How do one leverage data for meaningful insights?

At the core of it, Healthcare Analytics is driven by data mindset and data culture where an organization has to look at its data sources and bring up potential workflows to derive value out of a data initiative.

From a provider stand point, a data is available in form of patient demographics, patient conditions, patient diagnosis information, treatment plans, prescriptions, discharge summaries, patient progress notes, patient lab reports, patient claim files. Once we have these records identified, one usually establishes a data model that can store them in a centralized location after mining them from different sources. And further leverage AI algorithms to learn “features”, which are then further leveraged to generate insights.

The generated insights shall help in identifying actions that shall help in performing some meaningful activities to control certain aspects of the healthcare services for example –

• To proactively identify and prevent revenue leakages that are one of the most pressing challenges within revenue cycle management process.
• To generate a treatment plan that is in sync with patient’s conditions thus eliminating probabilities of errors.  
• To identify claim files proactively that identifies abnormal price patterns leveraging an AI algorithm, such as over pricing for some services that need not be repeatable

 Apart from treatment and revenue cycle optimization, with smart systems like AI BOT driven simple symptom checkers or real time decision systems, they are being leveraged to quickly go to a root cause of a problem or arrive to a decision for a patient.