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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

The Top Three 2020 Healthcare Trends and How to Prepare

After a tumultuous 2019, healthcare organizations are pivoting to make sense of the latest changes and prepare to face the top 2020 healthcare trends:

Consumerism—Can health systems respond to the consumer demands of better access and price transparency?
Financial Performance—With mergers, acquisitions, and private sector companies entering the healthcare arena, how will traditional hospitals and clinics compete?
Social Issues—How will health organizations respond to the opioid crisis and consider social determinants of health as part of the care process to provide comprehensive treatment?

As health systems struggle to survive amidst constant change, they must look forward and proactively prepare for what’s to come in 2020.

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Achieving Stakeholder Engagement: A Population Health Management Imperative

To succeed in population health management (PHM), organizations must overcome barriers including information silos and limited resources. Due to the systemwide nature of these challenges, widespread stakeholder engagement is an imperative in population-based improvement.
An effective PHM stakeholder engagement strategy incorporates the following:

Includes as many stakeholders as possible at the beginning of the journey.
Meets the unique analytics and reporting needs of the organization.
Enables users to measure, and therefore manage, PHM outcomes.
Provides the real-time analytics value-based care requires.

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Removing Barriers to Clinician Engagement: Partnerships in Improvement Work

With clinicians driving many of the decisions that affect health system quality and cost, they’re an essential part of successful improvement efforts. Clinicians are, however, notoriously overburdened in today’s healthcare setting, and getting their buy-in for additional projects is often a big challenge. To successfully partner with these professionals in improvement work, health systems must develop engagement strategies that prioritize clinician needs and concerns and leverage data that’s meaningful to clinicians.
Improvement leaders can approach clinician engagement on three levels:

Clinician-led local programs.
Department- or division-level programs.
Leadership-level growth and improvement programs.

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Artificial Intelligence in Healthcare: A Change Management Problem

The key to successfully leveraging artificial intelligence (AI) in healthcare rests not wholly in the technical aspects of predictive and prescriptive machines but also in change management within healthcare organizations. Better adoption and results with AI rely on a commitment to the challenge of change, the right tools, and a human-centered perspective.
To succeed in change management and get optimal value from predictive and prescriptive models, clinical and operational leaders must use three perspectives:

Functional: Does the model make sense?
Contextual: Does the model fit into the workflow?
Operational: What benefits and risks are traded?

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Three Key Strategies for Healthcare Financial Transformation

To succeed in today’s rapidly evolving business environment, healthcare organizations must have accurate financial data. Approximately 50 percent of CMS payments are now tied to a value component; hospital operating margins are at an all-time low; and consumer demands are rising with their costs. In order to meet these new challenges, health systems must shift their strategy or risk being left behind. This article details the operational, organizational, and financial strategies that drive financial transformation, as well as examples of how to obtain and utilize financial data, find waste reduction opportunities, and much more.

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Healthcare Quality Improvement: A Foundational Business Strategy

Waste is a $3 trillion problem in the U.S. Fortunately, quality improvement theory (per W. Edwards Deming) intrinsically links high-quality care with financial performance and waste reduction. According to Deming, better outcomes eliminate waste, thereby reducing costs.
To improve quality and process and ultimately financial performance, an industry must first determine where it falls short of its theoretic potential. Healthcare fails in five critical areas:

Massive variation in clinical practices.
High rates of inappropriate care.
Unacceptable rates of preventable care-associated patient injury and death.
A striking inability to “do what we know works.”
Huge amounts of waste.

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Machine Learning Tools Unlock the Most Critical Insights from Unstructured Health Data

Patient comments such as “I feel dizzy” or “my stomach hurts” can tell clinicians a lot about an individual’s health, as can additional background, including zip code, employment status, access to transportation, and more. This critical information, however, is captured as free text, or unstructured data, making it impossible for traditional analytics to leverage.
Machine learning tools (e.g., NLP and text mining) help health systems better understand the patient and their circumstances by unlocking valuable insights residing unstructured data:

NLP analyzes large amounts of natural language data for human users.
Text mining derives value through the analysis of mass amounts of text (e.g., word frequency, length of words, etc.).

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The DOS™ E-Book: A Launchpad for the Healthcare Cloud Journey

While over 90 percent of organizations in industries worldwide now use cloud computing in their operations, healthcare still lags behind. As health systems grow their ability to capture data, they still have only a fraction of the data they need to achieve today’s population health and precision medicine goals. Organizations looking to migrate to more agile cloud-based platforms and leverage data for measurable improvements can learn the fundamentals of this critical transformation in an e-book about the Health Catalyst Data Operating System (DOS™).

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A New Era of Personalized Medicine: The Power of Analytics and AI

Healthcare is looking towards an era of personalized medicine in which providers customize treatments for the individual patient. Realizing this tailored level of care s a new level of data volume and analytics and AI capabilities that, while novel to healthcare, other industries are thriving in. Choosing the right role models as healthcare works towards the analytics- and AI-driven territory of personalized medicine will guide informed strategies and establish best practices.
With experience and expertise in these key areas, the military, aerospace, and automotive industries can serve as healthcare’s best examples:

The human cognitive processes of complex decision making.
The digitization of their industries, with the “health” of their assets as key drivers.
Operating in a “big data” ecosystem.

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Harnessing the Power of Healthcare Data: Are We There Yet?

What can healthcare learn from Formula One racing? According to Dr. Sadiqa Mahmood, SVP of medical affairs and life sciences for Health Catalyst, race support teams leverage about 30TB of baseline data to create a digital twin of the car, track, and racer for simulation models that drive decisions at each race. Applied in the healthcare setting, a digital twin can help clinicians better understand each patient and their health conditions and circumstances in real time and make comprehensive, informed care decisions. But for the healthcare digital twin to happen, the industry must move away from data silos and towards a digital learning healthcare ecosystem.

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The Healthcare Analytics Summit™: 2019’s Top Data Discoveries and Insights

The 2019 Healthcare Analytics Summit™ (HAS) was packed full of insightful discussions about data democratization, delivering healthcare in a digital age, and the future of analytics and AI. The 2019 HAS infographic reveals 1,600 industry leaders attended, with 60 percent of attendees from the IT/analyst industry, discussing trending data topics, interacting with presenters through polling mechanisms, and utilizing networking opportunities to share solutions and problem-solving methods.

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How Artificial Intelligence Can Overcome Healthcare Data Security Challenges and Improve Patient Trust

As healthcare organizations today face more security threats than ever, artificial intelligence (AI) combined with human judgment is emerging as the perfect pair to improve healthcare data security. Together, they power a highly accurate privacy analytics model that allows organizations to review access points to patient data and detect when a system’s EHR is potentially exposed to a privacy violation, attack, or breach. With specific techniques, including supervised and unsupervised machine learning and transparent AI methods, health systems can advance toward more predictive, analytics-based, collaborative privacy analytics infrastructures that safeguard patient privacy.

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The 2019 Healthcare Analytics Summit: Thursday Recap

HAS attendees are accustomed to innovation and projections for the future of digital health. But on the final day of HAS 19, they met the next generation of transformation in person: teenager Justin Aronson presented a keynote on how data democratization will empower him and his peers to solve the challenges of coming decades. Other keynotes—Google’s Marianne Slight, former Bayer CDO Jessica Federer, and Beth Israel Deaconess System CIO Dr. John Halamka—contributed their visions for healthcare’s next era, and presenters in 20 breakout sessions shared the experiences, processes, and technologies that will carry digital transformation forward.

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The 2019 Healthcare Analytics Summit: Wednesday Recap

The first full day of the 2019 Healthcare Analytics Summit (HAS 19) featured keynotes from Thomas Jefferson University CEO Dr. Steve Klesko, best-selling author Daniel Pink, former New Jersey Attorney General Anne Milgram, and President of MDLIVE Medical Group Dr. Lyle Berkowitz. Two waves of breakout sessions covered success stories from organizations around the country and their journeys to transformation through further digitization.

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Activity-Based Costing: Healthcare’s Secret to Doing More with Less

Delivering high-quality, cost-efficient care to specific patient populations within a service line is nearly impossible without a sophisticated costing methodology. Activity-based costing (ABC) provides a nuanced, comprehensive view of cost throughout a patient’s journey and reveals the “true cost” of care—the real cost for each product and service based on its actual consumption—which traditional costing systems don’t provide.
With the true cost of care at their fingertips, healthcare leaders can identify at-risk populations earlier—such as pregnant women diagnosed with gestational diabetes mellitus—and more quickly implement effective interventions (e.g., more scrupulous monitoring and earlier screenings). Health systems that leverage the actionable insight from ABC further benefit by implementing the same, or similar, process/clinical improvement measures across other service lines.

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Why One Attendee Is Traveling From the U.S. Virgin Islands to the 2019 Healthcare Analytics Summit

After two Category 5 hurricanes in one year, the Schneider Regional Medical Center (SRMC) has a unique healthcare improvement journey ahead. Tina Comissiong, legal counsel and chief compliance officer of SRMC, knew she needed to attend the Healthcare Analytics Summit as soon as she learned about the event.
SRMC was severely damaged by hurricanes Irma and Maria in 2017, and recovery efforts have been underway ever since. In this article, Comissiong explains why she’s excited to attend this year’s summit and how she will apply what she learns to SRMC’s unique healthcare improvement journey.

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Justin Aronson: A High School Student and HAS 19 Keynote Who’s Transforming the Understanding of Genetic Variants

According to the next generation of healthcare transformation leaders, data democratization is mission critical for the future of improvement. High school student Justin Aronson explains how he leverages open-source health laboratory data to build a tool that improves the clinical interpretation of sequenced genetic variants. Aronson’s cloud-based data integration and visualization system, Variant Explorer, runs on genomic and phenotype data that’s feely accessible on the public archive ClinVar. He says that large-scale data democratization is the key to current and future healthcare problem solving.

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Healthcare’s Next Revolution: Finding Success in the Medicare Shared Savings Program

A series of revolutions has driven the development of the U.S. healthcare system, enabling dramatic improvements in all aspects of healthcare quality and outcomes over the past century. Although healthcare organizations have focused on moving towards value-based care for decades, the data shows that the shift is indeed taking place and fee-for-service models are declining.
New changes to the Medicare Shared Savings Program (MSSP) will help drive this change as revisions to MSSP require ACOs to take on more financial risk earlier. This article covers the following topics:

Important moments in history that led to today’s current challenges.
Why financial imperatives drive cultural change in our economic model.
Ways MSSP can help healthcare organizations achieve financial success.
How to utilize data to develop better healthcare delivery systems.

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Introducing the Health Catalyst Population Health Foundations Solution: A Data- and Analytics-first Approach to PHM

Introducing the Health Catalyst Population Health Foundations solution, which draws on integrated claims and clinical data, and provides essential, extensible tools and machine-learning capabilities for optimizing results in value-based risk arrangements. Accompanying solution services ensure that the strategic value of data is maximized to improve performance in risk contracts—and provide side-by-side subject matter expert partnership for establishing short- and long-term goals for population health management.

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Introducing Population Builder™: Stratification Module

The Health Catalyst Population Builder: Stratification Module allows healthcare organizations to identify the right patient populations in order to deliver the right care at the right time. The solution provides a seamless process for stratifying populations from multiple sources (EMR, claims, and clinical), using pre-defined, easily customized populations as building blocks. With a comprehensive view of the patients they manage, organizations can map populations along their continuum of care and confidently transition appropriate populations to population health interventions.

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Health Catalyst Named 2019 Healthcare IT Corporate Innovator

Utah HIMSS (UHIMSS) recognized Health Catalyst for its innovative leadership with the 2019 UHIMSS Healthcare IT Corporate Innovator award. Dale Sanders, Health Catalyst President of Technology, accepted the honor on behalf of his organization at the UHIMSS 2019 spring conference on May 17. He shared some key insights into what makes a great environment for ongoing innovation, including these valuable sources for invention and originality:

Mischief
Humor
Depression
Pen and paper
Naivety
Pattern recognition
Walking

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ACOs and CINs: Past, Present, and Future

Accountable Care Organizations (ACOs) and clinically integrated networks (CINs) are two types of organizations working to address the problem of rising costs. As ACOs and CINs continue to evolve, organizations moving into value-based care (VBC) face an ever-changing landscape. This article looks at the evolution of the ACO and CIN models, what new tools ACOs employ today to promote success, and lessons learned from organizations that have succeeded in alternative payment models. It also explores what healthcare experts believe the future of alternative payment models will look like and competencies to develop to meet those changing demands.

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The Top Six Examples of Quality Improvement in Healthcare

In order to thrive in an increasingly challenging healthcare environment, undertaking quality improvement projects is more important than ever for healthcare systems’ continued survival. However, health systems need to tackle the right projects at the right time to maximize the impact to their organization.
This article shares both clinical and financial and operational examples of quality improvement in healthcare that may help others as they tackle improvement projects. Some examples shared include:

Pharmacist-led Medication Therapy Management (MTM) reduces total cost of care.
Optimizing sepsis care improves early recognition and outcomes.
Boosting readiness and change competencies successfully reduces clinical variation.
New generation Activity-Based Costing (ABC) accelerates timeliness of decision support.
Systematic, data-driven approach lowers length of stay (LOS) and improves care coordination.
Clinical and financial partnership reduces denials and write-offs by more than $3 million.

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How to Increase Cash Flow Using Data and Analytics

In today’s challenging environment, healthcare leaders must seek opportunities to boost revenue through improved financial performance and reimbursement. Some common strategies include reducing the number of outstanding bill hold accounts, reducing A/R days, and managing discharged not final billed (DNFB) cases.
This article tackles, the following topics:

Common reasons accounts remain unbilled.
Identifying opportunities for improvement.
Using data analytics and process improvement to achieve financial goals.
Creating lasting improvements.

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Five Action Items to Improve HCC Coding Accuracy and Risk Adjustment With Analytics

A hot topic in healthcare right now, especially in the medical coding world is the Hierarchical Condition Category (HCC) risk adjustment model and how accurate coding affects healthcare organizations’ reimbursement.
With almost one third of Medicare beneficiaries enrolled in Medicare Advantage plans, it’s more important than ever for healthcare organizations to pay attention to this model and make sure physicians are coding diagnoses appropriately to ensure fair compensation. This article walks through basics of the risk adjustment model, why coding accuracy is so important, and five action items for interdisciplinary work groups to take. They include:

Having an accurate problem list.
Ensuring patients are seen in each calendar year.
Improving decision support and EMR optimization.
Widespread education and communication.
Tracking performance and identifying opportunities.

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