Population risk stratification has, so far, been biased toward structured data due to accessibility issues. As interest in long-term member wellness increases in importance it is the insights trapped in unstructured data that will become the differentiator in a changing and competitive market. The payers who are able to characterize member groups at a fundamentally more detailed level will have the advantage of population insight over those who struggle to do so.
Data sources that are increasing in scale and availability include electronic healthcare records (EHRs) data in Continuity of Care Document (CCD) format from providers, OCR notes about members, and nurses’ notes.
How can payers make effective use of unstructured data to stratify populations more effectively when much of their infrastructure is tied to structured data? Sources of unstructured data contain significantly more detail about members but are much more varied.
Here at Linguamatics Health, our Clinical NLP specialists understand the urgency and complexity of bringing together data sources, both structured and unstructured, in a workflow that gets you to insights you need quickly.