ICD9 vs ICD10 A comparison using Veterans Aging Cohort Study Data Farah K-Khan, Melissa Skanderson, Cynthia Brandt, Janet Tate, Amy Justice VACS-COMpAAAS Scientific Meeting December 13, 2016

ICD9 to ICD10 Impact on Research Data No Laterality (left or right side) Laterality added to increase specificity M21.722 – Unequal limb length, Left Humerus Non-specific codes Specificity increases depth of data Limited combination codes Extensive combination codes 14,000 codes 69,000 codes Length is 3 to 5 Length is 3 to 7 ICD10 detailed and specific, used globally Potential for researchers to use more targeted queries and get more specific outcomes. Researchers need to be aware of implications of mapping relationships where data overlaps ICD transition

Mapping Tool and Strategies Used the AHRQ MapIT 2015 tool General Equivalence Mapping(GEM) Batch processing of ICD9 using backward and forward mapping Created a Crosswalk Validation queries using Structured Query Language(SQL) Mapping tool and crosswalk Local validation and data quality assessment after mapping

ICD CODES COMPARISION Unique Patients in VACS 1 Year Comparison October 2014 to October 2015 vs. October 2015 to October 2016 Sample restricted to people who were alive and seen in both time intervals Inpatient Outpatient Percentage of unique people in VACS with alcohol related conditions, Diabetes, Hypertension, and Cocaine use

Alcohol CODES COMPARISION Unique Patients with any alcohol Diagnosis 1 Year Comparison - October 2014 to October 2015 vs. October 2015 to October 2016 Sample restricted to people who were alive and seen in both time intervals

Goals Evaluate data trend across time and code sets Evaluate original estimates compared to newer estimates for more conditions Make determination of programming strategy based on estimates Promote collaborative definition of conditions in ICD10 across cohorts With time we may have less missing data We may have to maintain ICD9 for older data Compare ICD9 CM estimates with ICD10CM for more conditions