Understanding Population Health Management: A Diabetes Example

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We all know that the United States healthcare system is facing significant quality and cost challenges. And a major driver of cost in healthcare is chronic disease. In fact, according to the Centers for Disease Control (CDC), more than 75 percent of our nation’s healthcare spending is on individuals with chronic conditions.

Diabetes is representative of the chronic health conditions at the root of our healthcare challenges. Consider these statistics from the 2011 National Diabetes Fact Sheet, the most recent comprehensive assessment of the impact of diabetes in the United States, jointly produced by the CDC, National Institutes of Health, American Diabetes Association, and other organizations:

  • Diabetes affects 25.8 million people—8.3 percent of the U.S. population.
  • 18.8 million of these people have been officially diagnosed with diabetes; 7 million have not.
  • An estimated 79 million American adults aged 20 years or older have prediabetes—blood glucose levels that are higher than normal but not yet high enough to be diagnosed as diabetes.
  • In adults, type 2 diabetes accounts for 90 to 95 percent of all diagnosed cases of diabetes.
  • Diabetes is the seventh leading cause of death in the United States
  • Diabetes is the leading cause of kidney failure, nontraumatic lower-limb amputations, and new cases of blindness among adults in the United States.
  • Diabetes is a major cause of heart disease and stroke.

With these numbers in mind, it’s no wonder that managing diabetes is a major emphasis of providers, payers, associations, accountable care organizations, and government programs seeking to improve the quality and cost of care nationwide.

Managing Diabetes with Healthcare Data

One challenge of addressing chronic health conditions is that symptoms often aren’t apparent until significant damage is done. If you’re a newly-diagnosed type 2 diabetic, you could have no signs indicating a problem. You could feel perfectly normal. That’s why managing diabetes requires managing by the numbers, with healthcare data.

Glucose control is key to minimizing the risk of many of the complications from type 1 or type 2 diabetes. The higher a patient’s hemoglobin A1c level, the poorer their blood sugar control and the higher their risk of complications. In fact, studies have shown that every percentage point drop in A1c blood test results can reduce the risk of eye, kidney, and nerve disease complications by 40 percent.

I’ve recently been very conscious of the need to manage my own type 2 diabetes by the numbers. Historically, my A1c has been well-controlled, but when I had it measured in May, it had gone up to 7.8. I felt fine, but my A1c was clearly trending in the wrong direction, putting me at a higher risk of complications. So I set a personal goal of getting into the lowest-risk category with an A1c of less than 7.

My goal was straightforward but, of course, it took discipline and effort. I determined to lose weight by making sure I took at least 10,000 steps a day—the equivalent of walking about five miles daily. I also was more careful with my intake of carbohydrates – a key intervention for any diabetic.  Since beginning this exercise regimen, I’ve lost 18 pounds and decreased my A1c to 7.4. When I have it tested in another month, I expect it to be even lower.

Managing Diabetes

I tell this story to make the following point: When it comes to managing chronic conditions like diabetes, you’re able to manage what you measure. Continuous measurement followed by appropriate intervention is the key.

Population Health Management: Managing Diabetes Populations

Measuring is where successful population health management starts. You can’t do much to manage your diabetes population if you can’t accurately identify that population or see how your population is trending. Identifying diabetes patients and measuring compliance has been difficult in the past—but today, with a healthcare enterprise data warehouse (EDW) and analytics tools, it doesn’t have to be. (Your EMR won’t be enough.)

By establishing an EDW, you create a data foundation that enables you to manage your diabetes population in sophisticated ways. You can:

  • Create and maintain a robust diabetes registry
  • Use diagnosis codes supplemented by clinical information to continue to define and refine your diabetes population
  • Identify patients who aren’t up-to-date on tests, including A1c, fasting lipids, blood pressure, microalbumin, and more
  • Establish benchmarks and compare those to state and national benchmarks
  • Identify diabetic patients with the highest risk of high cholesterol, hypertension, or heart disease
  • Monitor and report on key indicators for diabetes complications
  • Rank patients by number of care deficits to prioritize outreach efforts
  • Measure the success of your diabetes management interventions
  • Discover variations in diabetes care across your organization
  • Reduce waste
  • Understand exactly how diabetes care affects your organization’s costs
  • And much more

The best way to start creating better outcomes for diabetes patients—and those with other chronic diseases—is to use data well. An EDW makes it possible for you to do just that. And by using data well, you will be able to identify high-risk diabetics and those diabetics with treatment and screening gaps.  From this list you can actively prioritize and target interventions to those specific patient groups.  With good use of data, you enable each individual patient to better manage their own diabetes by the numbers.

Read about another example of population health management efforts in action from my colleague, Kathleen Merkley.

Do you have programs in place to manage diabetes and other chronic diseases in your population? What tools and strategies are you using to manage your population and measure success?

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