MacIntyre C R, Ackland M J, Chandraraj E J, Pilla J E
Victorian Infectious Diseases Service, Royal Melbourne Hospital, Parkville, Vic.
Aust N Z J Public Health. 1997 Aug;21(5):477-82. doi: 10.1111/j.1467-842x.1997.tb01738.x.
Hospital morbidity data in the form of International classification of diseases, 9th revision, clinical modification codes are often used for epidemiological studies and disease surveillance. We aimed to evaluate the reliability of the Victorian In-patient Minimum Database for use in epidemiological studies and disease surveillance. Data from 1993-94 were collected, as part of a coding audit of public hospitals in Victoria, from 7052 randomly selected records. The frequency of discrepancy in any coding field was 53 per cent, and of discrepancy in the principal diagnosis, 22 per cent. New Australian national diagnosis-related group (ANDRG) codes were assigned as a result of discrepancy in 13.6 per cent of cases. Discrepancy rates increased with increasing rarity of ANDRG, from 50 per cent to 56 per cent. Predictors of change in ANDRG assignment were discrepancy in the principal diagnosis, ANDRG frequency of over 0.6 per cent, more than three diagnoses, medical ANDRGs, length of stay over five days and rural hospitals. Rates of any discrepancy increased from 36 per cent in patients with one diagnosis to 94 per cent in patients with 12 diagnoses. The discrepancy rates were consistent with those of other studies. Coding discrepancy is likely to be caused by universal difficulties associated with the coding of hospital records, rather than any unique local problems. The predictors of discrepancy suggest that more complex cases are more prone to coding discrepancy. In areas where the database is less reliable, use of a supplementary data source, such as link-age studies, would improve reliability.
以国际疾病分类第九版临床修订本编码形式呈现的医院发病率数据常被用于流行病学研究和疾病监测。我们旨在评估维多利亚州住院患者最小数据库在流行病学研究和疾病监测中的可靠性。作为对维多利亚州公立医院编码审核的一部分,收集了1993 - 1994年7052条随机抽取记录的数据。任何编码字段的差异频率为53%,主要诊断的差异频率为22%。由于差异,13.6%的病例被重新分配了新的澳大利亚国家诊断相关组(ANDRG)编码。随着ANDRG罕见程度增加,差异率从50%升至56%。ANDRG分配变化的预测因素包括主要诊断中的差异、ANDRG频率超过0.6%、诊断超过三项、医疗ANDRG、住院时间超过五天以及农村医院。任何差异率从诊断一项的患者中的36%增加到诊断12项的患者中的94%。差异率与其他研究一致。编码差异可能是由医院记录编码普遍存在的困难导致,而非任何独特的本地问题。差异的预测因素表明更复杂的病例更容易出现编码差异。在数据库可靠性较低的地区,使用补充数据源,如关联研究,将提高可靠性。