J Langley1, S Stephenson, C Thorpe, G Davie. 1. Injury Prevention Research Unit, Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand. john.langley@ipru.otago.ac.nz
Abstract
OBJECTIVE: To determine the level of accuracy in coding for injury principal diagnosis and the first external cause code for public hospital discharges in New Zealand and determine how these levels vary by hospital size. METHOD: A simple random sample of 1800 discharges was selected from the period 1996-98 inclusive. Records were obtained from hospitals and an accredited coder coded the discharge independently of the codes already recorded in the national database. RESULTS: Five percent of the principal diagnoses, 18% of the first four digits of the E-codes, and 8% of the location codes (5th digit of the E-code), were incorrect. There were no substantive differences in the level of incorrect coding between large and small hospitals. CONCLUSIONS: Users of New Zealand public hospital discharge data can have a high degree of confidence in the injury diagnoses coded under ICD-9-CM-A. A similar degree of confidence is warranted for E-coding at the group level (for example, fall), but not, in general, at higher levels of specificity (for example, type of fall). For those countries continuing to use ICD-9 the study provides insight into potential problems of coding and thus guidance on where the focus of coder training should be placed. For those countries that have historical data coded according to ICD-9 it suggests that some specific injury and external cause incidence estimates may need to be treated with more caution.
OBJECTIVE: To determine the level of accuracy in coding for injury principal diagnosis and the first external cause code for public hospital discharges in New Zealand and determine how these levels vary by hospital size. METHOD: A simple random sample of 1800 discharges was selected from the period 1996-98 inclusive. Records were obtained from hospitals and an accredited coder coded the discharge independently of the codes already recorded in the national database. RESULTS: Five percent of the principal diagnoses, 18% of the first four digits of the E-codes, and 8% of the location codes (5th digit of the E-code), were incorrect. There were no substantive differences in the level of incorrect coding between large and small hospitals. CONCLUSIONS: Users of New Zealand public hospital discharge data can have a high degree of confidence in the injury diagnoses coded under ICD-9-CM-A. A similar degree of confidence is warranted for E-coding at the group level (for example, fall), but not, in general, at higher levels of specificity (for example, type of fall). For those countries continuing to use ICD-9 the study provides insight into potential problems of coding and thus guidance on where the focus of coder training should be placed. For those countries that have historical data coded according to ICD-9 it suggests that some specific injury and external cause incidence estimates may need to be treated with more caution.
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