HAS 20 Virtual Agenda Overview

(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI, Population Health — Course Level: Intermediate)

Ninety percent of the $3.3T spent in the U.S. annually for healthcare is for people with chronic and mental health conditions. It can be overwhelming to determine which data sources are best for segmenting the population to identify the patients that could benefit the most from population health interventions—critical for ensuring health during a pandemic. Are EMR data components, social determinants of health, claims data, clinical data, or other data the most relevant? This session will describe the use of various data sets to drive a machine learning platform, identify the relative contributions of the data, and discuss which sources are the most important for accurate predictive modeling.

(Revenue, Quality — Course Level: Intermediate)

Access to convenient care is one of the top drivers for patient care site decisions at all times, including the new normal. Learn how Texas Children’s Hospital used a system-wide task force with clinical and administrative leadership to transform patient access, without adding incremental clinical resources. This session will demonstrate how advanced technology—including telehealth, and standardized protocols were used to overcome obstacles to revolutionize the system’s accessibility, ensuring patients can access exceptional care. The result? Monthly visit volume increased by 27%, patient engagement increased, and millions in additional revenue were generated.

The organization will also share how its access work set the stage for continued care delivery during the pandemic, enabling the organization to sustain pre-COVID-19 visit volumes.

(Analytics Best Practices, Innovative Data and Analytics Transformation — Course Level: Intermediate)

COVID-19 response and recovery efforts provided urgent analytic use-cases, each one highlighting data quality as a prerequisite. Discover five essential data quality lessons that COVID-19 helped shine a light on, and how heath organizations can apply these lessons to be prepared for the future.

In this session, you will learn:

• Why assessing data quality at the end of the data pipeline is not good enough.
• How firefighting data quality issues falls on the backs of analysts in the absence of a systematic approach to data quality assessments.
• Why going beyond simple verification of data quality may require looking outside the four walls of a single organization, and more.

(Revenue — Course Level: Intermediate)

Among the many challenges health systems face due to COVID-19 is the significant impact the pandemic has on revenue cycle and operations. Care access is the foundation for optimal revenue performance. Discover how this community-based health system’s access functionality and delivery model enabled its quick response to COVID-19, and how they improved revenue and satisfaction, optimized capacity and improved care access, and grew revenue by:

• Increasing patient access by ensuring responsiveness to request for service, matching patients to the optimal service, provider, and location.
• Identifying opportunities for improvement, resulting in resource optimization.
• Driving stakeholder engagement by transforming resistant leaders into champions of change.

(Analytics — Course Level: Intermediate)

Data and analytics can be powerful weapons in confronting the disruptions and uncertainties healthcare is challenged with today. This is why data and analytics leadership is more vital than ever. This session will explore those disruptions and outline key action items for attendees to execute in order for their data and analytics program to be positioned to tackle uncertainty and manage disruption.

(Analytics — Course Level: Beginning)

With actionable data, Allina Health identified potential areas of bias and then applied the right interventions to decrease implicit biases. For example, data revealed that the African American populations receiving care at Allina Health were not enrolling in hospice programs when they were eligible because the hospitalists weren’t referring African Americans at the same rate as other populations. Vivian and her team implemented new measures including implicit bias trainings to help address and overcome these biases to ensure health equity for all.

(Analytics, Innovative Data and Analytics Transformation, Quality — Course Level: Beginning)

Organizations across the U.S. suspended elective surgeries to help keep resources available for patients with the COVID-19. While this was necessary, the suspension delayed care and resulted in substantial revenue loss. This presentation demonstrates how Banner Health integrated clinical, financial, and operational data to develop the organization’s elective surgery restart plan, effectively engaging patients in receiving the needed care, and restoring critical revenue streams.

(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Beginning)

Knowing where to start and how to gain leadership support for predictive analytics are daunting tasks. One of the largest pediatric hospitals in the U.S. will describe the strategies it used for choosing its initial use cases, a use case evaluation framework, and the lessons they’ve learned in their three-year predictive analytics journey. They will help you discover how to increase the likelihood of success in analytics initiatives, including routine business requests and urgent, emerging needs like COVID-19.

(Population Health, Innovative Data and Analytics Transformation — Course Level: Beginning)

During the COVID-19 outbreak, Mass General Brigham (MGB) chose a strategy of focusing many of their population health efforts on the needs of the most vulnerable communities. Access to data allowed the MGB team to identify hotspots with the highest case rates, so care teams knew where to focus their resources. Teaming up with local governments, MGB provided resources for underserved communities and proactively combatted the spread of COVID-19 by:

• Creating local pop-up COVID-19 testing sites in community health centers, bodegas, etc.
• Communicating educational messages or opt-in for outreach correspondence via mass texting in ten languages.
• Scaling a call center to provide screening and referrals based on social determinants of health.
• Assembling and mailing care kits to patients without masks.

(Machine Learning/AI — Course Level: Intermediate)

AI is no longer about the future. It’s about the present and what clinical and business leaders are doing today to leverage this next big shift in healthcare’s computing platform. As AI solutions become more pervasive, a host of ethical issues are coming forward. How we address them will determine whether AI will be a force for good for some—or all—health consumers.

In this session, Tom Lawry, author of the book, “Artificial Intelligence in Healthcare: A Leader’s Guide to Winning in the New Age of Intelligent Health Systems,” will define key ethical issues for use of AI in health, during a pandemic, and provide recommendations for creating a framework to guide its use in keeping with an organization’s mission and values.

(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI, Population Health, Quality — Course Level: Beginning)

COVID-19 illuminated the criticality of rapid access to integrated data and analytics. In this session, Renown Health will share how it is quickly delivering data to the Command Center and frontline team members to respond to the COVID-19 pandemic, ensuring its most vulnerable patients receive care and ensuring the safety of all its patients and team members. Learn how Renown Health is using rapid response analytics solutions and predictive analytics to create a new future where organizational leaders, physicians, and frontline teams leverage analytic insights to identify business opportunities, implement solutions, and deliver value to its organization.

(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Intermediate)

The COVID-19 pandemic demonstrated how quickly the healthcare industry can move when it needs to and has aligned leadership. One area where leaders and organizations have made rapid progress is capacity planning—including beds, mechanical ventilators, personal protective equipment, and staffing—even across traditional organizational boundaries. During this session, you will discover:

• How to identify different types of decision windows.
• Review leadership tools for forecasting and alerting in the context of what we’ve learned so far.
• Evaluate tool options for short term outlier detection.
• Applications of what we may encounter this Fall, Winter, and beyond.

(Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Advanced)

Machine learning is based on learning from past data and using that to predict the future. This assumes that the future looks like the past. However, this is no longer the case. There is now a longer-term problem for care disruption⁠ due to COVID-19—appointments have been missed or switched to televisits, lab tests have been delayed, and prescriptions have not been filled. How can data science help address this looming issue? This session shares lessons learned and shows how to recognize measure care disruption, predict which patients are at most risk, identify what kind of interventions are appropriate for patients, and how to use data science techniques to help manage the unpredictability of the new normal.

(Analytics Best Practices — Course Level: Intermediate)

You have a lot of choices when you eat out—from fast food that gives you a quick meal with minimal nourishment to a high-class buffet like the Bellagio in Las Vegas, which gives you choices, great flavor, and nutrition—everything you need to feel completely satisfied. Like the buffet at the Bellagio, analytics teams nourish health systems by combining the right ingredients of technology and care delivery expertise.

In this session, we will share how the best health systems leverage analytics in support of COVID recovery. We’ll provide a rubric to assess analytics for your health system and tips to become an analytically mature organization.

This session provides tips to mature your analytics:

• Find real opportunities.
• Quantify them and the resource lift to capture them.
• Prioritize by aligning with key strategies for the organization, department, and team.
• Elevate data analytics understanding throughout the organization through training.

(Innovative Data and Analytics Transformation, Population Health, Quality — Course Level: Beginning)

UPMC will share how it is using remote monitoring and telehealth, especially important during the pandemic, to improve the management of hypertensive disorder in the postpartum period. Hypertensive disorders during pregnancy complicate 10-15% of pregnancies in the U.S. Hypertension is the leading cause of postpartum hospital readmissions, and among the most important contributors to prematurity and serious maternal morbidity and mortality. They are enabling ongoing connections to the healthcare team for 42 days after hospital discharge from delivery, improving maternal outcomes.

(Innovative Data and Analytics Transformation, Population Health, Quality — Course Level: Beginning)

Medical practices are critical to fighting COVID-19, and they are on the frontlines of the ongoing shift toward value-based care. Value is the currency that increasingly matters to health care, and becomes even more critical for survival in the more competitive New Normal. Learn how advanced analytics—and integrating analysts as part of a team that uses actionable data—are creating positive health outcomes at low cost for independent medical practices and, ultimately, patients, in these areas:

• COVID-19 response and tracking.
• The ABCs of measures: Shared Savings, CDPHP Enhanced Primary Care Initiative (EPC), PQRS, CPCI, MSSP, MACRA, and more.
• Point-of-care, pre-visit planning.
• Patient access.
• Coding and compliance.

(Analytics, Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Intermediate)

COVID-19 compelled organizations to quickly advance the use of data science, swiftly embracing predictive models to improve the effectiveness of their response plans. Analytics maturity models are widely used to illustrate the stages a company travels through to reach the next level of analytics maturity. Some critics believe the linear nature of the analytics maturity models may inadvertently limit the effectiveness of data science. In this presentation, Jason Jones, Chief Data Scientist at Health Catalyst, will discuss the Data Science Adoption Model and will share how the model can be used to help data science practitioners and leaders direct investments and deliver real value.

(Analytics Best Practices, Innovative Data and Analytics Transformation, Machine Learning/AI — Course Level: Intermediate)

As COVID-19 makes timely access to comprehensive, accurate patient data increasingly urgent, healthcare organizations, pharma, and public health agencies are struggling to procure needed clinical information. An answer to this data challenge is a national data set that leverages deep, aggregated electronic health record data from patients across the United States, including patient history, comorbidities, vitals, treatment pathways, labs, and more. A proliferation of local standards and a lack of a standard COVID-19 definition has generated problems at the national level, driving the need for a standard COVID-19 patient type definition and registry. Only with this comprehensive, transparent view of patient health and the public health trends can providers, researchers, and policy makers make lasting, impactful progress against the outbreak. Discover how, with aggregated outbreak information from health systems across the United States, a standard COVID-19 definition and registry can accommodate the rapidly changing disease landscape and fill in critical gaps in clinical understanding.

(Innovative Data and Analytics Transformation, Population Health, Revenue — Course Level: Intermediate)

In the wake of COVID-19, ambulatory, non-emergent care converted overwhelmingly to virtual delivery (telehealth). The rapid transition created gaps in understanding of visit volume and outcomes due to a lack of analytics on virtual care. To bridge these gaps, Community Health Network (CHNw) developed an analytics suite to monitor its shift to more than 87 percent virtual visit delivery. Challenges the health system encountered included accounting for multiple visit virtual care types, accommodating different delivery platforms for video visits, and complying with rapidly changing reimbursement rules for telehealth. Join Patrick McGill, MD, Executive Vice President and Chief Analytics Officer for CHNw, to learn how ambulatory providers, managers, and administration can develop, track, and measure virtual care with an analytics platform.

(Analytics Best Practices, Innovative Data and Analytics Transformation, Life Science, Population Health — Course Level: Intermediate)

Responding to the COVID-19 pandemic materially amplified Northwell Health’s necessary speed from question to answer. At the peak of the pandemic, Northwell, the hardest hit healthcare system in the United States—had to face an evolving cohort definition for COVID-19, an additional 200 beds daily, and new healthcare professionals from across the country. Navigating this crisis required careful planning, communication, coordination, and research. This required unprecedented collaboration, an extensive patient registry, access to key datasets, geocoding, and serology testing. Learn about the data-driven response Northwell Health implemented from day one of the pandemic, the successes and lessons learned, and how technology and analytics can be used for future infection tracking and patient care.

(Analytics Best Practices, Innovative Data and Analytics Transformation — Course Level: Advanced)

Responding to the COVID-19 pandemic materially amplified our necessary speed from question to answer and from problem to solution. The dynamic needs of leadership across the academic medical center are now met by enhancing the existing analytics platform with near-real-time data flows and dashboards. This session will describe the processes and lessons-learned of rapidly deploying an end-to-end analytics solution to deliver data for predictions, lab testing, contact tracing, employee health, and “live” situational awareness for the COVID-19 Incident Command.

(Innovative Data and Analytics Transformation, Population Health, Cost — Course Level: Intermediate)

Healthcare organizations have struggled to balance the financial focus of value-based care with the patient focus of clinical care, while also striving to improve performance. This presentation shows how one healthcare network:

• Uses data and analytics to prioritize outreach in their statewide, community-based complex care coordination program.
• Tracks and trends patients and population risk over time.
• Risk stratifies to identify rising-risk patients.
• Effectively predicts cost and utilization—guiding future program development and focusing on prevention and wellness.

This presentation also includes details on how the healthcare system leveraged data and tools to respond to the COVID-19 outbreak and provides data insights about this high-risk population based on clinical criteria.