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Artificial Medical Intelligence to introduce medical record tech

AMI has released the full version of HCC Coding as part of the EMscribe suite of tools in support of medical records processing and abstraction.

Artificial Medical Intelligence (AMI) has released the full version of HCC Coding as part of the EMscribe suite of tools in support of medical records processing and abstraction.

The new completed HCC Coding Solution is built on the automatic generation of ICD10 codes and supporting demographic data for reimbursement which includes V22 HCC, the latest version from CMS.

HCC is a payment model mandated by the Centers for Medicare and Medicaid Services (CMS) in 1997. Implemented in 2003, this model identifies individuals with serious or chronic illness and assigns a risk factor score to the person. At present, there are more than 9000 ICD-10 codes that map to 79 HCC codes in the Risk Adjustment model.

Integrated and automated

AMI’s unique HCC module is offered as an integrated and automated component of its EMscribe coding and clinical abstraction suite which is able to support the requirement of HCC code submission. EMscribe automatically generates the individual’s health conditions using ICD10 diagnoses and demographic data directly extracted from the medical record and assigns the risk adjustment attributes to the case based upon a combination of the individual’s health conditions and demographic details. An HCC score is then generated by the EMscribe system and is either displayed in AMI’s Graphical User Interface or provided through an AMI’s Application Protocol Interface.

Administrative pressure relief

“AMI continues to lead with its innovative technology designed to mitigate the constant stream of new and more difficult administrative pressures and requirements on the healthcare system”, stated Stuart Covit, Chief Operating Officer.

“We are focusing on providing Artificial Intelligence to abstract information from the medical record, so when new mandates like MACRA come up we can adjust our technologies to address the required data elements.”

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