From population health analytics to risk adjustment and quality measures, our healthcare NLP solutions allow payers to  improve member care and reduce member risks.

Population Health Management and Analytics

To enhance population health analysis and identify the care needs of individuals, providers and payers must extract insights from data stored in unstructured text in EHRs.

Social Determinants of Health (SDoH)

Identifying the social determinants of health (SDoH) hidden within clinical notes and other patient data enables providers and payers to build a complete picture of their patients and members.
Risk adjustment for payers

Risk Adjustment

Many provider organizations are challenged with comprehensively and accurately identifying and documenting risk-adjusted conditions. Accurate risk adjustment leads to more appropriate preventative care initiated to ensure the most cost-efficient care can be delivered.
Voice of the customer data

Voice of the Customer

Voice of the customer (VoC) call feeds can provide a rich source of real world data (RWD). Pharma and healthcare organizations need to understand how their customers (e.g. patients, clinicians) are responding to marketed drugs and gain a broader picture of patient reported outcomes

Quality Measures

The regulatory burdens of initiative quality measures continue to put a strain on overworked hospital departments, and payers alike.

Big Data Analytics in Healthcare

The term "big data" was coined in the early 2000s by industry analyst Doug Laney. In Laney's definition, the term referred to information existing in large data sets, with high update rates and in a variety of formats.
Case Studies

Success Stories

Case Study: Large Payer Improves Patient Stratification using Unstructured Big Data
Case study

Case Study: Large Payer Improves Patient Stratification using Unstructured Big Data

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