93 Coding Disparity and Specificity During Emergency Department Visits After Transitioning to the Tenth Version of the International Classification of Disease

Abstract

The purpose of this study was to examine coding disparity and specificity after transitioning from ICD-9 to ICD-10. We sought to evaluate whether the increased granularity inherent in ICD-10 has led to greater specificity in diagnosis and coding. The study took place between 2014 and 2017 before and after the conversion from ICD-9 to ICD-10 within the Veteran’s Health Administration and looked at a national cohort of emergency department visits. Two study groups were looked at. The ICD-9 group looked at the first 6 months of years 2014 and 2015, respectively. The ICD-10 group looked at the first 6 months of 2016 and 2017, respectively. These time periods were selected so as to provide uniformity in the before and after groups as well as to avoid the immediate transition period around October 2015. For each visit, participants were characterized by age, sex, ethnicity, comorbidity, utilization and diagnostic coding disparity and specificity. The Chi-squared test was used to examine differences among characteristics. IRB approval was obtained from the University of Maryland and Baltimore VA Medical Center. The cohort included 2,058,189 emergency department visits by 1,245,586 unique individuals over the study period. When looking at the distribution of codes 5365 unique ICD-9 codes were employed compared with 13,632 ICD-10 codes. A two-sample Kolmogorov-Smirnov (D(2000)=0.255, p<0.001) revealed with both ICD-9 and ICD-10 codes having a very large skew (skewness=3.460, kurtosis=17.005). Similarly, the top 100 ICD-9 codes were used in 58% of encounters while the top 100 ICD-10 codes were used in 50% of encounters. The encounters coded with ICD-10 were not consistently coded with more specificity. Forty-three percent of ICD-9 encounters included multiple ICD codes while only 34% of ICD-10 encounters included multiple codes. Average patient age was 60 years and 90% were male. Among the notable comorbidities were coronary artery disease (18%), diabetes (28%), opioid related disorders (19%) and PTSD (20%.) There were no statistical differences in the demographics within (p=0.318) or between groups (p=0.303), or in the distribution of diagnoses within (p=0.999) or between groups (p-0.905), with 95% confidence intervals and 21 degrees of freedom. The most common ED diagnoses during both the ICD-9 and ICD-10 time periods were back pain followed by bronchitis, chest pain and abdominal pain. When comparing unspecified codes to more specific ones, the percent of unspecified codes for back pain were similar for ICD-9 (32%) and ICD-10 (31%). The percent of specified for bronchitis were also similar for ICD-9 (17%) and ICD-10 (16%) For chest pain, ICD-9 encounters (29%) used more specific codes than ICD-10 (18%). For abdominal pain, ICD-10 encounters (66%) used more specific codes than ICD-9 (35%). We examined coding disparity and specificity using the International Classification of Diseases, after the transition from ICD-9 to ICD-10. The distribution of diagnoses remained unchanged before and after the transition. However, there were fewer encounters with multiple codes with ICD-10. While the encounters after the transition to ICD-10 used more unique codes, providers did not consistently exploit these to create more specific codes. The magnitude of lost revenue has not been studied.