ADVANCING RISK ADJUSTMENT FOR SCHIZOPHRENIA

推进精神分裂症的风险调整

• 批准号: 6200740
• 负责人: BRADLEY C MARTIN
• 金额: $ 7.24万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-07-01 至 2002-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6200740
• 关键词: Medicare /Medicaid; clinical research; disease /disorder proneness /risk; health care cost /financing; health care model; health care service utilization; health services research tag; human data; mental disorder diagnosis; model design /development; schizophrenia

The goal of this research application is to develop a new risk adjustment measure for indigent persons suffering from severe mental illness, schizophrenia. More specifically, the researchers intend to develop and validate a schizophrenia specific risk adjustment index based on combined information from prescription drugs, diagnoses codes, and demographic/eligibility information commonly found in administrative data bases. Potentially, a diseases specific risk adjustment index using diagnoses codes and drug markers found in administrative claims data will outperform claims derived indices based on demographics combined with diagnosis based information alone. The theoretical basis of the proposed model is derived from previous risk adjustment techniques based on comorbidities derived from ICD-9-CM codes developed by Elixhauser, Deyo, and Charlson and drug exposure data that can compliment comorbity information and delinieate disease and comorbidity severity initially organized by VonKorf. Other candidate variables specific to schizophrenia are also proposed. A retrospective longitudinal review of administrative Medicaid claims data linked with Georgia mental health institutional inpatient data for approximatley 15,000 persons suffering from schizophrenia between 1995 and 1998 will be used to build a prospective diagnosis based and a combined risk adjustment model including the diagnosis, demographic, and drug based information. The risk adjustment models will adjust for two outcomes of interest, total one year resource utilization and resource utilization specific to mental health and substance abuse. The risk adjustment models will be prospective in nature, where information obtained in one year will be used to predict expenditures the year after. The models will be developed and validated using a split halves validation procedure, where candidate variables will be screened and internally validated using bootstrap methods on a random half of the sample and measures of discrimination and validation will be calculated using the validation sample. Expert clinical judgement will used to supplement statistical candidate variable screening. The results of this research will provide payers of mental health a means to adjust capitated payment rates and enable researchers to stratify varying levels of risk in quasi-experimental retrospective comparitive evaluations. Ultimately this research could be extended to develop a risk adjustment model for all mental disorders. This application is responsive to Healthy People 2000's priority area for economic evaluation in Mental Disorders Prevention.

这项研究申请的目标是为患有严重精神疾病、精神分裂症的贫困者制定一种新的风险调整措施。 更具体地说，研究人员打算根据处方药、诊断代码和行政数据库中常见的人口/资格信息的综合信息，开发和验证精神分裂症特定风险调整指数。潜在地，使用在行政索赔数据中发现的诊断代码和药物标记的疾病特定风险调整指数将优于仅基于人口统计数据与基于诊断的信息相结合的索赔衍生指数。所提出模型的理论基础源自先前的风险调整技术，该技术基于 Elixhauser、Deyo 和 Charlson 开发的 ICD-9-CM 代码衍生的合并症以及药物暴露数据，这些数据可以补充合并症信息并描述 VonKorf 最初组织的疾病和合并症严重程度。 还提出了精神分裂症特有的其他候选变量。对 1995 年至 1998 年间大约 15,000 名精神分裂症患者的医疗补助行政索赔数据与佐治亚州精神卫生机构住院患者数据进行回顾性纵向审查，将用于建立基于前瞻性诊断的组合风险调整模型，包括诊断、人口统计和基于药物的信息。风险调整模型将针对两个感兴趣的结果进行调整：一年的总资源利用率和特定于心理健康和药物滥用的资源利用率。风险调整模型本质上是前瞻性的，一年内获得的信息将用于预测下一年的支出。 这些模型将使用分半验证程序进行开发和验证，其中将使用引导方法对随机一半样本进行筛选和内部验证候选变量，并使用验证样本计算区分和验证的度量。 专家临床判断将用于补充统计候选变量筛选。这项研究的结果将为心理健康支付者提供一种调整按人头付费率的方法，并使研究人员能够在准实验性回顾性比较评估中对不同水平的风险进行分层。 最终，这项研究可以扩展到开发所有精神障碍的风险调整模型。该应用程序响应了 Healthy People 2000 精神障碍预防经济评估的优先领域。