Assessing Medical Need Among Children in Managed Care

这项研究考察了风险评估模型如何很好地识别管理保健计划中儿童的医疗需求，并将建立一个使用健康计划中所有可用自动数据的全信息儿科特定风险评估模型。儿科风险评估的独特挑战没有得到足够的重视。我们的假设是，目前的风险模型不够敏感，无法正确识别儿童作为一个群体和有特殊需求的儿童的医疗需求。此外，由于这些模式被用来调整管理性医疗支出，我们预计医疗计划将有财政激励措施，以避免让儿童和有儿童的家庭，特别是有特殊需要的儿童入学。使用一个由参与儿科风险评估研究的人数最多的人组成的数据集，190万人，包括515,729名儿童，这项研究的具体目标是：1)确定当前的风险评估模型是否足够敏感，足以确定受管医疗保健计划中儿童的预期医疗成本和利用率。我们将通过比较现有的以普通人群为重点的风险评估模型和少数儿科特定的风险评估模型，来研究风险评估模型对儿童和有儿童的家庭的医疗需求的预测能力。将特别关注高费用慢性疾病儿童的需求。2)评估是否存在阻碍保健计划招收儿童和有子女家庭的财务障碍。3)评估额外的健康状况信息如何提高风险评估工具的预测性能。这项研究是独一无二的，因为没有全面的研究检查风险评估方法的敏感性，以确定管理护理中儿童的医疗需求，而不考虑他们的保险来源。儿科风险评估研究也没有探索利用管理保健信息系统中所有可用信息的机会。

This study examines how well risk assessment models identify the medical needs of children in managed care plans and will build a full information pediatric specific risk assessment model that uses all of the automated data available from health plans. Inadequate attention has been paid to the unique challenges of pediatric risk assessment. Our hypothesis is that current risk models are not sensitive enough to correctly identify medical need among children as a group and among children with special needs. Moreover, because these models are used to adjust managed care payments, we expect health plans will have financial incentives to avoid enrolling children and families with children, particularly children with special needs. Using a dataset comprised of the largest number of people involved in a pediatric risk assessment study, 1.9 million people, including 515,729 children, the specific aims of this research are to: 1) Determine whether current risk assessment models are sensitive enough to identify expected healthcare cost and utilization for children in managed health care plans. We will study how well risk assessment models predict medical need among children and families with children by comparing existing risk assessment models focused on the general population to the few pediatric specific risk assessment models. Specific attention will be paid to the needs of children with high cost chronic medical conditions. 2) Evaluate if there exist financial disincentives for health plans to enroll children and families with children. 3) Assess how additional health status information improves the predictive performance of risk assessment instruments. This study is unique because no comprehensive research has examined the sensitivity of risk assessment methods to identify medical need among children in managed care regardless of their insurance source. Pediatric risk assessment research has also not explored opportunities to use all information available in managed care information systems.