Weiner J P, Dobson A, Maxwell S L, Coleman K, Starfield B, Anderson G F
Johns Hopkins School of Public Health, Baltimore, MD 21205, USA.
Health Care Financ Rev. 1996 Spring;17(3):77-99.
Researchers at The Johns Hopkins University (JHU) developed two new diagnosis-oriented methodologies for setting risk adjusted capitation rates for managed care plans contracting with Medicare. These adjusters predict the future medical expenditures of aged Medicare enrollees based on demographic factors and diagnostic information. The models use the Ambulatory Care Group (ACG) algorithm to categorize ambulatory diagnoses. Two alternative approaches for categorizing inpatient diagnoses were used. Lewin-VHI, Inc. evaluated the models using data from 624,000 randomly selected aged Medicare beneficiaries. The models predict expenditures far better than the Adjusted Average per Capita Cost (AAPCC) payment method. It is possible that risk adjusted capitation payments could encourage health plans to compete on the basis of efficiency and quality and not risk selection.
约翰霍普金斯大学(JHU)的研究人员开发了两种新的面向诊断的方法,用于为与医疗保险签约的管理式医疗计划设定风险调整后的人头费率。这些调整器基于人口统计学因素和诊断信息预测老年医疗保险参保者未来的医疗支出。这些模型使用门诊护理组(ACG)算法对门诊诊断进行分类。采用了两种对住院诊断进行分类的替代方法。莱文-维希公司(Lewin-VHI, Inc.)使用从624,000名随机选择的老年医疗保险受益人那里获得的数据对这些模型进行了评估。这些模型在预测支出方面比调整后的人均成本(AAPCC)支付方法要好得多。风险调整后的人头支付有可能鼓励健康计划在效率和质量而非风险选择的基础上展开竞争。