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© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.

Healthcare Informatics: Ready to Unleash a New Wave of Advanced Analytics? By Steve Barlow, Senior Vice President and Co-Founder

© 2014 Health Catalystwww.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.

Informatics Metaphor

Look no further than the last scene of Raiders of the Lost Ark to comprehend the current state of healthcare informatics. Specifically when Indiana Jones is being told the government has top men working on discovering the secrets of the Ark of the Covenant, when in fact it is being slowly wheeled into a dark, gigantic warehouse amid what looks to be thousands of other such treasures.

They don’t know what they’ve got there!”

– Indiana Jones‘‘

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Healthcare Informatics Challenge

Much like Indy’s Ark of the Covenant, massive amounts of powerful data sits in storage unused.

Health systems have done a great job of acquiring data, especially over the last few years since electronic health records (EHRs) became widespread. But for the most part, the data just sits in a dark warehouse without creating value for those who store it.

Fortunately, today’s healthcare executives understand the value of their data and the importance of making it readily available for analysis to drive organizational change, lower costs and improve patient care.

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Triple Aim

• Improving the individual experience of care

• Improving the health of populations

• Reducing the per capita cost of care for populations

Healthcare Informatics Challenge

By extracting the insights of the stored data, health systems will be able to reduce outcome variations and raise the level of quality and patient satisfaction while driving down the cost of care, the goal of the Institute for Healthcare Improvement’s Triple Aim.

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PER CAPITA COST

SOURCE: IHI TRIPLE AIM

Triple Aim• Improving the individual experience of care

• Improving the health of populations

• Reducing the per capita cost of care for populations

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The Birth of Healthcare Informatics

Over the past three decades, visionaries saw a need and opportunity for technology and information to support the decision-making process in delivering improved patient care.

Pioneers at informatics think tanks, such as the University of Utah, Indiana University, Columbia, and others, have made significant breakthroughs in terms of using data to understand and manage populations.

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Healthcare’s Current “Recreational” Data SituationHealthcare’s current data situation is still fairly reactive and historical, however. Brent James at Intermountain Healthcare calls it “recreational data collection,” i.e., collecting data for its own sake — the way some people collect coins or stamps. Or the way Indy collects ancient relics to display in a museum.

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Moving from Data Acquisition to Data ExtractionThe next frontier is moving from data acquisition to data extraction. This new phase will make it possible for analysts to extract the data out of the EHR, and combine it with data from other systems to provide proactive care to populations of patients.

Health systems will need a significant change in strategy to succeed. Budgets must balance between data capture and storage, and data extraction and analysis.

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Using the Data

It is important to understand that health systems need more than clinical data for decision-making because this type of data doesn’t provide enough information to answer every quality improvement or patient care question.

Health systems also need to analyze financial data, quality data, pharmacy data, and other factors that can affect the quality and cost of care.

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Using the Data

By connecting all of the various types of healthcare data, it will then be possible to answer questions such as these:

Which hip prosthetic delivers the best outcomes, both from a cost and a quality of life standpoint?

How can we find and eliminate variations in care delivery in order to improve outcomes and lower costs?

Why did this population of patients, treated at this hospital, have better quality and financial outcomes than those patients at other hospitals?

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Using the Data

Understanding the entire picture of patient care is best accomplished by aggregating data from the individual source systems into a Late-Binding™ electronic data warehouse (EDW).

Informatics analysts can use powerful analytics applications to make new knowledge discoveries to support clinical decisions and adherence to standards across patient populations.

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Using the Data

A good example is the accepted standard of not performing elective inductions on pregnant mothers before 39 weeks.

Most healthcare organizations understand the value of this standard in reducing risks to the mother, the newborn, and the provider, and have rules in place to support it.

Yet when we analyze the EHR data for our clients, we often discover that 15 percent of the time they are not adhering to the standard.

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Determining Which Data is Useful

One of the best ways to decide which data is useful is by looking at which data is being used and which is not. If no one is looking at the report or using the data why bother keeping it?

Because that’s the way it’s always been done is not a good reason.

Instead, health systems should focus their data capture on the information that assists clinical decisions at the point of care.

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Placing Effort Where the Greatest Value LaysThe best way to launch a quality initiative is to start where the changes will do the most good. In selecting a clinical process for quality improvement, choose the process with high volumes that will result in greatest ROI.

For example, efforts and resources to focus on hand procedures is nearly the same as focusing on patients with congestive heart failure (CHF).

However, the volumes will be much higher with CHF patients, thus a higher ROI.

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Looking AheadThe Rise of the Healthcare ConsumerThe day is coming when consumers shop for providers and procedures, such as hip replacements or even open heart surgery, the same way they shop for cars — armed with a printout and consumer reviews.

To survive and thrive in this new world of healthcare informatics, providers will need to move from collecting data to analyzing it for critical insights, and from there to knowledge and finally wisdom — the classic maturation cycle of data.

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More about this topic

Unlocking the Power of Data at Texas Children’s Hospital An article from Healthcare Informatics

Healthcare Data Analytics Can Prevent Early-Term DeliveriesAn article from Healthcare Informatics

Building a High-quality Cancer Care Delivery SystemA health system case study on using analytics to address rising cancer care costs

© 2013 Health Catalystwww.healthcatalyst.com

Other Clinical Quality Improvement Resources

Click to read additional information at www.healthcatalyst.com

Steve Barlow is a co-founder of Health Catalyst and former CEO of the company. He oversees all development activities for Health Catalyst's suite of products and services. Mr. Barlow is a founding member and former chair of the Healthcare Data Warehousing Association.

He began his career in healthcare over 18 years ago at Intermountain Healthcare, and acted as a member of the team that led Intermountain's nationally recognized improvements in quality of care delivery and reductions in cost. Mr. Barlow holds a BS from the University of Utah in health education and promotion.

More by this author:

What Is the Best Healthcare Data Warehouse Model? Comparing Enterprise Data Models, Independent Data Marts, and Late-Binding™ Solutions

6 Reasons Why Healthcare Data Warehouses Fail

The Best Data Architecture: Know When to Bind Your Healthcare Data