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COMPARATIVE STUDY
JOURNAL ARTICLE
MULTICENTER STUDY
RESEARCH SUPPORT, NON-U.S. GOV'T
Quality of data regarding diagnoses of spinal disorders in administrative databases. A multicenter study.
Journal of Bone and Joint Surgery. American Volume 1997 October
The purpose of the present study was to evaluate the accuracy of data regarding diagnoses of spinal disorders in administrative databases at eight different institutions. The records of 189 patients who had been managed for a disorder of the lumbar spine were independently reviewed by a physician who assigned the appropriate diagnostic codes according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). The age range of the 189 patients was seventeen to eighty-four years. The six major diagnostic categories studied were herniation of a lumbar disc, a previous operation on the lumbar spine, spinal stenosis, cauda equina syndrome, acquired spondylolisthesis, and congenital spondylolisthesis. The diagnostic codes assigned by the physician were compared with the codes that had been assigned during the ordinary course of events by personnel in the medical records department of each of the eight hospitals. The accuracy of coding was also compared among the eight hospitals, and it was found to vary depending on the diagnosis. Although there were both false-negative and false-positive codes at each institution, most errors were related to the low sensitivity of coding for previous spinal operations: only seventeen (28 per cent) of sixty-one such diagnoses were coded correctly. Other errors in coding were less frequent, but their implications for conclusions drawn from the information in administrative databases depend on the frequency of a diagnosis and its importance in an analysis. This study demonstrated that the accuracy of a diagnosis of a spinal disorder recorded in an administrative database varies according to the specific condition being evaluated. It is necessary to document the relative accuracy of specific ICD-9-CM diagnostic codes in order to improve the ability to validate the conclusions derived from investigations based on administrative databases.
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