Publications

Vocabulary service supporting the longitudinal patient electronic medical record

03/20/2008

Frank Naeymi-Rad, PhD, MBA

Introduction

The process of abstracting clinically significant knowledge from the patient chart has been a major challenge for HIM professionals. This process is compounded when non-clinical staff conducts the abstraction. As the role of HIM professionals are expanded from administrative to clinical delivery support, liability associated with HIM professional abstraction is compounded. The current evolution of natural language processing (NLP) has created an opportunity to help medical record professionals speed-up the identification and coding of key clinical findings. Enhancements in medical terminology, like SNOMED® CT, has also added significant speed in mapping clinical findings to target coding systems such as SNOMED®, RxNorm, NDC, ICD, LOINC and CPT®. To date, most NLP technology has been used within a retrospective setting. As these systems learn more about the usage of each medical specialty terminology, it is likely that the technology will be increasingly adopted by application providers. However, the HIM industry continues to rely on non-clinical staff's interpretations of the results of automatic or manual abstraction. Typically, abstraction is performed at the end of the patient encounter primarily to support billing and reimbursement. Therefore, financial or administrative codes are the most common targets for the abstraction.[..]

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