Population health considers the health status and outcomes of an entire group of people, rather than focusing just on specific individuals. Is your population health strategy ready to drive results?
Every patient is unique.
That’s a good guiding principle for any clinician, especially when they have a patient right in front of them. It reminds them to pay attention to the details and remember that the patient is a person, an individual, not just a chart or a diagnosis.
But to truly make a difference, healthcare providers and leaders also need to think strategically about groups of patients. They need to think about entire patient populations.
Focusing on addressing population health is increasingly important in this era of value-based care. In fact, many organizations are turning to population health analytics to help them achieve value-based care, as a recent report from Deloitte noted.
What is Population Health?
According to the Institute for Healthcare Improvement (IHI), the definition of population health is: “the health outcomes of a group of individuals, including the distribution of such outcomes within the group. These groups are often geographic populations such as nations or communities, but can also be other groups such as employees, ethnic groups, disabled persons, prisoners, or any other defined group.”
In other words, population health considers the health status and outcomes of an entire group of people, rather than focusing just on specific individuals. It incorporates data from individuals, and it identifies risks and patterns and uses that information to predict behaviors and design prevention strategies.
It’s important to understand that the definition of “population” is flexible. The National Committee for Quality Assurance (NCQA) developed a population health management model that begins with identifying the population you’re trying to address. That population can vary in size and focus. NCQA uses patients over 65 who receive long-term services as an example of a particular patient population that could be the center of a program.
Using Data to Drive Population Health
As the American Hospital Association’s Center for Health Innovation emphasizes, a population health management program is one that strives to improve clinical outcomes of a particular group of patients by using care coordination and patient engagement.
A good population health management program relies on clinical data about patients and the factors that affect their health and well-being, such as social determinants of health. To deliver care that’s based on solid, updated data, you first must acquire that data. That can entail using a reliable analytics platform to collect the data that you need and analyze it for opportunities to identify needs. This will help your organization obtain actionable data about your patients.
For example, you can use data from performance measurement programs that help you identify patients at risk for certain medical conditions such as diabetes and heart disease. Using that data, you can then develop and deploy intervention programs to target those specific patient groups.
Predictive Modeling and Risk Stratification
Predictive modeling can help you achieve risk stratification, a key part of population health management. As James Dom Dera, MD, wrote in 2019 for Family Practice Management, “Risk stratification is a technique for systematically categorizing patients based on their health status and other factors. It allows for risk-stratified care management, in which practices manage patients based on their assigned risk level to make better use of limited resources, anticipate needs, and more proactively manage their patient population.”
That is, you can determine which of your patients are at highest risk for poor outcomes and design interventions that are most likely to be effective. (For example, Dera noted that his practice assigned longer visit times to patients with chronic diseases who fell into the highest risk categories.) You can design other interventions, based on your available resources, for the remaining assigned risk levels. Then you can track the efforts to make sure the interventions are achieving their intended purpose.
You don’t have to rely solely on the data from your electronic health records. As Dera noted, you can use both objective data and input from physicians and other staff to assign risk levels.
It’s important to note that assessing risk and assigning risk stratification scores is an ongoing process. Life happens. And your patients’ health, living environment, financial situation and other circumstances may change, which would alter their risk profile. Your organization should determine how often to revisit each patient’s risk level to see if it needs to be adjusted.
The Bottom Line
A population health management program is based on the premise of collecting and analyzing data to help you be proactive in the future. You want to be aware of the risk factors that affect certain groups of people so that you can design targeted strategies that allow your team to intervene early.
Ultimately, this approach can result in better patient outcomes. It can result in significant savings for your organization, too, by targeting issues before they require more expensive interventions, such as hospitalizations.