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Health Catalyst Editors

Health Catalyst Editors is a team of senior editors and writers at Health Catalyst that bring over 60+ combined years of healthcare writing experience and a broad knowledge of the industry

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Health Catalyst Editors

Why Data-Driven Healthcare Is the Best Defense Against COVID-19

COVID-19 has given data-driven healthcare the opportunity to prove its value on the national and global stages. Health systems, researchers, and policymakers have leveraged data to drive critical decisions from short-term emergency response to long-term recovery planning.
Five areas of pandemic response and recovery stand out for their robust use of data and measurable impact on the course of the outbreak and the individuals and frontline providers at its center:

Scaling the hospital command center to pandemic proportions.
Meeting patient surge demands on hospital capacity.
Controlling disease spread.
Fueling global research.
Responding to financial strain.

Health Catalyst Editors

Safeguarding the Ethics of AI in Healthcare: Three Best Practices

As artificial intelligence (AI) permeates the healthcare industry, analytics leaders must ensure that AI remains ethical and beneficial to all patient populations. In absence of a formal regulatory or governing body to enforce AI standards, it’s up to healthcare professionals to safeguard ethics in healthcare AI.
The potential for AI’s use in support of the pandemic response can have enormous payoffs. However, ensuring its ethical implementation may prove challenging if healthcare professionals are not familiar with the accuracy and limitations of AI-generated recommendations. Understanding how data scientists calculate algorithms, what data they use, and how to interpret it is critical to using AI in a meaningful and ethical manner to improve care delivery. By adhering to best practices for healthcare AI, health systems can guard against bias, ensure patient privacy, and maximize efficiencies while assisting humanity.

Health Catalyst Editors

Three Analytics Strategies to Drive Patient-Centered Care

The cost of uncoordinated care that fails to prioritize patient needs is estimated to be over $27.2 billion. One of the primary reasons behind these wasted healthcare dollars is a failure to effectively leverage data to understand patient needs—a must-have to deliver patient-centered, value-based care (VBC).
Three analytics strategies enable health systems to focus on patients while also meeting the financial standards for VBC delivery:

Prioritize patient outreach by risk level.
Deploy data tools to combat COVID-19.
Promote data literacy.

Detailed information from comprehensive data sets allows health systems to understand patient needs at a granular level and then use that insight to drive care decisions. More informed care ensures health systems are also meeting the core elements of VBC—managing costs, delivering quality, and ensuring an excellent patient experience.

Health Catalyst Editors

To Safely Restart Elective Procedures, Look to the Data

Many health systems have realized they lack the data and analytics infrastructure to guide a sustainable reactivation plan and recover lost revenue from months of halted procedures due to COVID-19. However, with operational, clinical, and financial data, augmented by analytics tools, leaders have the visibility into hospital and resource capacity to guide a safe, sustainable elective surgery restart plan.
The first step on the road to recovery for health systems is access to robust analytics to understand the full impact of COVID-19 on clinical, financial, and operational outcomes. Second, organizations need data-sharing tools, like data displays and dashboards, allowing leaders to make decisions based on consistent data that support the organization’s reactivation goals. Leaders can even take the data one step further with predictive models and forecast procedure count, staff, and resources.

Health Catalyst Editors

Medical Practices’ Survival Depends on Four Analytics Strategies

With limited resources compared to large healthcare organizations and fewer personnel to shoulder burdens like COVID-19, medical practices must find ways to deliver better care with less. Delivering quality care, especially in a pandemic, is challenging, but analytics insight can guide effective care delivery methods, especially for smaller practices.
Comprehensive data combined with team members who can turn numbers into real-world information are essential for medical practices to ensure a strong financial, clinical, and operational future. Independent medical practices can rely on four analytics strategies to survive the uncertain healthcare market and plan for a sustainable future:

Prioritize access to up-to-date, comprehensive data sources.
Form a multidisciplinary approach to data governance.
Translate data into analytics insight.
Invest in analytics infrastructure to support rapid response.

Health Catalyst Editors

Shifting to Virtual Care in the COVID-19 Era: Analytics for Financial Success and an Optimized Patient Experience

The COVID-19 era has seen a decline in visits to ambulatory care practices by 60 percent and an estimated financial loss for primary care of over $15 billion. Shutting down elective care is financially unsustainable for health systems and for patients, who continue to need non-pandemic-related care. While virtual medicine has emerged as a viable and mutually beneficial solution for patients and providers, the shift from in-person to virtual health is logistically and financially complicated.
Processes and workflows from in-person care don’t directly translate to the virtual setting, and a financially successful shift requires deep understanding of the factors driving patient engagement and revenue in the new normal. As such, meeting patient needs and financial goals requires robust enterprisewide analytics that drill down to the provider level.

Health Catalyst Editors

Healthcare Financial Transformation: Five Leading Strategies

Healthcare financial transformation—improving care delivery while lowering costs—has been an ongoing challenge for health systems in the era of value-based care and an even more prominent concern amid COVID-19. While better care and reduced expense to organizations and consumers might seem like opposing goals, by understanding the true cost of services and other drivers of expense, organizations can successfully manage costs while maintaining, and even improving, care delivery. To that end, health systems can use data- and analytics-driven tools and strategies to addresses financial challenges, including uncompensated care, prolonged accounts receivable days, discharged not final billed cases, inefficient resource use, and more.

Health Catalyst Editors

Six Strategies to Navigate COVID-19 Financial Recovery for Health Systems

Research projects that 2020 healthcare industry losses due to COVID-19 will total $323 billion. As patient volumes fall and pandemic-related expenses rise, health systems need a strategy for both immediate and long-term financial recovery. An effective approach will rely on a deep, nuanced understanding of how the pandemic has altered and reshaped care delivery models. One of the COVID-19 era’s most impactful changes has been the shift from in-person office visits to virtual care (e.g., telehealth). Though patients and providers initially turned to remote delivery to free up facilities for COVID-19 care and reduce disease transmission, the benefits of virtual care (e.g., circumventing the time and resource drain of patients traveling to appointments) position telehealth as lasting model in the new healthcare landscape. As a result, healthcare financial leaders must fully understand the revenue and reimbursement implications of virtual care.

Health Catalyst Editors

Six Proven Methods to Combat COVID-19 with Real-World Analytics

As data in healthcare becomes more available than ever before, so does the need to apply that data to the unique challenges facing health systems, especially in a pandemic. Even with massive amounts of data, health systems still struggle to move data from spreadsheets to drive change in a clinical setting.
These six methods allow health systems to transform data into real-world analytics, going beyond basic data usage and maximizing actionable insight:

Create effective information displays.
Add context to data.
Ensure data processes are sustainable.
Certify data quality.
Provide systemwide access to data.
Refine the approach to knowledge management.

Advancing data use in healthcare with real-world analytics arms health systems with effective tools to combat COVID-19 and continue delivering quality care driven by comprehensive, actionable insight.

Health Catalyst Editors

How to Optimize the Healthcare Revenue Cycle with Improved Patient Access

Despite pandemic-driven limitations, health systems can still find ways to optimize revenue cycle and generate income. When health systems improve and prioritize patient access through a patient-centered access center, they can improve the revenue cycle performance through decreased referral leakage, better patient trust, and optimum communication across hospital departments.
Rather than relying on traditional revenue cycle improvement tactics, health systems should consider three ways a patient-centered access center can positively impact revenue cycle performance:

Advance access.
Optimize resources.
Engage stakeholders.

Health Catalyst Editors

Population Health Success: Three Ways to Leverage Data

As the healthcare industry continues to focus on value, rather than volume, health systems are faced with delivering quality care to large populations with limited resources. To implement population health initiatives and deliver results, it is critical that care teams build population health strategies on actionable, up-to-date data. Health systems can better leverage data within population health and drive long-lasting change by implementing three small changes:

Increase team members’ access to data.
Support widespread data utilization.
Implement one source of data truth.

Access to accurate, reliable data boosts population health efforts while maintaining cost and improving outcomes. With actionable analytics providing insight and guiding decisions, population health teams can drive real change within their patient populations.

Health Catalyst Editors

Four Strategies Drive High-Value Healthcare Analytics for COVID-19 Recovery

COVID-19 response and recovery is pushing healthcare to operate at an unprecedented level. To meet these demands and continue to improve outcomes and lower costs, healthcare analytics must perform more actionably and with broader organizational impact than ever. Health systems can follow four strategies to produce high-value analytics to withstand the pandemic and make healthcare better in the long term:

Minimize benchmarking.
Outsource regulatory reporting.
Grow risk-based stratification capabilities.
Run activity-based costing plus at-risk contracting.

Health Catalyst Editors

The Healthcare Analytics Summit™: Top Data Discoveries and Insights from HAS 20 Virtual

The 2020 Healthcare Analytics Summit™ (HAS 20 Virtual) took place for the first time from a remote platform. But, as the 2020 HAS infographic demonstrates, the remote experience delivered on HAS event’s customary high level of engagement and meaningful healthcare insights. The 2020 conference focused on the theme of analytics in the new normal, sharing insights around pandemic response and recovery to a record-setting audience.

Health Catalyst Editors

Six Ways Health Systems Use Analytics to Improve Patient Safety

With preventable patient harm associated with over 400,000 deaths in the U.S. annually, improving safety is a top priority for healthcare organizations. To reduce risks for hospitalized patients, health systems are using patient safety analytics and trigger-based surveillance tools to better understand and recognize the types of harm occurring at their facilities and intervene as early as possible.
Six examples of analytics-driven patient safety success cover improvement in the following areas:

Wrong-patient order errors.
Blood management.
Clostridioides difficile (C. diff).
Opioid dependence.
Event reporting.
Sepsis.

Health Catalyst Editors

Healthcare Analytics Summit 2020: Day Three Recap

The Healthcare Analytics Summit 20 Virtual (HAS 20 Virtual) concluded three days of online programming on Thursday, September 3, 2020. Though COVID-19 forced this year’s event to take place virtually, the geographic dispersal of attendees and presenters didn’t dampen the depth of insights or level of engagement previous summits are known for. After two days of keynote addresses, breakout presentations, small Braindate gatherings, and project and solution showcase, HAS 20 Virtual maintained its momentum. The conference closed on a powerful note with yet more world-class speakers, groundbreaking innovations, and common theme of the power of analytics and human potential in healthcare’s new normal.

Health Catalyst Editors

Healthcare Analytics Summit 2020: Day Two Recap

Day two of the Healthcare Analytics Summit 20 Virtual (HAS 20 Virtual) included keynote speakers followed by live Q&As, quizzes to earn points for the HAS game, the Analytics Walkabout, Machine Learning Marketplace, and Digital Innovation Showcase. Attendees enjoyed topical keynote speakers like Amy P. Abernethy, MD, PhD, acting CIO of the U.S. Food and Drug Administration, who discussed the importance of data in addressing COVID-19; Yonatan Adiri, CEO of Healthy.io, who presented on a smartphone-enabled urine test to improve healthcare accessibility; and Sampson Davis, MD, emergency medicine physician and New York Times best-selling author, who shared how education saved his life.

Health Catalyst Editors

Virtually Kicking Off the 2020 Healthcare Analytics Summit

For the first time from an online platform, Health Catalyst COO Paul Horstmeier welcomed attendees to the Healthcare Analytics Summit 20 Virtual (HAS 20 Virtual), promised a highly interactive online experience that would maintain the breadth and depth of expertise as well as the spirit of innovation of the conference’s in-person iterations.
HAS 20 Virtual will also provide some of the fun and good humor attendees have enjoyed in year’s past–from the Virtual fun run to the friendly competition for the most notable socks–HAS 20 Virtual has moved these activities online. Highlights from Day one of HAS 20 included keynotes from Eric Topol, MD and Ari Robicsek, MD, as well as two breakout session waves.

Health Catalyst Editors

Beginning the Conversation: Health Equity

Equity impacts the fabric of society down to the type and quality of healthcare different racial and ethnic patient populations receive. COVID-19 has underscored disparities in healthcare delivery in the United States, as the pandemic has disproportionately affected the nation’s black communities. To care for and recognize the value of all individuals, healthcare must leverage data and analytics to better understand patient populations by race and ethnicity and determine how to meet the needs of its underserved populations.

Health Catalyst Editors

Restarting Ambulatory Care and Elective Procedures: Analytics Guide Safe, Pragmatic Decisions

As Health Catalyst continues to engage its health system partners in their COVID-19 journeys through virtual client huddles, topics are delving further into restarting ambulatory care and elective procedures. The May 21, 2020, forum explored how organizations are responding to the pandemic and planning for the next phases. Participants explored two vital topics in the COVID-19 era:

How virtual care analytics supports rapid change in ambulatory care delivery.
How analytic insights help drive a COVID-19 financial recovery plan.

Health Catalyst Editors

Three Keys to Improving Hospital Patient Flow with Machine Learning

Health systems alike struggle to effectively manage hospital patient flow. With machine learning and predictive models, health systems can improve patient flow for different departments throughout the system like the emergency department. Health systems should focus on three key areas to foster successful data science that will lead to improved hospital patient flow:
Key 1. Build a data science team.
Key 2. Create a ML pipeline to aggregate all data sources.
Key 3. Form a comprehensive leadership team to govern data.
Improving hospital patient flow through predictive models results in reduced patient wait times, reduced staff overtime, improved patient outcomes, and improved patient and clinician satisfaction.

Health Catalyst Editors

Health Systems Share COVID-19 Financial Recovery Strategies in First Client Huddle

More than 100 attendees joined the first of a series of Health Catalyst virtual client huddles designed to support client partners and aid collaboration and direct client connections in this time of unprecedented change. According to an April 2020 survey of Health Catalyst clients, 72.6 percent said they had a strong interest in examples, guidance, and tools from other health systems. In the client-only session, insights shared included the most common COVID-19 analytic projects and one health system’s elective surgery plan.
The health system shared the challenges they faced in understanding the financial impact of halting elective surgeries as well as creating a plan for working through their backlog. They also shared the tools and strategies they are using to aid their financial recovery.

Health Catalyst Editors

The Top Five Insights into Healthcare Operational Outcomes Improvement

Effective, sustainable healthcare transformation rests in the organizational operations that power care delivery. Operations include the administrative, financial, legal, and clinical activities that keep health systems running and caring for patients. With operations so critical to care delivery, forward-thinking organizations continuously strive to improve their operational outcomes. Health systems can follow thought leadership that addresses common industry challenges—including waste reduction, obstacles in process change, limited hospital capacity, and complex project management—to inform their operational improvement strategies.
Five top insights address the following aspects of healthcare operational outcomes improvement:

Quality improvement as a foundational business strategy.
Using improvement science for true change.
Increasing hospital capacity without construction.
Leveraging project management techniques.
Features of highly effective improvement projects.

Health Catalyst Editors

The Healthcare Analytics Adoption Model: A Roadmap to Analytic Maturity

The focus on analytics is contributing to the “EHR problem”—doctors prioritizing the EHR over patients. The Healthcare Analytics Adoption Model (HAAM) walks healthcare organizations through nine levels that lay the framework to fully leverage analytic capabilities to improve patient outcomes:
Level 1. Enterprise Data Operating System
Level 2. Standardized Vocabulary & Patient Registries
Level 3. Automated Internal Reporting
Level 4. Automated External Reporting
Level 5. Waste and Care Variability Reduction
Level 6. Population Health Management & Suggestive Analytics
Level 7. Clinical Risk Intervention & Predictive Analytics
Level 8. Personalized Medicine & Prescriptive Analytics
Level 9. Direct-To-Patient Analytics & Artificial Intelligence
Analytics are crucial to becoming a data-driven organization, but providers and administrators can’t forget about the why behind the data—to improve outcomes. Following the HAAM enables organizations to build a sustainable, analytic platform and empower patients to become data-driven when it comes to their own care.

Health Catalyst Editors

Population Health Management: A Path to Value

As value-based care (VBC) definitions and goals continue to shift, organizations struggle to create a roadmap for population health management (PHM) and to track associated costs and revenue. However, health systems can move forward with PHM amid the uncertainty by following the best practices of a path to value:

Begin with Medicare Advantage—a good growth opportunity with low barriers to entry.
Focus on ambulatory, not acute, care as it delivers more value.
Leverage registries based on utilization to identify the most impactable 3 to 10 percent of utilizers.
Simplify the physician burden by focusing on reasonable measures.

Health Catalyst Editors

A Roadmap for Optimizing Clinical Decision Support

Compared to industries such as aerospace and automotive, healthcare lags behind in decision support innovation. Following the aerospace and automotive arenas, healthcare can learn critical lessons about improving its clinical decision support capabilities to help clinicians make more efficient, data-informed decisions:

Achieve widespread digitization: Healthcare must digitize its assets and operations (patient registration, scheduling, encounters, diagnosis, orders, billings, and claims) for effective CDS similarly to how aerospace digitized the aircraft, air traffic control, baggage handling, ticketing, maintenance, and manufacturing.
Build data volume and scope: Healthcare must collect socioeconomic, genomic, patient-reported outcomes, claims data, and more to truly understand the patient at the center of the human health data ecosystem.