The Next Crisis In American Healthcare: ICD-10 And The Problem With Medical Coding Error

Presented by
Dr. Elliot Familant, CTO and Founding Partner
Artificial Medical Intelligence (AMI)

There is a change to the American Healthcare system in 2014 that will have a large impact on hospitals and it is not related to Affordable Care Act. This change, long in coming, affects a key aspect of the system by which hospitals and physicians are reimbursed for services provided. It is the change from existing medical coding system, ICD-9, to a new and greatly expanded coding system, ICD-10. Implementing this change involves extensive changes to hospital information systems but more importantly, it significantly affects the way Medical Coders will be doing their jobs in the future.

The key to a successful implementation of ICD-10 resides in the ability of these healthcare workers to do their job using this new medical classification list.

Yet, over 30 years of studies on human performance in using medical classification systems point to one conclusion. The systems are too complicated for individual coders and as a result, significant numbers of errors are made. The transition from ICD-9 to ICD-10 will likely exacerbate this problem. This talk will briefly discuss the history of medical classification lists and their role in the American Healthcare System today. The human performance literature associated with using these systems will be reviewed and an argument will be made that as the classifications have grown more complex, human performance has declined. Technical mitigation through the use of Computer Assisted Coding Systems will be discussed. However, it will be argued that a better solution would involve a fundamental revision to the way medical coding is done for billing and reimbursement purposes, specifically, the adaptation of a simplified classification system that would allow hospitals to generate bills in a timely and accurate manner.

Full Webinar Recording

Dr. Elliott Familant is the Chief Technical Officer and a founding partner at Artificial Medical Intelligence (AMI), a company that produces Computer Assisted Coding (CAC) products, in Eatontown New Jersey. He received his Ph.D. from Syracuse University in Experimental Psychology and worked at Bellcore and AT&T labs as a human factors engineer and service designer prior to his tenure at AMI. In his current position, Dr. Familant invented technologies that allow computer systems to extract medical codes from free text documents. Using these technologies, he led the first successful implementation of CAC technology in a hospital setting and has now successfully deployed AMI systems in over 120 hospitals in the United States. In 2014, Dr. Familant was issued a patent for a process he developed that establishes objective standards for human task performance when criteria for correctness are lacking or ill-defined. He currently resides in Tinton Falls, New Jersey with his wife Lynne and their three cats. He can be contacted at efamilant@artificialmed.com.