To improve member care and reduce risks you need to fully understand your patients, that means making using of all available data in the EHR. Learn how we help healthcare payers and insurers gain value from their text with clinical NLP Solutions including: Social Determinants of Health, population health analytics, risk adjustment, quality measures and more.

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

Social Determinants of Health (SDoH)

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.

Quality Measures

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

Risk Adjustment

Medicare advantage and commercial risk adjustment involves the review of clinical notes to identify diagnoses that are not captured in the discrete EHR field. Manual processes are time consuming and repetitive. NLP can do the heavy lifting for you.

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.

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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