Introduction Countries use varying coding standards, which impact international coded data comparability. The 'main condition' (MC) field is coded within the Discharge Abstract Database as "reason for admission"or "largest resource use". Objective We offer a preliminary analysis on the frequency of and contributing factors to MC definition agreements within an inpatient Canadian dataset. Methods Six professional coders performed a chart review between August 2016 and June 2017 on 3,000 randomly selected inpatient charts from three acute care hospitals in Calgary, Alberta. Coders classified the MC as "reason for admission", "largest resource use"or "both". Patients were admitted between 1st January and 30th June 2015 and met the inclusion criteria if they were ≥18 years, had an Alberta personal health care number, and had an inpatient visit for any service outside of obstetrics. Agreement between the two MC definitions was stratified by length of stay (LOS), emergency department admission, hospital of origin, discharge location, age, sex, procedures, and comorbidities. Chi-square analysis and frequency of inconsistencies were reported. Results Only 34 (1.51%) of the 2,250 patient charts had disagreeing MC definitions. Age, emergency visit on admit, LOS, hospital, and discharge location were associated with MC agreement. Chronic conditions were seen more often in MC definition agreements, and acute conditions seen within those disagreeing. Conclusion There was a small proportion of cases in which the condition bringing the patient to hospital was not also the condition occupying the largest resources. Within disagreements, further research using a larger sample size is needed to explore the presence of MC in a secondary/tertiary condition, the association between patient complexity and disagreeing MC definitions, and the nature of the conditions seen in the inconsistent MC definitions.
CITATION STYLE
Wiebe, N., Quan, H., Southern, D. A., Doktorchik, C., & Eastwood, C. (2021). Describing agreement in the main condition coding field using Canadian ICD-11 inpatient data. International Journal of Population Data Science, 6(1). https://doi.org/10.23889/ijpds.v6i1.1397
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