Stineman M G, Escarce J J, Goin J E, Hamilton B B, Granger C V, Williams S V
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia 19104-2676.
Med Care. 1994 Apr;32(4):366-79. doi: 10.1097/00005650-199404000-00005.
Dissatisfaction with Medicare's current system of paying for rehabilitation care has led to proposals for a rehabilitation prospective payment system, but first a classification system for rehabilitation patients must be created. Data for 36,980 patients admitted to and discharged from 125 rehabilitation facilities between January 1, 1990, and April 19, 1991, were provided by the Uniform Data System for Medical Rehabilitation. Classification rules were formed using clinical judgment and a recursive partitioning algorithm. The Functional Independence Measure version of the Function Related Groups (FIM-FRGs) uses four predictor variables: diagnosis leading to disability, admission scores for motor and cognitive functional status subscales as measured by the Functional Independence Measure, and patient age. The system contains 53 FRGs and explains 31.3% of the variance in the natural logarithm length of stay for patients in a validation sample. The FIM-FRG classification system is conceptually simple and stable when tested on a validation sample. The classification system contains a manageable number of groups, and may represent a solution to the problem of classifying medical rehabilitation patients for payment, facility planning, and research on the outcomes, quality, and cost of rehabilitation.
对医疗保险现行康复护理支付系统的不满引发了对康复预期支付系统的提议，但首先必须创建一个康复患者分类系统。1990年1月1日至1991年4月19日期间，125家康复机构收治并出院的36980名患者的数据由统一医学康复数据系统提供。分类规则是使用临床判断和递归划分算法形成的。功能相关组的功能独立性测量版本（FIM-FRGs）使用四个预测变量：导致残疾的诊断、通过功能独立性测量所测量的运动和认知功能状态子量表的入院分数，以及患者年龄。该系统包含53个FRGs，并解释了验证样本中患者自然对数住院时间方差的31.3%。FIM-FRG分类系统在概念上简单，在验证样本上进行测试时很稳定。该分类系统包含数量可控的组，可能代表了一种解决方案，用于对医疗康复患者进行分类，以用于支付、机构规划以及康复结果、质量和成本的研究。
