Data-Driven Healthcare

How Analytics and BI are Transforming the Industry

Laura B. Madsen

• Publisher: Wiley
• Year: 2014
• ISBN:
  9781118973899
• Edition: 1
• Topic: Commerce
• Subtopic: Gestion de l'information

Healthcare is changing, and data is the catalyst

Data is taking over in a powerful way, and it's revolutionizing the healthcare industry. You have more data available than ever before, and applying the right analytics can spur growth. Benefits extend to patients, providers, and board members, and the technology can make centralized patient management a reality. Despite the potential for growth, many in the industry and government are questioning the value of data in health care, wondering if it's worth the investment.

Data-Driven Healthcare: How Analytics and BI are Transforming the Industry tackles the issue and proves why BI is not only worth it, but necessary for industry advancement. Healthcare BI guru Laura Madsen challenges the notion that data have little value in healthcare, and shows how BI can ease regulatory reporting pressures and streamline the entire system as it evolves. Madsen illustrates how a data-driven organization is created, and how it can transform the industry.

• Learn why BI is a boon to providers
• Create powerful infographics to communicate data more effectively
• Find out how Big Data has transformed other industries, and how it applies to healthcare

Data-Driven Healthcare: How Analytics and BI are Transforming the Industry provides tables, checklists, and forms that allow you to take immediate action in implementing BI in your organization. You can't afford to be behind the curve. The industry is moving on, with or without you. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry is your guide to utilizing data to advance your operation in an industry where data-fueled growth will be the new norm.

CHAPTER 1
What Does Data Mean to You?

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DATA:

noun plural but singular or plural in construction, often attributive

1. Factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation. <the data is plentiful and easily available—H. A. Gleason, Jr.><comprehensive data on economic growth have been published—N. H. Jacoby>
2. Information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful.
3. Information in numerical form that can be digitally transmitted or processed.

(Merriam-Webster, 2014)

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The frenetic pace of change in healthcare has been hard to deal with. The broad adoption of electronic health records (EHRs) has ushered in a wave of data that most organizations are not sure what to do with, beyond the standard regulatory reporting. The HITECH Act of 2009 ensured that data, for all the good and bad, is here to stay. Everyone wants it, but very few organizations really know how to get it or what to do with it once it's there.

When I work with organizations that are just getting started, they often express similar concerns:

• “Where do I start?”
• “Do I have the right staff?”
• “Do I have the right technology?”
• “What are other healthcare organizations doing?”

The answers to those questions are easy compared to the next question: “How?” How do you start? How do you know you have the right staff or technology, and how (and perhaps more important, why) would you compare yourself to other healthcare organizations?

Today, it's a forgone conclusion that we have to manage our data. Not just because we have so much of it but because there is so much assumed value in the data. The challenge is that the pace of change is so rapid and there is so much data available, some useful and some not, that the answer to the challenge is one none of us wants to hear. It's just going to take some time. We need time to realign our processes and transition to our new way of thinking in healthcare.

Fundamentally, every medical record is a tool for collecting information: the information a physician collects when looking at you in a physical examination; the results of lab tests. The constant automatic information collection is going to increase, whether it's your phone monitoring your heart rate or your scale sending information about your weight to your health provider, or the contact lenses Google wants to market that measure blood glucose levels.

They all are sources of information about your health and well-being. And the challenge we face collectively, inside the health-care establishment and outside it, is how to take all this information, separate what's useful from what's not, and then apply it to improve the decisions of patients and care providers.

—David Blumenthal (Quoted in Fallows, 2014)

Everyone in healthcare is adapting, from the patients and physicians in a clinic office to the back-end staff and administrators trying to understand the right amount of investment and value that's embedded in this data. What we all want is to strike the right balance; we want to use and manage data, not become a slave to it. The future and the potential of data hints that if we can find that right balance, our organizations and the care that they provide will become more effective, safer, and better aligned with cost. That is the goal of any data-driven healthcare organization.

The Gap

For years, my family had no idea what I did for a living. For a while, they wondered if the job I claimed to have was just a confusing cover-up for a covert lifestyle, perhaps with the CIA. Now when I tell people what I do, the response is always “You must be really busy.” Is it possi­ble that in 15 years it went from being so elusive it made more sense that I was a spy, to so common the middle-aged woman, seated next to me on a flight, knew exactly what I was talking about?

There are no easy answers; you better understand your data.

—Jeff Burke, Executive Advisor, Bon Secours Health System

I'm finally part of the in crowd. My early collegial connection to analysis seemed to seal my fate as a data wonk. Then, lo and behold, the Harvard Business Review said in 2012 that the data scientist is the sexiest job of the twenty-first century (Davenport and Patil, 2012). Finally, my patience paid off. But what does that really mean? What does it mean to be a data scientist? What does it mean to be data driven? What does it mean to invest in data? Not that many years ago, I had to work really hard to prove to healthcare organizations that data was the way forward. Today, I find myself trying to be heard above the noise. Data has become so ubiquitous, so popularized that we've forgotten what it really takes to do the work. We've fallen victim to the “Keeping Up with the Joneses: Data Edition.” We can't articulate the value that data will provide for our own organization. In our fast-paced, soda-pop, YouTube-clip world, data has become a Hollywood starlet. We put you on a pedestal and then beat it down. We need you, we want you, yet we don't want to invest in you.

If I sound frustrated, it's because I am. At least once a month I get a call from the executive of a healthcare company that goes something like this:

“Laura, we've spent a year and a million dollars and we don't have anything to show for it.”

“What was your goal?”

“To do BI.”

“Okay, what do you have now?”

“A system that takes eight minutes to return one report that tells us how many patients we have.”

I wish this was the exception. I'm still surprised that, for all the talk, when I get onsite at a hospital or health plan and start peeling back the layers I'm confronted with the reality that is healthcare—a data warehouse pulled together by transactional data experts at best, or at worst, a series of tables that were created by some savvy business users that's called a warehouse. The gap in the reality of what exists and the stuff you hear advertised in case studies is so large you can't see the other side.

Data Is a Four-Letter Word

I still believe data is the way forward, but it's not an easy way forward. Creating a data-driven healthcare organization (DDHO) means that we have to slow down long enough to plan. We have to know and articulate the value that our data can bring to our organizations. But we also have to know when to say stop so we can reassess and reengage. Data can be powerful and valuable, but before it becomes that, it can be an unforgiving master. We have to change the culture of healthcare to become a data-driven industry. We have to get rid of the naysayers and stop thinking about data as either our salvation or our end. It's just data. It's neither good nor bad. It's what you do with it that matters.

First, let's determine if becoming data driven is the right thing for the industry or, more specifically, your organization. During my corporate life I've had to write a number of SWOT analyses. Popularized as a matrix, it breaks down the strengths, weaknesses, opportunities, and threats of a project or program (Wikipedia Contributors, 2013). (See Figure 1.1.)

Figure 1.1 SWOT

This SWOT analysis for becoming a data-driven healthcare organization is generic, but I encourage you to take this framework and fill it in for yourself to see if becoming a DDHO makes sense for you. We want to find a way to leverage the strengths and exploit the opportunities while managing the weaknesses and reducing the threats.

Strengths

In this case, we have to find a way to take those individual case studies where a power user found value in data and expand that to other departments or advance the skill set to other individuals. In addition, we can take some of the key reports, the ones that are used the most frequently, and try to improve on them or send them to a broader (appropriate) audience. We need to account for the way in which our organization works; whether it is decision by committee or a strong hierarchal chain of command, having internal resources who know and understand how things get done is critical to taking the program to the next level. Finally, we can take advantage of our internal depth of knowledge of our own data, which is invaluable as we begin this journey. That collective knowledge in your organization needs to be empowered to be brought together and incentivized to work together to break down any barriers, perceived or real, that impede the organization's ability to utilize its own integrated data.

Weaknesses

Internally, we have data silos that have these organizational moats around them. These aren't grain silos; they're miss...

Table of contents

• Cover
• Series
• Title Page
• Copyright
• Dedication
• Foreword
• For the Skimmers
• Acknowledgments
• Chapter 1: What Does Data Mean to You?
• Chapter 2: What Happens When You Use Data to Transform an Industry?
• Chapter 3: How the Lack of Data Standardization Impedes Data-Driven Healthcare
• Chapter 4: Adopting Your Data Warehouse for the Next Step in BI Maturity
• Chapter 5: Creating a Data-Driven Healthcare Organization
• Chapter 6: Applying Big Data to Change Healthcare
• Chapter 7: Making Data Consumable
• Chapter 8: Data Privacy and Confidentiality: A Brave New World
• Chapter 9: A Call to Action
• Appendix A: Readiness for Change
• Appendix B: Tenets of Healthcare BI
• Appendix C: Estimating the Efforts
• Appendix D: Business Metrics
• Appendix E: Agenda | Company Name | JAD Session
• Appendix F: Data Visualization Guide
• Afterword
• About the Author
• Index
• End User License Agreement