Learn more about Health Catalyst Editors

Author Bio

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

Read articles by Health Catalyst Editors

Insights

Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

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.

Read more
My Folder
Health Catalyst Editors

Healthcare NLP: The Secret to Unstructured Data’s Full Potential

While healthcare data is an ever-growing resource, thanks to broader EHR adoption and new sources (e.g., patient-generated data), many health systems aren’t currently leveraging this information cache to its full potential. Analysts can’t extract and analyze a significant portion of healthcare data (e.g., follow-up appointments, vitals, charges, orders, encounters, and symptoms) because it’s in an unstructured, or text, form, which is bigger and more complex than structured data.
Natural language processing (NLP) taps into the potential of unstructured data by using artificial intelligence (AI) to extract and analyze meaningful insights from the estimated 80 percent of health data that exists in text form. Though still an evolving capability, NLP is showing promise in helping organizations get more from their data.

Read more
My Folder
Health Catalyst Editors

Four Steps to Effective Opportunity Analysis

Opportunity analysis uses data to identify potential improvement initiatives and quantifies the value of these initiatives—both in terms of patient care benefits and financial impact. This process is an effective way to find unwarranted and costly clinical variation and, in turn, develop strategies to reduce it, improving outcomes and saving costs along the way. Standardizing the opportunity analysis process makes it repeatable and prioritizes actionable opportunities.
Quarterly opportunity analysis should follow four steps:

Kicking off the analysis by getting analysts together to do preliminary analysis and brainstorm.
Engaging with clinicians to identify opportunities and, in the process, get clinician buy in.
Digging deeper into the suggested opportunities to prioritize those that offer the greatest benefits.
Presenting findings to the decision makers.

Read more
My Folder
Health Catalyst Editors

The Top Five 2019 Healthcare Trends

Bobbi Brown, MBA, and Stephen Grossbart, PhD have analyzed the biggest changes in the healthcare industry and 2018 and forecasted the trends to watch for in 2019. This report, based on their January 2019, covers the biggest 2019 healthcare trends, including the following:

The business of healthcare including new market entrants, business models and shifting strategies to stay competitive.
Increased consumer demand for more transparency
Continuous quality and cost control monitoring across populations.
CMS proposals to push ACOs into two-sided risk models.
Fewer process measures but more quality outcomes scrutiny for providers.

Read more
My Folder
Health Catalyst Editors

Customer Journey Analytics: Cracking the Patient Engagement Challenge for Payers

Customer journey analytics uses machine learning and big data to track and analyze when and through what channels customers interact with an organization, with an aim to influence behavior (e.g., buying behaviors among retail customers). Similarly, healthcare organizations want to influence health-related behaviors, such a taking medication as prescribed and not smoking, to improve outcomes and lower the cost of care. In a partnership with an analytics services provider, a payer organization is leveraging customer journey analytics among healthcare consumers to identify the best opportunities and channels for patient outreach. With this analytics-driven engagement strategy, the payer has found an opportunity to significantly improve patient engagement—a predicted overall increase from 18 percent to 31 percent.

Read more
My Folder
Health Catalyst Editors

How to Build a Healthcare Analytics Team and Solve Strategic Problems

Health systems have vast amounts of data, but frequently struggle to use that data to solve strategic problems in a timely fashion. A healthcare analytics team, made up of the right people with the right tools and skillsets, can help address these challenges. This article walks through the steps organizations need to take to put an effective analytics team in place.
These include the following:

Recognizing the need for change.
Demonstrating the value of an analytics team.
Conducting a current state assessment.
Identifying solutions.
Implementing a phased approach.
Building a roadmap.
Making the pitch.
Putting the roadmap into action.

The article also includes the foundation skills to look for when putting together the team and tips on how best to organize.

Read more
My Folder
Health Catalyst Editors

Leveraging Technology to Increase Patient Satisfaction and Employee Engagement

Health systems are challenged by the need to keep patients and employees satisfied and engaged. This can be especially difficult for organizations in flux, growing, merging, and changing. And as leaders of these organizations know, poor patient satisfaction ratings lead to reduced reimbursements, which affect the bottom line.
To meet this challenge and improve patient satisfaction, health system leaders are taking advantage of technology, such as rounding software, that supports effective communication and drives the type of culture change that boosts both caregiver and patient satisfaction and encourages engagement. Embedding rounding technology into current processes makes rounding better and easier. The correlation between effective, efficient rounding and high patient satisfaction scores is clear. Rounding can and does increase engagement and satisfaction, which in turn leads to higher reimbursement potential. Learn how health system leaders can move from talking about rounding technology to incorporating it into daily workflow.

Read more
My Folder
Health Catalyst Editors

Unlocking the Power of Patient-Reported Outcome Measures (PROMs)

Health systems attempt to measure an ever-increasing amount of clinical measures, these often miss the mark of what matters to patients. Patient-Reported Outcomes (PROs) are the missing link in empowering patients and helping to define good outcomes.  This article walks through how patient-reported outcome measures (PROMs) can help identify best practices and drive system-wide quality improvement. PROMs can help health systems do the following:

Serve as a guide for appropriateness and efficiency.
Lead to better shared decision-making.
Demonstrate value and transparency

This article also discusses the effect of PROMs on providers in a culture of “one more thing,” and tips for effective implementation.

Read more
My Folder
Health Catalyst Editors

ACOs: Four Ways Technology Contributes to Success

With an increasing emphasis on value-based care, Accountable Care Organizations (ACOs) are here to stay. In an ACO, healthcare providers and hospitals come together with the shared goals of reducing costs and increasing patient satisfaction by providing high-quality coordinated healthcare to Medicare patients.
However, many ACOs lack direction and experience difficulty understanding how to use data to improve care. Implementing a robust data analytics system to automate the process of data gathering and analysis as well as aligning data with ACO quality reporting measures.
The article walks through four keys to effectively implementing technology for ACO success:

Build a data repository with an analytics platform.
Bring data to the point of care.
Analyze claims data, identify outliers, including successes and failures.
Combine clinical claims, and quality data to identify opportunities for improvement.

Read more
My Folder
Health Catalyst Editors

The Four Keys to Increasing Hospital Capacity Without Construction

Many health systems have a hospital capacity problem as demand for patient beds rises. When the supply of usable patient beds can’t meet demand, the negative impact on patients and staff can be significant.
Hospitals can solve capacity problems with four key concepts:

Using data, start with the problem and the ideal solution.
Be sure the analytics team works with teams throughout the organization—including leadership.
Have leaders spend time with the operations team to understand workflow.
Focus on the impact, not the tool.

Read more
My Folder
Health Catalyst Editors

Why Clinical Quality Should Drive Healthcare Business Strategy

Healthcare today is in the midst of a massive transformation. The opportunities for improvement are great if healthcare systems can do the following:

Reduce clinical variation.
Reduce rates of inappropriate care and care-associated patient injury and death.
Follow accepted best care practices.
Eliminate waste.

This article covers the different types of waste in healthcare systems, ways to reduce them, financial alignment around waste reduction opportunities, and the importance of reducing clinical variation. The core driver of healthcare systems must be improving clinical quality. Almost always, with proper clinical management, better care is cheaper care through waste management.

Read more
My Folder
Health Catalyst Editors

How to Evaluate Emerging Healthcare Technology With Innovative Analytics

As healthcare systems are pressured to cut costs and still provide high-quality care, they will need to look across the care continuum for answers, reduce variation in care, and look to emerging technologies. This article walks through how to evaluate the safety and effectiveness and of emerging healthcare technology and prioritize high-impact improvement projects using a robust data analytics platform. Topics covered include:

The importance of identifying variation in innovation.
Ways to improve outcomes and decrease costs.
The value of an analytics platform.
The reliable information that produce sparks for innovation.
Identifying and evaluating emerging healthcare technology.
Knowing what data to use.
The difference between efficacy and effectiveness in evaluation of emerging healthcare technology.

Read more
My Folder
Health Catalyst Editors

Reducing Hospital Readmissions: A Case for Integrated Analytics

Health systems continue to prioritize reducing hospital readmissions as part of their value-based payment and population health strategies. But organizations that aren’t fully integrating analytics into their readmission reduction workflows struggle to meet improvement goals. By embedding predictive models across the continuum of care, versus isolated them in episodes of care, health systems can leverage analytics for meaningful improvement.
Organizations that integrate predictive models into readmissions reduction workflows have achieved as much as a 40 percent reduction in risk-adjusted readmissions indexes. Effective analytics integration strategies use a multidisciplinary development approach to meet the needs of a patient’s entire care team and deliver common tools for all involved in the patient’s healthcare journey.

Read more
My Folder
Health Catalyst Editors

Emergency Department Quality Improvement: Transforming the Delivery of Care

Overcrowding in the emergency department has been associated with increased inpatient mortality, increased length of stay, and increased costs for admitted patients. ED wait times and patients who leave without seeing a qualified medical provider are indicators of overcrowding. A data-driven system approach is needed to address these problems and redesign the delivery of emergency care.
This article explores common problems in emergency care and insights into embarking on a successful quality improvement journey to transform care delivery in the ED, including an exploration of the following topics:

A four-step approach to redesigning the delivery of emergency care.
Understanding ED performance.
Revising High-Impact Workflows.
Revising Staffing Patterns.
Setting Leadership Expectations.
Improving the Patient Experience.

Read more
My Folder
Health Catalyst Editors

Social Determinants of Health: Tools to Leverage Today’s Data Imperative

Social determinants of health (SDOH) data captures impacts on patient health beyond the healthcare delivery system. Traditional health data (e.g., from healthcare encounters) only tells a portion of the patient and population health story. To understand the full spectrum of health impacts (e.g., from environment to relationship and employment status), organizations need data from their patient’s daily lives. The urgency for SDOH data is particularly strong today, as value-based payment increasingly presses health systems to raise quality and lower cost. Without fuller insight into patient health (what happens beyond healthcare encounters) organizations can’t align with community services to help patients meet needs of daily living—prerequisites for maintaining good health.
Standardizing SDOH data into healthcare workflows, however, requires an informed strategy. Health systems will benefit by following a standardization protocol that includes relevant and comprehensive domains, engages patients, enables broader understanding of patient health, integrates with organizational EHRs, and is easy for clinicians to follow.

Read more
My Folder
Health Catalyst Editors

Improving Quality Measures Can Lead to Better Outcomes

Current quality measures are expensive and time consuming to report, and they don’t necessarily improve care. Many health systems are looking for better ways to measure the quality of their care, and they are using data analytics to achieve this goal. Data analytics can be helpful with quality improvement. There are four key considerations to evaluate quality measures:

Organizations must develop measures that are more clinically relevant and better represent the care provided.
Clinician buy-in is critical. Without it, quality improvement initiatives are less likely to succeed.
Investment in tools and effort surrounding improvement work must increase. Tools should include data analytics.
Measure improvement must translate to improvement in the care being measured.

When the right measures are in place to drive healthcare improvement, patient care and outcomes can and do improve.

Read more
My Folder