Find the insights about chronic disease hidden in clinical notes with Linguamatics NLP
Medicare advantage and commercial risk adjustment involves the review of clinical notes to identify diagnoses that are not captured in the discrete EHR fields. These are important for both member care and for reimbursement.
Finding these diagnoses is particularly important for a long term conditions such as:
For all of these conditions you need to show the evidence of face-to-face encounters and the date those occurred, to provide an audit trail.
Traditional manual coding processes are time consuming and repetitive and often require large teams.
Using Linguamatics Natural Language Processing (NLP) platform you can take an augmented intelligence approach to risk adjustment. NLP does the heavy lifting of scanning through the patient record to identify relevant sections, enabling the reviewer to jump to relevant evidence or place of interest. This approach provides a significant improvement in efficiency.
For populations with complex comorbidities, Linguamatics NLP platform can identify missing diagnoses from member populations which can be used for risk assessment such as adjusting reimbursement member calculations for hierarchical condition category (HCC) codes. Identifying key disease terms from clinical notes in this semi-automated process results in significant improvements in efficiency and improved reimbursement.
The Linguamatics augmented intelligence workflow processes the clinical notes for each patient with comorbidities and identifies codes for missing complications and diagnoses (e.g. retinopathy or skin ulcerations with Diabetes patients), these results and supporting evidence are then reviewed and validated. Using this approach can lead to a 50% reduction in the time it takes to find and review codes.
The flexibility of Linguamatics NLP platform means it can be used for risk adjustment in-addition to call center analytics, population health analytics to identify Social Determinants of Health (SDoH), and quality measures reporting.