team. Many challenges are shared between providers and pharma. The pandemic has solidified the need for a strategic long-term partnership to solve these common challenges by building bridges between providers and pharma through data, technology, and shared expertise.

Join this session to discover:

• The need for provider and pharma partnerships.
• Where pharma comes in to play for providers.
• A collaborative framework.
• Examples of successful partnerships.

Topic: Successful, Large-Scale Quality Improvement at Ascension

Good quality is good business. Ascension has demonstrated real change that happened on a dramatic scale across a system of systems. They have realized over $1 Billion of annual cost savings while working on improving quality. How did they achieve that? How does clinical change happen at the front line where it really matters? Dr. David Pryor will share his learnings over the years about how to achieve quality improvement that matters. He will discuss four critical points:

• Focus on the innovators and early adopters
• Capitalize on existing trends
• Set the right goals
• Work goals in the right way

Join Dr. Pryor and Brent James as they share learnings and best practices.

Healthcare organizations increasingly rely on data to inform strategic decisions. This growing dependence makes ensuring data across the organization is fit for purpose more critical than ever. Decision-making challenges associated with pandemic-driven urgency, variety of data, and lack of resources have further highlighted the critical importance of healthcare data quality and prompted more focus and investment. However, many data quality initiatives are too narrow in focus and reactive in nature or take longer than expected to demonstrate value. In this session, you’ll learn actionable ways to help your organization guard against the data quality challenges uncovered this past year and be better prepared to respond in the future.

Participants will learn:

• How data profiling and data quality assessments can increase data quality transparency, expedite root cause analysis, and close data quality monitoring gaps.
• How to leverage AI to reduce data quality monitoring configuration and maintenance time and improve accuracy.
• How defining data quality based on its measurable utility can provide a scalable way to ensure data are fit for purpose and avoid cost outstripping return.

Navigating healthcare can be chaotic and challenging for patients with complex needs, necessitating effective care management to provide quality care and manage the costs associated with patients searching and receiving the care they need. Learn how UnityPoint Health continuously sharpens its focus on care management using AI and analytics. The organization leverages a unified, reusable data source that empowers care managers to easily identify and engage with the right patients at the right time. The results are improved patient experience, reduced inpatient admissions and emergency department visits, and a $32M reduction in healthcare spending, the result of decreased utilization.

Participants will learn:

• How to best use predictive models to identify high-risk patients.
• How to determine the probability of admission.
• What tools can be used to provide cross-continuum patient and family support, decreasing unnecessary utilization.

Don’t miss this notable healthcare improvement and financial success edition of Jeopardy with host Tom Burton (a distant cousin of Alex Trebek). In this game show breakout session, Tom will test three lucky contestants’ knowledge of five key transformations vital to thriving with lower patient volumes in the post-COVID-19 era. If you’ve ever had the pleasure of attending one of Tom’s breakout sessions in the past, you know you’re in for an interactive, fun experience! Come to learn and be entertained.

Participants will learn:

• What the five key transformations are to ensure post-COVID-19 success.
• How analytics plays a crucial role in each of the five key transformations.
• How health systems can succeed financially by fully adopting quality improvement in all parts of their organization as a business strategy.

COVID-19 has made urgent the need for rapid evidence generation around disease understanding, testing, and treatment patterns in broad populations. In response, the Reagan-Udall Foundation for the FDA and Friends of Cancer Research developed the COVID-19 Evidence Accelerator to convene a real-world data healthcare ecosystem. This session will feature case examples from the Reagan Udall Foundation Evidence Accelerator and demonstrate the importance of a national data repository in driving real-world evidence generation to support multistakeholder collaboration.

Participants will learn:

• How healthcare organizations, public health, and research can effectively collaborate.
• How to design and execute an optimal process to incorporate a risk prediction model into operation.
• How an optimal data structure and user-friendly visualization design can greatly improve model development and utilization.