An EMR is a digital tool that permits patient medical data to be stored, as opposed to traditional paper medical records.

The concept of AI making healthcare decisions from patient healthcare data sources is difficult to accept, driven by a paradox driven by two statements.

A prior authorization is an approval from a health plan, required before specialized services or medications are provided to ensure that they can be paid for.

Disability NLP is the use of NLP to detect evidence of disability in structured and unstructured medical records.

Summarization remains the highest utility of healthcare LLM AI. We cover expected developments in 2025 from most to least significant for the healthcare domain.

Medical record deidentification NLP is the use of NLP in the removal of protected health information (PHI) from a data asset.

SDoH NLP is the use of NLP to detect aspects of patients that are peripheral to their medical status but have a large impact on their wellbeing.

Healthcare interoperability is the ability to transmit and receive healthcare data in a frictionless and secure manner between healthcare participants.

Risk adjustment is component of the US health economy whereby federal resources are distributed to health plans based on membership quantity and attributes.

Tenasol is one of the only companies offering AI/NLP HEDIS evidence detection with advanced machine learning technology in a clear an transparent way.

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.

The healthcare data industry feels poised for policy transformations with the adoption of AI, healthcare interoperability, and introduction of HL7 FHIR.

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.

FHIR data is a unique new generation of data whereby the guardrails are narrowly defined, data transfer is fast, but anything is still possible.