HEDIS NLP is the use of NLP for HEDIS/Quality, where plans are rewarded for providing preventative checkups for patients based on their age and gender.

CQL stands for Clinical Quality Language - a SQL-style query language used for calculating HEDIS measure performance metrics.

Learn how to convert a medical record from between HL7 FHIR, HL7 CDA/C-CCDA, HL7 ADT, and PDF or other unstructured medical record data sources.

C-CDA stands for Consolidated Clinical Document Architecture - the most dominant structured electronic format at present, though it is not the most recent.

HEDIS is a set of criteria for evaluating if patients are receiving preventative care checkups relevant to them based on their age and gender.

Understand why PDF and TIFF medical records and other unstructured health care data sources are so difficult to parse.

This blog aims to compare and contrast known vendors, relative performances, and limitations of these OCR systems.

Given that all healthcare system in the world ultimately need to have a billing component, the concept of medical data categorization is essential.

We look at HL7v2, also called ADT for Admit Discharge Transfer - the first digitally standard of healthcare data adopted globally.

HL7 FHIR (also just called ‘FHIR’) is the fourth and most recent standardized representation of healthcare data for transmission.

In this article, we explore the importance and value of deduplicating patients, focusing on various method sets tailored to do so.

In this blog post, we give a tour of the definitions of AI and its often associated fields of study.

A brief description of how predictive analytics assist practitioners in in the prevention and treatment of illnesses.

A delve into how a medical record is structured under specifically the C-CDA (HL7 v3) and FHIR (HL7 v4) structures in detail.

What are the barriers preventing large language models from being in used more commonly in healthcare?

A description of the methods of healthcare data deduplication in the management of medical record data.

The evolution of medical NLP, highlighting significant milestones and discussing its profound impact on healthcare.