Coding and Natural Language Processing in U.S. Healthcare - Physician & Patient Interaction
By dmcgill
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Since roughly 1940, physicians and scientists have been trying to incorporate computers into healthcare processes to streamline diagnosis and reporting. However, technology did not become able to handle these tasks until the early 21st Century. -
Researchers at Latter-Day Saints Hospital in Utah, USA developed an electronic medical records systems in the late 1960s. It supported nursing, pharmacy, laboratory, and radiology healthcare operations and served as a model for today's EHR systems. -
San Diego, CA company Science Applications International Corp received a $1 billion grant from the department of defense to create an electronic military patient record management system, Composite Health Care System (CHCS). The software was installed in over 100 Department of Defense hospitals. However, interoperability between health record systems remained low since many non-DoD still used paper charts. -
President Bush details a plan to improve the health IT landscape in the US during his State of the Union Address. The plan focuses on innovation of record management systems by increasing funding and government coordination. Government funds were added to existing health IT grants and a new cabinet level position was created to review and modify regulations. -
President Obama signed the American Recovery and Reinvestment Act which also included the Health Information and Technology for Economic Clinical Health Act (HITECH). HITECH offered incentives for adopters of EHR systems and fines for those who did not adopt them in a timely manner. This act allows providers to make these changes to their record keeping systems in stages in order to ensure meaningful use. -
By 2015, 85% of hospitals were using some type of EHR system that met the Department of Health and Human Services' requirements. This was up from 12% in 2012. However, adopting meaningful use practices remained an issue. -
Today, new techniques for analyzing clinical data are being introduced to create a more full picture of patient and population health needs. One being researched is Natural Language Processing (NLPs) which looks for patterns in qualitative data such as provider health records. NLP helps lessen the burden of interoperability between providers and patients by examining trends in records to examine risk factors.