TL/DR –
Bevey Miner, executive vice president of health care strategy and policy at Consensus Cloud Solutions, explains how extraction AI is aiding in the training of machine learning models to recognize and extract data from documents, thus providing structured data with confidence scores. Miner believes this approach is crucial in dealing with the challenges faced in the health care sector and facilitating adherence to evolving standards, particularly in light of limited resources. Utilizing extraction AI, she argues, can not only assist with structured data formatting but can also help meet emerging FIHR standards without the need for extensive financial or human resources.
AI Uses in Healthcare: Extracting Structured Data from Unstructured Documents
Executive vice president of health care strategy and policy at Consensus Cloud Solutions, Bevey Miner, highlights the role of extraction artificial intelligence (AI) in health care. The technology is training machine learning models to recognize and extract information from documents, converting unstructured data into structured data.
This AI approach is a possible solution to the challenges in health care, enabling organizations to comply with evolving standards with limited resources.
Emerging Technologies in Digital Health Strategy
HL7 FHIR [Fast Healthcare Interoperability Resources] and X12 are examples of structured data used in health care. Compared to these, unstructured data such as faxes, scanned images, and TIFF images need to be transformed into structured data to be usable.
The lack of structured data results in additional work for health care professionals, who often have to manually enter data before treating a patient. With a workforce shortage and increasing burnout, AI offers a solution by automating data entry.
Differentiating Types of Artificial Intelligence
Generative AI, which generates new data from prompt questions, is garnering much attention. However, there are concerns about its use and reliability. The focus here is on extraction AI or intelligent document extraction. This form of AI uses machine learning to recognize and classify information from documents, converting unstructured data into structured data.
Extraction AI provides a source of truth by referring back to the original document. For example, Consensus Clarity, a solution from Consensus Cloud Solutions, provides confidence scores for each data field. Generative AI, on the other hand, lacks a verifiable source of truth.
Extraction AI is a promising tool in health care, aiding the transition to structured data formats and helping organizations meet new FHIR standards without the need for extensive resources or expensive technology.
—
Read More Health & Wellness News ; US News