Managing clinical and financial risk in today’s ever-changing health care environment is a complex proposition. But with a good of understanding of patients’ potential risk for costly health complications, organizations can turn the risk of value-based reimbursement into opportunity to provide higher quality, more cost-efficient care. Advanced analytics can give health care providers the understanding they need to succeed.
With analytics, organizations can efficiently gather, clean and validate data from multiple sources and then use that data to discern patterns and make more accurate predictions of their patient population’s health needs. This data will help them focus on the patients who have the most potential for clinical improvement—and cost savings.
Gathering the big data is possible because of the vast amounts of claims, clinical and other data generated by practices.
But analytic results can only be as good as the data by which they are generated. And much of a health care providers’ big data is just that—a large amount of unstructured numbers. Only about 20 percent of electronic medical record data is marked, labeled or tagged so that it can be identified and acted upon. Big data must be cleaned, validated, normalized and extracted. Only then will it become a powerful tool to help organizations create a true picture of their patients and practice.
Check out this video below to learn more about how analytics can help organizations make better clinical and financial decisions.
In our next post, we’ll look at how analytics allows organizations to create a predictive model that highlights patients who need extra clinical attention.