Analyst & IT Roles

Insights

Eric Denna, PhD
Ryan Smith

Improving Strategic Engagement for Healthcare CIOs with Five Key Questions

A healthcare CIO’s role can demand such an intense focus on technology that IT leaders may struggle to find natural opportunities to engage with their C-suite peers in non-technical conversations. To bridge the gap, healthcare CIOs can answer five fundamental questions to better align their programs with organizational strategic goals and guide IT services to their full potential:

Whom do we serve?
What services do we provide?
How do we know we are doing a great job?
How do we provide the services?
How do we organize?

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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.

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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.

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John Wadsworth

The Number One Skill for a Healthcare Data Analyst

In today’s high-pressured world of healthcare, health systems don’t need report writers. They need highly valuable healthcare data analysts. A top healthcare data analyst becomes a partner for clinical and operational improvement by using a five-step method for solving complex problems.
This article walks through this step-by-step approach and demonstrates its application using the real-world example of building a diabetes registry. In addition to this specialized approach to solving problems, the article discusses the five essential skills for data analysts needed in the diabetes registry example:

Data query
Data movement
Data modeling
Data analysis
Data visualization

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John Wadsworth

6 Essential Data Analyst Skills for Your Healthcare Organization

Healthcare organizations are turning to the enterprise data warehouse (EDW) as the foundation of their analytics strategy. But simply implementing an EDW doesn’t guarantee an organization’s success. One obstacle organizations come up against is that their analytics team members don’t have the right skills to maximize the effectiveness of the EDW. The following six skills are essential for analytics team members: structured query language (SQL); the ability to perform export, transform, and load (ETL) processes; data modeling; data analysis; business intelligence (BI) reporting; and the ability to tell a story with data.

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Imran Qureshi

How to Turn Data Analysts into Data Scientists

Healthcare data scientists are in high demand. This shortage limits the ability of healthcare organizations to leverage the power of artificial intelligence (AI). Health systems must better utilize their data analysts, and, where possible, turn some data analysts into data scientists.
This report covers the following:

Healthcare use cases and which ones data analysts can take the lead on.
Specific steps for turning data analysts into data scientists.
How to identify the best candidates among your data analysts.
Recommended resources to get started on an AI journey.

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John Wadsworth

What Healthcare Analysts Can Learn About Data Analytics From the World of Surfing

It might sound surprising, but the world of surfing just might hold key observations about the world of healthcare analytics. After watching the Pipeline Masters in Oahu, John Wadsworth, Technical Operations VP at Health Catalyst, took away three key principles from the world of surfing that are important for healthcare analysts:

Understand the Changing Environment.
Know When to Say No, So You Can Say Yes to the Right Opportunity.
Get Good at Positioning.

This article also offers insights on moving from reactive to prescriptive analytics, the top five technical skills data analysts need, and a four step model for problem solving.

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Health Catalyst Editors

Three Principles for Making Healthcare Data Analytics Actionable

Data is everywhere. But without a plan to extract meaning from data and turn insights into action, data can’t impact outcomes. Generating value from data takes work, but it can be done. To create compelling data insights that promote action, health systems can follow three guiding principles for actionable healthcare data analytics as well as hire analysts with seven important skills.
Three principles form the foundation for actionable healthcare data analytics:

Balance investments.
Hire generalists over specialists.
Develop a team that’s highly aligned and loosely coupled.

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Sarah Provan, BS
Caitlin Kelly

The Number One Secret of Highly Effective Healthcare Data Analysts

Data-driven quality improvement is propelling healthcare transformation. The ability to strategically leverage healthcare data is essential, making highly effective data analysts more valuable than ever. So, what attributes differentiate a good data analyst from a great analyst?
Stephen Covey’s well-known book “The 7 Habits of Highly Effective People,” has long had far-reaching impacts in the business world. These same principles are relevant today and applicable in the world of healthcare analytics. Learn how Covey’s second habit, “Begin With the End in Mind,” drives great healthcare data analysts.

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Larry Grandia

Healthcare Information Systems: A Look at the Past, Present, and Future

Healthcare information systems are integral to hospital operations and clinical care for patients. In the 1960s healthcare was driven by Medicare and Medicaid and HIT developed shared hospital accounting systems. In the 1970s communication between departments and individual transactional systems became important. DRGs drove healthcare in the 1980s and HIT needed to find ways to pull both clinical and financial data in order for reimbursements. The 1990s saw competition and consolidation drive technology to create IDN-like integration. In the 2000s outcomes-based reimbursement became the drive behind developing real-time clinical decision support. For the future, ACOs and value-based purchasing means that CIOs will need to implement data warehouses and analytics application to provide the insights to drive performance improvement necessary for hospital survival.
 

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John Wadsworth

When Healthcare Data Analysts Fulfill the Data Detective Role

There’s a new way to think about healthcare data analysts. Give them the responsibilities of a data detective. If ever there were a Sherlock Holmes of healthcare analytics, it’s the analyst who thinks like a detective. Part scientist, part bloodhound, part magician, the healthcare data detective thrives on discovery, extracting pearls of insight where others have previously returned emptyhanded. This valuable role comprises critical thinkers, story engineers, and sleuths who look at healthcare data in a different way. Three attributes define the data detective:

They are inquisitive and relentless with their questions.
They let the data inform.
They drive to the heart of what matters.

Innovative analytics leaders understand the importance of supporting the data analyst through the data detective career track, and the need to start developing this role right away in the pursuit of outcomes improvement in all healthcare domains.

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Steve Barlow

Eight Reasons Why Chief Data Officers Will Help Healthcare Organizations Thrive in the Future

The state of healthcare information technology and analytics has evolved to the point where a revised executive structure is advisable in the C-suite. This new structure calls for a Chief Data Officer (CDO) to focus on extracting data from systems and on mining value from that data, rather than getting data into systems, which is the responsibility of the CIO.
This article makes the case for the CDO, explains how the need for this emerging role evolved, outlines its responsibilities, advises on how to recruit and budget for this position, and details its domain in eight critical business areas:

Governance and standards
Managing risk
Reducing costs
Driving innovation
Data architecture and technology
Data analytics
Meeting regulatory demand
Creating business value

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Russ Staheli, MPH

4 Ways Healthcare Data Analysts Can Provide Their Full Value

Analysts are most effective when they have the right tools. In healthcare, that means providing data analysts with a means of accessing and testing ALL of the available data and using it to discover more insights. To do this, analysts need guidance more than they need a detailed set of instructions. And, equally as important, they need a data warehouse and access to a testing environment and data discovery tools, so they can truly do the work they were hired to do: analyze.

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John Wadsworth

What Is the ROI of Investing in a Healthcare Data Analyst? A Real Example of Saving Millions.

Making the most of a healthcare data analyst’s knowledge is a key component to getting the best ROI from a hospital improvement project. But all too often, analysts serve merely as data validators — they justify the data that leadership wants validated. Because analysts aren’t decision makers, they don’t have the authority to ask the questions that can save a health system millions. Empowering analysts, however, enables them to ask the right questions — and find the right answers — that will lead to significant savings.

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John Haughom, MD
John Wadsworth
Leslie Falk
Paul Horstmeier
Russ Staheli, MPH

The Changing Role of Healthcare Data Analysts—How Our Most Successful Clients Are Embracing Healthcare Transformation (Executive Report)

The healthcare industry is undergoing a sea change, and healthcare data analysts will play a central role in this transformation. This report explores how the evolution to value-based care is changing the role of healthcare data analysts, how data analysts’ skills can best be applied to achieve value-based objectives and, finally, how Health Catalyst’s most successful health system clients are making this cultural transformation happen in the real world.

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John Wadsworth

3 Frequent Mistakes in Healthcare Data Analytics

Healthcare organizations are recognizing the value of healthcare analytics, especially in their Big Data, population health management, or accountable care initiatives. This is good because without analytics it is difficult to impossible to run these programs successfully. That said, analytics are not the magic bullet and proper process must be in place. The three most common mistakes health systems makes with their healthcare analytics are: 1. Analytics Whiplash- when the analytics goes from one project to another without being able to fully understand the data and what it’s saying. 2. Coloring the Truth- When analysts don’t feel like they can be completely forthcoming with information and only give leadership the news they want to hear. 3. Deceitful Visualizations- Manipulating charts, graphs, and the like to reflect what the analyst or leadership wants the data to say, rather than what it actually says.

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John Wadsworth

The Best Organizational Structure for Healthcare Analytics

After working with many healthcare organizations to help them implement the appropriate EDW for their needs, we’ve learned how important it is to create cross-functional teams from across the organization. Why? These cross-functional teams will simultaneously improve clinical and financial outcomes and demonstrate ROI. By following this approach, you’ll experience the following advantages:

Removal of organizational barriers between team members
Prioritization of BI and analytic efforts according to institutional readiness and need
Engagement and prioritization from appropriate leadership
Buy in from each level of the organization to improvement goals

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Dale Sanders

Ten Great Behaviors of the Best Healthcare IT Vendors

I’ve been a CIO in various forms throughout my decades-long healthcare IT career and have always help healthcare IT vendors to high expectations. Now that I’m on the vendor side of healthcare IT, I hold our company and myself to those same high levels of expectations. Here are the ten great behaviors I expect of my vendors:

Help me compete, hire, measure, save, listen, expand, plan and innovate, migrate, prove, and evolve.

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Jennie Welch

Healthcare Careers: From Nursing to Health Information Technology

I always knew I wanted a healthcare career. I didn’t know I end up going from nursing to health information technology (IT). I loved caring for patients directly and making a difference in the life of an individual. For years, I thrived on the challenge of being a nurse and when I started to look for a new challenge, I found a way to impact patients millions of a time instead of just one-at-a-time in health IT. As I researched the opportunity of working for Health Catalyst, I was impressed by the fact that the company was founded and run by healthcare veterans—people who have actually worked in the halls of hospitals. I feel like I’ve come full circle. Working in health IT, we are making a difference in healthcare—for nurses, for physicians, and for their patients. I look forward to transforming healthcare with Health Catalyst for a long time to come.

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Dale Sanders

Why the CIO Has the Opportunity to Play a Transformative Role in the New Wave of Analytics

All of us quietly yearn to be heroes. CIOs are no exception. We want to harness the power of healthcare analytics, using information technology to dramatically improve healthcare quality and costs. Despite their privileged position atop the IT food chain, though, only a handful of healthcare CIOs ever get to realize this dream. Why? Simply put, CIOs never own both the data content and application layers of any meaningful technology, at the business transformation level. Which is why the Enterprise Data Warehouse (EDW) represents a CIO’s last chance to be a transformational hero in healthcare.

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Larry Grandia

My Thanks to Healthcare IT Professionals ... Along with a Look Back and Forward

Healthcare automation isn’t a new concept … and for that author Larry Grandia, who’s been in the business for more than four decades, is grateful. “The industry has been on a breathtakingly expensive and time consuming sprint for the past decade or so automating essential operational information systems. Capping this technology effort with a foundation-based data strategy — an enterprise data warehouse, robust analytics and a sound data governance plan — holds the promise of a rich harvest from decades of significant IT investment and untold professional effort. My personal thanks to the many IT professionals and healthcare vendors and suppliers that have gotten the industry to this pivotal base camp. I firmly believe the peak is in sight!

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Dale Sanders

Switching It Up: How Dale Sanders Went From Nuclear Warfare to Healthcare

When healthsystemCIO.com asked me to write this blog (HealthsystemCIO original post), I was a bit reluctant to write a piece with so many first-person pronouns, but I hope the readers will look past that annoyance. This blog is not about me. It’s a story of the unpredictable combination of fate, luck, planning, and preparation that rolls together and creates a career. I’m sure many of you could tell a similar story. I don’t know anyone who can honestly say they planned and executed each of the steps in their career with 100 percent foresight of the future. Below, you’ll find a description of odd events that acted like a series of switches on a railroad track in my life. If not for those switches, the path of my career would have been much, much different.

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