Robust Suicide/Reinjury Risk Models to Assess Healthcare Systems

描述（由申请人提供）：最近的研究表明，自杀状态最有效的治疗发生在医疗保健系统内的多层次预防倡议的背景下。这些发现强调了建立能够解决自杀和再伤害风险的服务的重要性。虽然提供关键服务与降低自杀率有关，但重要的是要了解服务如何有助于防止自残者随后再次受伤。例如，2012年全国预防自杀行动联盟研究工作组利益相关者调查将自杀和自杀再伤害研究列为其研究的三大优先事项之一。目前，高达25%的自杀完成者和高达70%的非致命性再伤患者在再伤后12个月内因已知的非致命性自残行为在医疗保健环境中接受治疗。尽管存在多状态、基于人群、患者级和系统级的数据，但这些数据库中的信息并未得到有效提取。我们希望证明，先进的统计建模将为这些信息的提取提供机制，使政策制定者能够区分更有效的医疗保健提供系统

DESCRIPTION (provided by applicant): Recent research suggests that the most effective treatment of suicidal states occurs in the context of multi- level prevention initiatives within healthcare delivery systems. Such findings underscore the importance to create services that can address suicide and reinjury risks. While offering key services have been associated with reduced suicide rates, it is important to understand how services contribute to prevent self-harming persons from subsequent reinjury. For instance, the 2012 National Action Alliance for Suicide Prevention Research Task Force Stakeholder Survey ranked studies of suicide and suicide reinjury among its three highest priorities for research. Presently, up to 25% of all suicide completers and up to 70% of all nonfatal reinjuring patients are treated in a healthcare environment for a known nonfatal act of self-harm within 12 months of subsequent reinjury. Despite the availability of multi-state, population-based, patient-level, and system-level data, th information in such databases is not being effectively extracted. We wish to demonstrate that advanced statistical modeling will provide mechanisms for the extraction of such information that will enable policy makers to differentiate healthcare delivery systems that are more effective in preventing intentional reinjury from those that experience higher reinjury rates. This Phase I study investigates the feasibility of applying new statistical methods to analyze models of care for self-harming individuals using patient-level medical records obtained from AHRQ's extensive Healthcare Cost and Utilization Project [HCUP]. Data characterizing consecutive presentations to healthcare systems for treatment of self-harm from the state health services divisions or state hospital associations in five states will be used first to develop healthcare system risk models and then to test associations between post-injury medical treatment and the likelihood of fatal or nonfatal intentional reinjury within 12 months of an index, nonfatal intentional self-injury. Model will be developed using the Best Approximating Model (BAM) approach that selects and validates robust model searches while simultaneously handling common modeling problems such as the presence of possible model misspecification, missing values, over fitting, multicollinearity, rare event outcomes bias, and inflated error from multiple comparisons. Simulation studies will be performed to characterize the advantages of the BAM strategy for developing a robust suicide/reinjury risk model over widely-used multivariate statistical methods such as stepwise regression. Feasibility study results will provide the preliminary research for more advanced Phase II healthcare risk model development, evaluation, and dissemination that, in turn, establishes the essential foundation for Phase III product commercialization.