Understanding Population Health Management: A Diabetes Example

TheWorld Health Organizationreports that nearly1.5 million peopledie from diabetes annually. In addition to the devastating mortality rate, health experts estimate on a global scale the cost of diabetes will reach$2.1 trillion到2030年。

Given its prevalence and economic impact, diabetes is representative of the chronic health conditions at the root of global healthcare challenges, highlighting the need for population health management. With an effective approach to managing the health of populations, providers and healthcare organizations can improve the quality and reduce the cost of diabetes care worldwide.

Managing Diabetes with Healthcare Data

应对糖尿病等慢性疾病的一个挑战是，症状往往在严重损害发生之前并不明显。例如，一个新诊断的2型糖尿病患者可能没有任何迹象表明有问题，尽管测试结果可能会证明并非如此。这种不可靠的症状是一种更值得信赖的方法——一种利用对糖尿病管理至关重要的医疗数据的方法。

For example, glucose control and therefore glucose data are key to minimizing the risk of many complications stemming 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,studieshave shown that every percentage point drop in A1c blood test results can reduce the risk of eye, kidney, and nerve disease complications by as much as 40 percent. As a result, patients and clinicians need continual access to timely data to maintain target glucose levels.

Management by Measurement: A Personal Anecdote on Managing Diabetes via Data

On a personal note, I’m very conscious of the need to manage my own Type 2 diabetes by monitoring data and trends. Historically, my A1c had been well-controlled. Several years ago, however, it was measured at 7.8. I felt fine at the time, but my A1c was clearly trending in the wrong direction, which put me at a higher risk of complications. In 2014 I set a personal goal of getting into the lowest-risk category, by consistently having my A1c readings below 7.

My goal took discipline and effort. I was determined to lose weight and walked least 10,000 steps per day—the equivalent of walking about five miles. I also closely monitored my intake of carbohydrates, which is a key intervention for any diabetic. In less than a year, I lost 18 pounds and decreased my A1c to 7.4.

Jumping forward to 2021, my battle with diabetes continues. My A1c has fluctuated up and down but has averaged around 7.2. In 2020, I focused more on biking and decreased my weight by another 12 pounds. The COVID-19 pandemic has given me more time to focus on intense cycling, and I finally reached my goal of an A1c of 5.9 (Figure 1).

Figure 1: The author reached an A1c of 5.9 in 2021.

It has been a long journey, but I’m now in the lowest risk group, with my A1c only slightly above normal (a non-diabetic upper limit is 5.7). Additionally, my primary care provider recommended I cut my dose of glimepiride (an oral hypoglycemic agent) in half. This marks the first time since my diagnosis 12 years ago that I have decreased my diabetes medications, and it feels great! I am due for another A1c check in fall 2021 and looking forward to seeing my progress so I can learn and adjust diabetes management to reduce my risk of complications and mortality.

I tell this story to make the following point: When managing chronic conditions like diabetes, one can only manage what they can measure. Engaging patients in active management of their disease metrics is essential to managing any chronic disease. Regularly scheduled measurements coupled with care coordination and appropriate intervention is the best approach.

人口健康管理:管理糖尿病人口

Scaled to a population level, the personal anecdote above demonstrates

how successfulpopulation health management首先要测量和准确地识别糖尿病人群，并监测疾病的发展趋势。These tasks have been difficult in the past, but advanced analytics tools and healthcare data platforms, such as the Health CatalystData Operating System (DOS™), are making population health monitoring more accessible.

By aggregating data from multiple sources, a data platform provides the foundation for sophisticated diabetes population management, such as the following:

• 建立并维护一个健全的糖尿病登记系统。
• Use diagnosis codes supplemented by clinical information to continue to define and refine the diabetes population.
• 确定没有接受最新检测的患者，包括糖化血红蛋白、空腹血脂、血压、微量白蛋白等。
• 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 toprioritize outreach efforts.
• 衡量糖尿病管理干预的成功。
• Discover variations in diabetes care across an organization.
• Reduce waste.
• Understand exactly how diabetes care affects an organization’s costs.

Creating Better Diabetes Outcomes

糖尿病患者和其他慢性疾病患者获得更好结果的最佳机会在于有效地利用数据。一个数据平台使世界杯厄瓜多尔vs塞内加尔波胆预测组织能够识别糖尿病高危患者和那些治疗或筛查差距。然后，组织可以对这些特定的患者群体进行优先和针对性的干预。良好的数据管理和患者访问也能使每个人更好地通过数据管理自己的糖尿病。

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

1. Introducing the Care Management Suite: A Data-Driven, Transparent Solution
2. Population Health Management: A Path to Value
3. Six Need-to-Know Guidelines for Successful Care Management
4. Social Determinants of Health: Tools to Leverage Today’s Data Imperative