Williams B C, Phillips E K, Torner J C, Irvine A A
Division of General Medicine, University of Virginia School of Medicine, Charlottesville.
Med Care. 1990 May;28(5):379-91. doi: 10.1097/00005650-199005000-00001.
This study examined the feasibility of using routinely collected information on patients enrolled in home health care to predict their subsequent use of services. Data were gathered from 1,984 episodes of care randomly sampled from home health care agencies of the Virginia Health Department. Age, sex, Medicare and Medicaid enrollment, referral source, medical diagnosis, and prognosis were used to predict the total number of visits, the duration of enrollment, and the intensity of service. Since the data were originally gathered to study the effects of the implementation of diagnosis-related groups (DRGs) on home health services, half of the patients were enrolled before and half after the implementation of DRGs. Using multiple linear regression analysis, significant amounts of variance in each measure of home health care utilization were explained by the predictor variables (R2 = 0.04 to 0.10). For example, after controlling for other predictor variables, age 75 years or older predicted longer durations of enrollment and lower intensities of service as compared with other age groups (P less than 0.05), and four of 14 diagnosis categories predicted at least one measure of utilization (P less than 0.05). Medicaid enrollment predicted longer durations of enrollment and lower intensities of service in home health care (P less than 0.05) in the post-DRG but not the pre-DRG period. These results demonstrate the value of routinely collected information in predicting the use of home health services. To develop more accurate estimates of needs for home health services for particular groups of patients, additional information on chronic functional impairments, informal caregiving, and the chronicity of needs may be useful.
本研究探讨了利用常规收集的家庭医疗保健患者信息来预测其后续服务使用情况的可行性。数据来自从弗吉尼亚州卫生部家庭医疗保健机构随机抽取的1984例护理事件。年龄、性别、医疗保险和医疗补助参保情况、转诊来源、医学诊断和预后被用于预测就诊总次数、参保时长和服务强度。由于这些数据最初是为研究诊断相关分组（DRG）的实施对家庭医疗服务的影响而收集的，一半患者在DRG实施之前参保，另一半在DRG实施之后参保。使用多元线性回归分析，预测变量解释了家庭医疗保健利用各指标中显著的方差量（R2 = 0.04至0.10）。例如，在控制其他预测变量后，与其他年龄组相比，75岁及以上的年龄预测参保时长更长且服务强度更低（P小于0.05），并且14个诊断类别中的4个预测了至少一项利用指标（P小于0.05）。医疗补助参保预测了DRG实施后但不是DRG实施前家庭医疗保健中更长的参保时长和更低的服务强度（P小于0.05）。这些结果证明了常规收集的信息在预测家庭医疗服务使用方面的价值。为了更准确地估计特定患者群体对家庭医疗服务的需求，关于慢性功能障碍、非正式护理以及需求的慢性程度的额外信息可能会有所帮助。
