How does population health analytics benefit providers?

Population health management has garnered significant interest in recent years. As populations age and live longer, the need to better understand and care for these individuals – who often have chronic diseases and health risks, and experience unique social and economic factors – also rises. Population health management spans across the healthcare continuum, with many organizations throughout the care journey playing a role in this effort.

But how does population health analytics benefit providers in managing their patient cohorts? This blog aims to summarize how data analytics support the treatment and management of key patient populations.

What is population health analytics?

Before we can understand the role of data in population health management, we must understand what population health analytics is. As defined by Tableau, “population health analytics is using data to enable healthcare providers to make informed management and strategy decisions based on data analytics.”

In other words, data analysis is a must-have element of population health management. As in many efforts of healthcare, though, data is often siloed, complex, or not complete, making it incredibly difficult to analyze and derive meaningful insights from. For providers to truly get the most out of population health analytics, they must have secure access to vast amounts of standardized, accurate data – including clinical data, claims data, patient sociodemographic data, and more – and the ability to perform the appropriate analyses.

Some providers have already mastered this effort. They’re applying population health analytics to make informed decisions in managing their patient populations, to understand care gaps, and more.

How population health analytics benefits providers: 3 industry examples

1. Predicting patient risk

By compiling and making sense of large amounts of population data, providers can gain more focused patient insights. They can group similar types of risk together to inform patient engagement and treatment based on risks such as

chronic conditions, risk of future hospitalizations, diagnoses of substance abuse or mental health, and more.

Armed with such information, providers can take a more methodical, informed approach to every at-risk interaction. Risks of the same kind can have one overall strategy rather than having to reinvent engagement efforts every time.

Still, a population-wide view of patient risks with the ability to drill down into patient-specific details allows for focused, personalized encounters while creating better speed and efficiency from a cohort management perspective

2. Identifying social determinants of health (SDOH) and addressing barriers to care

Patient risks are often the result of pre-existing conditions affecting their overall health. Barriers to care, though, can get in between any patient – healthy or at-risk – and the providers they need to see.

Barriers to care include anything from lack of transportation or low income to food insecurity and domestic violence. Regardless of the one or many barriers that patients experience, the result is the same: It’s harder for them to see their provider, which is likely to reduce how often they engage in their care and could negatively impact their health outcomes.

That is, unless provider organizations and hospital systems understand the barriers patients are facing. When armed with access to population health analytics, large provider groups can identify common barriers to care in their communities – and they don’t have to compile and analyze the data on their own! Payer partners can work with providers to provide data visibility and drive health equity initiatives.

This empowers providers to step in to help resolve the obstacles, which may mean funding programs or be as simple as shifting staff priorities to new forms of engagement, outreach, and even care delivery – a more cost-effective, yet still impactful approach to help get patients past their barriers and to their visits

3. Measuring results

As the shift from volume to value progresses, so does the need for providers to measure the value they are delivering to their patients.

Providers can leverage population health analytics to demonstrate the quality of care they’re giving. This in turn helps them out-perform other providers when negotiating value-based program initiatives with payers or simply helps them gain

market share as patients begin to compare provider performance against each other.

To stay ahead in these scenarios and similar situations, providers need data to ensure they’re performing on par – or better than – their competition. This is another example of the need for, and value in, payer-provider data visibility.

The same population dataset that informs addressing social determinants of health can be applied to measure value-based performance, furthering the advancement of patient health outcomes. Population health analytics can be continuously referenced to drive ongoing efforts for better performance across quality initiatives, patient outcomes, and in improving the patient experience.

Leveraging population health analytics at your organization

Getting value out of population health analytics begins with having access to large volumes of patient data. With Inovalon, healthcare organizations can reference the industry’s largest primary source dataset to better manage their patient populations.

Learn more about how our population health insights can support your population health management needs.