What Is the Role of Data Analytics in Population Health Management?
Data analytics can assist population health management in improving patient outcomes, enhancing care management, and address social determinants of health.
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- Population health management has become an important method for improving community health.
As the population health management market continues to develop in the healthcare space, systems must gather data from multiple sources, apply analytics to the data, and manage the care for the population.
The health management method relies on data analytics to identify populations in need of care, measure the care provided to those populations, and deliver care to the correct people.
The process of population health management begins by gathering key demographic and clinical data about patients, often from electronic health records.
Through data analytics and population health management, providers can improve patient outcomes, enhance care management, and address social determinants of health.
Using data to improve patient outcomes
To best serve a group of individuals, providers, and physicians must utilize data. Big data is often used to address population health concerns to assist large communities of people.
In a panel covered by HealthITAnalytics, Jefferson Health’s medical information officer Bracken Babula explained how understanding patient metrics and risk scores development is critical to the data collection process.
“Some of the things that we’re trying to start figuring out how to use are risk scores that might pull a number of different metrics from all over the system. Basics like age, gender, insurance, and more complicated things like certain past medical history and lab values. We can then pull that all into a broader overview of the patient, with the idea being that you can then target your outreach,” Babula said.
Through data analytics, medical professionals can gain insights into patient needs and allocate resources to those who may need them more, improving care management.
Enhancing care management
By implementing data analytics, providers are replacing the “one size fits all” care mentality to deliver value-based care.
The purpose of value-based care is to standardize the healthcare process by enhancing the patient experience, the health of patient populations, and the cost of care. Through data analytics, providers can assess which processes are the most effective methods for wellness and prevention within value-based care models.
According to Cleveland Clinic, “Prevention of health (through quitting smoking, dietary and lifestyle changes, exercise, etc.) reduces the need for expensive tests, procedures, and medications. You’re staying well cuts healthcare costs for everyone.”
With population health management, organizations can consider physical and social determinants of health that may impact individuals and focus on “well care” rather than waiting for a patient to become ill.
Addressing social determinants of health needs
Increasingly, data analytics and population health management are being used in work with social determinants of health. At Stanford Children’s, researchers are collecting data from patients to better understand environmental factors that could influence an individual’s health.
“The one huge aspect of this that we’re looking at Stanford Children’s is around the social determinants of health. Understanding what are the conditions, beyond just the typical things you collect in a physician visit. Is there domestic violence or food insecurities, or things like that, that really would ultimately affect the patient’s health down the road and may have different interventions than a typical physician visit?” revealed Stanford Children’s chief analytics officer Brendan Watkins.
Jefferson Hospital also studied social determinants of health regarding the COVID-19 vaccine. The hospital used metrics called the social vulnerability index and the community need index to assess and target where the vaccines should go.
The future of big data in population health management
As data analytics continues to grow in the population health management space, Geisinger director of machine learning Abdul Tariq told HealthITAnalytics that she envisions consumer health informatics expanding not only in healthcare but also in the tech and provider world.
“As more and more people get these wearable devices like Fitbit, Apple Watch, that data will start getting captured, then there will be a market that will open up where technology companies will start providing some of these insights that traditional health systems have provided,” Tariq said.
“With that regulation, I’m sure there will be policy enactments that will change how providers deliver care. Then, eventually, the policy will shift how providers, systems, get into this space, and what that means.”
With wearable devices, there is an opportunity for providers to access that data to improve patient outcomes. Through data analytics and population health management, systems can identify populations in need, stratify risk, and track patient progress.
