Lorence Daniel P, Ibrahim Ibrahim Awad
College of Human Development, Department of Health Policy and Administration, School of Information Sciences and Technology, Pennsylvania State University, University Park, PA, USA.
J Health Care Finance. 2003 Summer;29(4):29-42.
The objective of this study was to measure the consistency of coded medical data through information managers' reports of the overall coding error level in patients' medical records. Using a cross-sectional design, we examined the reported percent of records containing coding errors significant enough to change a diagnostic related group (DRG). Results indicate about 87 percent, 9 percent, and 5 percent of respondents reported that significant coding errors existed in less than 5 percent, 6-10 percent, and greater than 10 percent of the medical records in their institutions, respectively. Significant variation was found in the accuracy and consistency of coding practice and associated data quality across key demographic and organizational variables. Significantly large error rates in coded data exist in some organizations. Given variations across key demographic characteristics, providers may tend to distrust all coded data, when aggregated. As the United States moves toward an evidence-based medicine environment, the use of current patient data classification methods may be of limited value without increased attention to coding practices.
本研究的目的是通过信息管理人员关于患者病历中总体编码错误水平的报告,来衡量编码医学数据的一致性。采用横断面设计,我们检查了报告中包含足以改变诊断相关组(DRG)的编码错误的记录百分比。结果表明,分别约有87%、9%和5%的受访者报告称,其所在机构中编码错误严重到足以改变DRG的病历比例分别低于5%、6 - 10%和高于10%。在关键人口统计学和组织变量方面,编码实践的准确性和一致性以及相关数据质量存在显著差异。一些组织中编码数据的错误率极高。鉴于关键人口特征存在差异,汇总后提供者可能会倾向于不信任所有编码数据。随着美国向循证医学环境转变,如果不更加关注编码实践,当前患者数据分类方法的使用可能价值有限。