Melfi C, Holleman E, Arthur D, Katz B
Indiana University Department of Medicine, School of Medicine, Indianapolis 46202-5200, USA.
J Clin Epidemiol. 1995 Jul;48(7):917-26. doi: 10.1016/0895-4356(94)00202-2.
Recently, there has been a great deal of discussion regarding the use of administrative databases to study outcomes of medical care. A major issue in this discussion is how to classify patients in terms of characteristics such as disease-severity, comorbidities, resource needs, stability, etc. Different indices have been developed in an attempt to provide a common classification scheme in terms of these characteristics. In this paper, we examine the utility of four indices in the prediction of length of stay and 30-day mortality for patients undergoing total knee replacement surgery between 1985 and 1989. The indices that we compare are the Deyo-adapted Charlson Index, the Relative Intensity Score derived from Patient Management Categories (PMCs), the Patient Severity Level derived from PMCs, and the number of diagnoses (up to five) listed in the Medicare claims data. The first three of these indices represent measures of comorbidity, resource use, and severity of illness, respectively. The number of diagnoses is likely to capture aspects of each of these characteristics. We find that all of the indices improve (in terms of model fit) over the baseline (no index) models of length of stay and mortality, and the Relative Intensity Score and Patient and Severity Level result in the greatest improvement in measures of model fit. We found, however, that these two indices have a non-monotonic relationship with length of stay and mortality. The Deyo-adapted Charlson Index performed least well of the four indices in terms of explanatory ability. The number of diagnoses performed well, and does not suffer from problems associated with miscoding on claims data.
最近，关于使用行政数据库来研究医疗护理结果的讨论很多。在这个讨论中的一个主要问题是如何根据疾病严重程度、合并症、资源需求、稳定性等特征对患者进行分类。已经开发了不同的指数，试图根据这些特征提供一个通用的分类方案。在本文中，我们研究了四个指数在预测1985年至1989年接受全膝关节置换手术患者的住院时间和30天死亡率方面的效用。我们比较的指数是改编后的迪尤-查尔森指数、从患者管理类别（PMC）得出的相对强度评分、从PMC得出的患者严重程度水平以及医疗保险理赔数据中列出的诊断数量（最多五个）。其中前三个指数分别代表合并症、资源使用和疾病严重程度的衡量指标。诊断数量可能涵盖了这些特征的各个方面。我们发现，所有指数（就模型拟合而言）都比住院时间和死亡率的基线（无指数）模型有所改进，相对强度评分以及患者严重程度水平在模型拟合度量方面带来了最大的改进。然而，我们发现这两个指数与住院时间和死亡率存在非单调关系。在解释能力方面，改编后的迪尤-查尔森指数在这四个指数中表现最差。诊断数量表现良好，并且不存在与理赔数据编码错误相关的问题。
