One year of ICD-10: First half 2016 data shows coding trends and impacts

One year following the official implementation of ICD-10, the coding industry is beginning to report valid results regarding accuracy, productivity, and denial trends. While some of these facts and figures are self-reported by HIM directors and anecdotal in nature, other findings are grounded in hard, fast coding performance data. Such is the case with the results from Central Learning (www.centrallearning.com), a web-based system that electronically assesses coder knowledge using real medical record cases and expert-verified answer keys.

This article summarizes coder performance data as measured across 50 health systems and 300 coders as of June 30, 2016. It compares these findings with other industry reports and extrapolates key findings for HIM directors and revenue cycle executives. Since coding and diagnosis-related group (DRG) assignment are the major drivers behind health system revenue streams, consistent data analysis helps to ensure accurate coding and reimbursement.

According to Central Learning data, coding accuracy is slightly increasing after nine months under ICD-10 for both experienced coders and coders-in-training. While the industry overall still lags behind the 95% accuracy benchmark achieved in ICD-9, we're getting closer in all three major patient types: inpatient, outpatient, and emergency services.

Fifty health systems are represented in the data, providing a broad-based assessment. We compared coder accuracy from Q1 (January 1?March 31) with Q2 (April 1?June 30) to identify recent, timely trends in code quality. The figure on p. 13 lists the most current benchmark of our status through June 30, 2016.

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