Combination of chronic conditions determining clinical relevance and resource use

慢性病的组合决定临床相关性和资源利用

• 批准号: 8727877
• 负责人: SIRAN M. KOROUKIAN
• 金额: $ 17.92万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8727877
• 关键词: Combination; chronic; conditions; determining; clinical

DESCRIPTION (provided by applicant): Chronic conditions often co-occur, and one in five individuals with chronic illness also presents with activity limitations. In addition, because of shared pathophysiology, drug-drug interactions or drug-disease interactions, chronically ill older individuals may also present with geriatric syndromes, such as falls, cognitive impairment, or urinary incontinence. Our group has demonstrated that it is the combination of chronic conditions (CC) together with functional limitations (FL) and/or geriatric syndromes (GS), rather than CCs alone, that are associated with unfavorable health outcomes (fair/poor health status, two-year health decline, and mortality). However, little is known about the specific combinations of conditions - within and across the broad rubrics of CC, FL, and GS - that have the greatest implications for clinical and resource management. Relying on statistical learning techniques, and using the 1992-2010 linked Health and Retirement Study (HRS) and Medicare data, we aim to identify and rank specific combinations of CC, FL, and GS according to a) frequency; b) health outcomes; c) health services utilization; and d) institutional and non-institutional cost of care. Our metrics for health services utilization include acute (admission to the emergency department or to the hospital and the number of inpatient days), post-acute (skilled nursing facility, home health care, or hospice), and long-term care. Furthermore, we will examine variations in multiple chronic conditions (MCC) combinations and outcomes across subgroups of older adults by age, sex, race/ethnicity, and socioeconomic status, as well as between fee-for-service Medicare beneficiaries and managed care enrollees. This study is innovative, in that, rather than focusing on CCs alone, it accounts for the impact of specific CC(s) in conjunction with presence and severity of FL and GS, on health outcomes, health services use and costs in older adults. Our use of the HRS-Medicare data will offer a unique perspective by combining the rich primary data on such pertinent measures cognitive status, by severity, from the HRS with utilization data from Medicare claims files. In addition, we rely on state-of-the-art approach of statistical learning to understand "what the data says" with regard to identifying specific combinations of clinical conditions in relation to health care use and outcomes. The findings will have important implications in both research and clinical practice. Methodologically, our study will highlight the importance of a more nuanced approach to defining MCC when examining health outcomes and resource use. From a clinical perspective, the findings will show the importance of a more comprehensive and personalized approach when characterizing patients with MCC. In addition, as we identify subgroups of patients with MCC with high risk for poor outcomes and high resource use, it will be possible to design targeted interventions to better meet these patients' health care needs and to curtail health care utilization.

描述（由申请人提供）：慢性疾病通常同时发生，五分之一的慢性疾病患者也存在活动限制。此外，由于共同的病理生理学、药物-药物相互作用或药物-疾病相互作用，慢性病老年人也可能出现老年综合征，如福尔斯、认知障碍或尿失禁。我们的研究小组已经证明，慢性疾病（CC）与功能限制（FL）和/或老年综合征（GS）的结合，而不是单独的CC，与不利的健康结果（一般/较差的健康状况，两年的健康下降和死亡率）相关。然而，很少有人知道的具体组合条件-内和跨CC，FL和GS的广泛的标题-有临床和资源管理的最大的影响。依靠统计学习技术，并使用1992-2010年相关的健康和退休研究（HRS）和医疗保险数据，我们的目标是根据a）频率; B）健康结果; c）卫生服务利用率; d）机构和非机构成本来识别和排名CC，FL和GS的特定组合。 在乎我们的卫生服务利用指标包括急性（急诊或住院和住院天数），急性后（专业护理设施，家庭医疗保健或临终关怀）和长期护理。此外，我们还将研究多种慢性病（MCC）组合和结果的变化，这些变化是按年龄，性别，种族/民族和社会经济地位划分的老年人亚组，以及按服务收费的医疗保险受益人和管理式护理登记者之间的变化。这项研究是创新的，因为它不是仅仅关注CC，而是考虑了特定CC（S）与FL和GS的存在和严重程度相结合对老年人健康结局，卫生服务使用和成本的影响。我们对HRS-Medicare数据的使用将提供一个独特的视角，通过将HRS中有关认知状态（按严重程度）的丰富原始数据与Medicare索赔文件中的利用数据相结合。此外，我们依靠最先进的统计学习方法来了解“数据说什么”，以确定与医疗保健使用和结果相关的临床条件的特定组合。这些发现将在研究和临床实践中具有重要意义。在方法上，我们的研究将强调在检查健康结果和资源使用时，采用更细致入微的方法来定义MCC的重要性。从临床角度来看，这些发现将显示在描述MCC患者时更全面和个性化方法的重要性。此外，当我们确定MCC患者的亚组具有不良结局和高资源使用的高风险时，将有可能设计有针对性的干预措施，以更好地满足这些患者的医疗保健需求并减少医疗保健利用。