Development and validation of data quality rules in administrative health data using association rule mining

Introduction Data quality assessment is a challenging facet for researches using coded administrative health data. Our previous study had demonstrated the potentials of association rule mining to assess data quality. The objective of this study is to develop and validate a set of coding association rules for data quality assessment. Objectives and Approach We used the Canadian reabstracted hospital discharge abstract data (DAD) with clinical diagnosis coded in International Classification of Disease – 10th revision, Canada (ICD-10-CA) codes for rule development. The DAD data were divided into 5 age groups. Association rule mining were conducted on reabstracted DAD in each age group to extract ICD-10 coding association rules at the three and four digits levels. The rule strength was assessed using support and confidence. The rules will be reviewed by a panel of 5 physicians and 2 coding specialists to assess their appropriateness from clinical and coding perspectives using a modified Delphi rating Results In total, 975 rules at the three digits level and 822 rules at the four digits level were learned from the data. Half of the rules were in the age group of ≥65 and no rules were found in the age group of 5 to 19. The interquartile range of rule confidences were 0.112 to 0.425 in the three digits level and 0.073 to 0.222 in the four digits level. Two-thirds of rules had the diagnosis codes related to endocrine and metabolic disorders and diseases of circulatory, respiratory and genitourinary systems. The panel review will be conducted in early April and will have the final set of rules available before the conference. Conclusion/Implications This study developed a set of validated ICD-10 coding association rules and creates a useful tool to cost-effectively assess data quality in routinely collected administrative health data

Training Coding Specialists for the Future: Methods and Materials for the Beta Version of ICD-11

Introduction In June 2018, the World Health Organization (WHO) will release the 11th Version of International Classification of Diseases (ICD-11). New training methods and materials are required. As a WHO Collaborating Center, with Canadian Institute for Health Information (CIHI) members, we trained 6 coding professionals for testing ICD-11 coding processes. Objectives and Approach The objective was to achieve a high level of inter-rater reliability using ICD-11 for acute care chart coding. We used Adult Learning principles with CIHI members and 6 certified coding specialists to co-create presentations, practice materials, and decision trees to teach knowledge and skill with ICD-11 tooling and content. Training involved 14 hours of interactive learning plus additional practice hours. A bank of questions and coding scenarios tested knowledge and application of ICD-11 terminology and principles. Coding was undertaken on a set of 3000 randomly selected inpatient Calgary hospital discharges as part of a large CIHR funded ICD-11 field trial. Results The coding team achieved an average score of 84% on the ICD-11 coding quiz and 0.65 (0.33 -1.0) agreement on parent code of main condition for the coding quiz scenarios.  60 inpatient charts were coded by more than one coder to test inter-rater reliability.  Agreement was ≧ 0.80 for the majority of parent codes for main condition. Coding differences may be due to unfamiliar code choices or training gaps. New code descriptions in ICD-11 enhance code selection. Challenges included training while codes were being built in the ICD-11 browser, and minimal coding rules or standards. Conclusion/Implications Recommendations include more code descriptions in the browser and rules in a reference guide, teaching from simple to complex conditions, and multiple scenarios with ‘gold standard’ codes for practice. Reference Guide, Coding Tool, and Browser recommendations have been shared with members of the WHO Morbidity and Quality & Safety Advisory groups