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The Four Pillars of Successful Self-Service Analytics in Healthcare

Travis Touroo

Sr. Product Manager, DOS

To prepare for successful self-service analytics, healthcare organizations must lay a strong foundation to ensure team members feel comfortable and confident with data. Many health systems are so eager to reap the benefits of self-service analytics that they rush its implementation before their team members are ready. These hurried approaches often lead to unsuccessful self-service analytics implementation that lacks the agility to support systems in a rapidly changing industry. To ensure self-service analytics success and avoid common pitfalls, healthcare organizations can focus on four pillars that build a strong self-service analytics foundation:1. Develop a data-centric culture.2. Promote data literacy.3. Garner leadership support and ensure governance.4. Define a business goal.

Accelerate Data-Driven Healthcare Improvement: 5 Tenets

Growing amounts of data can be overwhelming for healthcare entities to organize, manage, and distribute effectively, sometimes making data more of a burden than a benefit. However, if organizations adopt the right data mentality, they can gain insight into performance, track an intervention’s success, and improve outcomes. According to data experts, Bryan Hinton, our Chief Technology officer, and TJ Elbert, our SVP and General Manager of Data, organizations can apply five mindset changes to avoid data overload and achieve data-driven improvement:1. Focus on data orchestration, not data computing.2. Leverage real-time data, especially in a pandemic.3. Prioritize data democratization over data control.4. Use AI, if you’re not already.5. Change current care models to fit the data.

Deliver Better Population Health by Avoiding 3 Mistakes

Jonas Varnum

Population Health Strategic Services, VP 

Despite the widespread use of population health as a solution to control rising costs and poor outcomes, healthcare organizations struggle to effectively achieve population health success. A common barrier to success is lack of access to data about a system’s most impactable patients, their interventions, and how said interventions impact a patient’s health. However, health systems can overcome the following all-too-common population health mistakes by leveraging detailed data about their most impactable patients and interventions:1. Lacking an effective solution for data-driven strategy.2. Using delayed analytic insight to understand performance and opportunities.3. Not tracking member-level data to measure intervention effectiveness.

The Healthcare Research Network: 5 Modernizing Features

In an era of technological innovation and extraordinary connectivity, why does clinical research follow a decades-old model? Clinical trials remain concentrated among leading urban medical centers with narrow patient populations, but today’s data and collaborative capabilities can support a broader, more robust reach. To that end, the new Health Catalyst Research Offering accelerates and optimizes clinical research in five groundbreaking ways:1. Connects key players in clinical research.2. Provides a network of healthcare provider systems, biopharmaceutical companies, and clinical research organizations.3. Gives access to research-oriented Health Catalyst products and services.4. Supports clinical study from planning through the active trial.5. Maintains a national repository of clinical data.

Close Gaps in Patient Care with the Health Catalyst Embedded Care Gaps™ Application

Tarah Neujahr Bryan

Chief Marketing Officer

With the pandemic fueling increasing financial and clinical demands, health systems need automated tools and processes to deliver cost-effective care without compromising quality. Traditional data infrastructure that delivers delayed insights to clinicians creates additional barriers to better care. Yet, many organizations still use these fragmented systems. Now, with the Health Catalyst Embedded Care Gaps™ application, organizations can deliver relevant insight to decision makers at the point of care. With accurate, actionable insight embedded directly into the EHR, Embedded Care Gaps empowers clinicians to close gaps in patient care, maximize every patient visit, and operate at the top of their licenses. Furthermore, patients reap the benefits of closing gaps by receiving more complete care through an efficient, well-planned visit.

HAS 21 Virtual in Review: Soaring Satisfaction Rates, Attendee Profiles, and More

Even virtually, transporting 3,000-plus healthcare leaders and activists across three international destinations is no small feat. Add world-class data and analytics insight and inspiration from healthcare and beyond to the voyage and you have a three-day journey of a lifetime—otherwise known as the Healthcare Analytics Summit™ (HAS) 21 Virtual. The 2021 edition of healthcare’s premier analytics summit once again gathered innovators and heroes from around the globe to explore multi-domain analytics as the framework for a winning team approach to healthcare transformation.

Surprise Billing in Healthcare: The No Surprises Act Takes a Stand for Patients

Mikki Fazzio, RHIT, CCS

Content Integrity Consultant, Principal

Most providers aim to protect patients from unexpected and unmanageable medical bills. But on January 1, 2022, this responsibility becomes law under the No Surprises Act. The upcoming legislation targets surprise medical bills, which occur when a patient unknowingly receives care from out-of-network providers and is subject to higher charges than for in-network care. These unexpected bills degrade the patient experience and decrease the likelihood of payment for care. Surprise bills may also be more common than many consumers and providers realize—according to the Centers for Medicare and Medicaid Services, in 2016, 42.8 percent of emergency room bills resulted in out-of-network charges. With greater price transparency, the No Surprises Act seeks to protect patients but also impacts providers and facilities, ambulance services, and more, who must comply to receive timely payment and avoid penalties.

Find the Right Term for Your Goals: How to Choose Healthcare Terminology Standards

Cessily Johnson

Vice President of Terminology & Master Data Management

With an overwhelming number of healthcare terminology standards, how do industry professionals determine which ones they need to know? Terminology users can start by matching their purpose with the correct standard. Because different healthcare terminology standards fulfill distinct purposes, matching purpose to standard generally leads users to the right term for their goals. Terminology users can match their purpose with the correct standard by first identifying the standard’s purpose. Purposes encompass billing, clinical, laboratory, and pharmacy terminology standards:1. Healthcare billing terminology.2. Clinical terminology.3. Clinical and laboratory terminology.4. Pharmacy terminology.

Three Reasons Augmented Intelligence Is the Future of AI in Healthcare

Health systems increasingly turn to AI to help all team members make more informed decisions in a shorter time frame. Instead of an artificial-intelligence approach that threatens the critical role healthcare experts play in decision making, organizations should define AI as augmented intelligence. In his first podcast, Dr. Jason Jones, our Chief Analytics and Data Science Officer, explains how augmented intelligence can help health systems accelerate progress toward achieving the Quadruple Aim. The three unique opportunities augmented intelligence offers health systems include the following:1. Augmented—not artificial—intelligence.2. Think “change management.”3. Address and overcome healthcare disparities.

Advancing Health Equity: A Data-Driven Approach Closes the Gap Between Intent and Action

Jason Jones, PhD

Chief Analytics and Data Science Officer

Trudy Sullivan, MBA

Chief Diversity, Equity, & Inclusion Officer

Improving health equity is gaining traction as a healthcare delivery imperative. Yet, while equity is indivisible from healthcare quality, many initiatives targeting disparities fall short. Organizations too often rely solely on leader and stakeholder passion and perseverance without sufficiently leveraging data and analytics to understand, measure, and support equity improvement efforts. It’s time for the industry to pursue equitable care with the same resources it uses in other key dimensions, such as safety and efficacy—by leveraging data. A data-driven approach to equity opens health system’s most advanced predictive resources to equity efforts, thereby driving massive, measurable, data-informed improvement that benefits all.

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