How population health analytics reduces healthcare disparities

population health analytics

The state of healthcare is changing. 

Today, medical data is giving us a better understanding of how healthcare reaches the communities that need it. Recent developments have shown that even though healthcare resources are available, getting these resources to those who need these remains a huge challenge.

Medical data is deepening our understanding of people’s health. It is now clear that healthcare should be a more holistic process; one that merges behavioural health, medical science, and social services to create a patient-centric system called whole-person care.

So, how do healthcare organisations meet the challenges of whole-person care while reducing the disparity in healthcare equity? Population health analytics might be the solution you are looking for.

What is SAS population health analytics?

SAS population health analytics refers to several software modules from SAS. These modules collect data from disparate sources and convert them into useful information. 

Medical data, both structured and unstructured, contains a variety of information on patient demographics.

A quick glance through the body of medical data reveals useful information, like patient age, their address, sickness, and treatment. On its own, the information is of limited value, but by using SAS analytics, you understand the healthcare needs of entire communities. Healthcare analytics helps you grasp the state of healthcare and better understand its structural problems, at least in terms of supply.

SAS also helps you gain insights at all levels, including entire population segments, helping you put the right healthcare programmes in place. In the long run, this reduces inequality and makes whole-person care a more achievable goal.

Analytics helps reduce healthcare disparities

One of the biggest problems you might be facing is analysing structured and unstructured medical data coming from different sources, like scans and Fitbit devices. 

Merging data from disparate sources and different formats is a trying task for any organisation, no matter what its network infrastructure is like.

SAS analytics can help you work around this problem through machine learning technology. 

Using SAS analytics, you can combine health data, genetic data, geographical data, and even behavioural data to better understand patient demographics, income disparities, and other major factors contributing to healthcare inequality.

You can then use this information to construct more effective healthcare programmes, prioritising the communities that need healthcare more urgently.

Using the right technology, you can also forecast healthcare demand for entire communities and develop medical programmes based on these requirements. Identifying patients that are at high risk and optimising healthcare resource allocation based on this knowledge is also much easier.

Bring whole-person care to patients using powerful analytics

Implementing whole-person care is a journey. 

It is a practice that incorporates multiple sources of information that go beyond medical data. Behavioural health, location, finances, and other non-medical factors that determine a person’s health or access to resources all play a role. Making these connections can be difficult when using archaic data management systems. 

Analytics can help make these connections and make whole-person care more achievable. 

Population healthcare analytics from SAS can help us create a more accurate picture of healthcare services. Through the use of machine learning technology, like NLP, SAS analytics can analyse the data to provide a complete picture for patients. 

Using SAS analytics, analysts can draw up charts to better understand patients based on their situation and healthcare needs. These insights allow you to chart more effective healthcare programmes for each patient.

Part of improving resource management is reducing the incident of error. Healthcare providers can make mistakes during surgeries or diagnosis. SAS analytics can reduce errors through data sharing and expand medical knowledge, deepen our understanding of medical procedures, reduce the rate of errors and improve patient safety and care.

Enjoy the benefits of proactive healthcare management with SAS analytics

As the industry trends towards whole-person care, you need systems that can help you become more proactive in managing healthcare resources. 

SAS analytics offers you the tools you need to create proactive healthcare programmes that reduce disparities while providing whole-person care that helps individuals lead healthier lives.


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