ICD-10 Transition Aided By Online Tool

By Katie Wike, contributing writer

A tool developed by the University of Illinois at Chicago and the University of Arizona should provide support for providers during the ICD-10 transition through bidirectional mapping of the codes.

A study published in the Journal of the American Medical Informatics Association has detailed an online tool that could prove very useful to providers as they transition to ICD-10. “Examining the network graphs of individual ICD-10-CM diagnosis codes from the online tool can provide a quick view of the challenges facing administrators evaluating high-cost diagnoses,” the authors claim.

Researchers created a bidirectional map of the code sets in ICD-9 and ICD-10, according to iHealth Beat. They identified 36 network patterns within the codes and arranged them into 5 categories: identity; class-to-subclass; subclass-to-class; convoluted; and no mapping. From there, the codes were analyzed - and researchers found only 4,127 ICD-10 codes had straightforward translations from ICD-9.

EHR Intelligence reports the study’s authors believe the need for tools will be necessary when the transition occurs this October. “While standards and guidelines are taught to professional medical coders9 who attempt to normalize the stylistic differences, many clinics and physicians create a punch sheet, or a list of codes, that will likely introduce biases in the use of ICD-10-CM codes,” the researchers maintain.

“We are providing a web portal and annotated tables to help administrators, clinicians, and coders quantitatively and qualitatively evaluate the financial and compliance risks associated to querying and analyzing datasets coded historically in ICD-9-CM and thereafter in ICD-10-CM,” concluded researchers. “Indeed, consulting firms and specialty organizations have even recommended dual coding during a few months of the transition period, which very few organizations can afford.”

The researchers ask that future studies observe inconsistencies across and variations between healthcare organizations to determine how coding styles affect reimbursement and the usefulness of coding data for secondary and tertiary purposes.