According to Accenture, “cyber coders” i.e. certified clinical coders equipped with AI tools, provide an opportunity to deliver faster and smarter clinical coding while facilitating revenue assurance for hospitals. Early results at the proof of concept stage, indicate that the combination of coder plus artificial intelligence was comparable to or better than a human coder alone.
In consulting with Australian CEOs and CIOs of 30 different healthcare organisations, they found that ICD-10 codes are used inconsistently and create challenges for healthcare administrators to accurately forecast revenue. They found the variability of coding assignment is between 20 to 30 percent and varies by individual, by hospital and by state. Better documentation of ICD-10 diagnosis coding leads to better revenue assurance, improved decision making, resource allocation and improved hospital administration.
According to both the Australian Institute of Health and Welfare and the Health Information Managers Association of Australia research (Ref 1), Australia suffers from an undersupply of skilled, certified clinical coders. Artificial Intelligence won’t take away jobs from clinical coders, however, it will augment their role and increase their capacity to deliver faster, more accurate health information services that are critical to health system revenue. You can find out more about the role of a clinical coder from the Clinical Coders’ Society of Australia.
Busy clinicians focus on providing high quality patient care and their case notes provide the source data for coders. Increasing the numbers of “cyber coders” may provide insights into how case note documentation can be improved by streamlining the accurate flow of information between clinicians and clinical coders so that clinical terms can be codified according to the Australian Coding Standards.
Accenture is a member of the AAAiH. You can read the full Accenture blogs on this topic here:
Intelligent clinical coding: Rethinking hospital revenue (Part I)
Intelligent clinical coding: Rethinking hospital revenue (Part II)
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