Risk-Adjusting Hospital Outcomes for Veteran's Socioeconomic Status

根据退伍军人的社会经济地位调整医院结果的风险

• 批准号: 9188841
• 负责人: AMAL N. TRIVEDI
• 金额: --
• 依托单位: PROVIDENCE VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9188841
• 关键词: Accountability; Admission activity; Affordable Care Act; Age; Benchmarking; Calibration; Caring; Characteristics; Clinical; Collaborations; Consensus; Data; Diagnosis; Discrimination; Electronic Health Record; Enrollment; Ethnic Origin; Goals; Health Information System; Health Policy; Healthcare Systems; Heart Rate; Heart failure; Homelessness; Hospital Mortality; Hospitals; Incentives; Income; Learning; Measurement; Measures; Medicaid; Medical center; Medicare; Methods; Modeling; Mortality Determinants; Neighborhoods; Nursing Homes; Observational Study; Outcome; Outcome Measure; Patient risk; Patients; Performance; Pneumonia; Predictive Factor; Private Sector; Provider; Race; Records; Reporting; Research; Research Priority; Resource Allocation; Risk; Risk Adjustment; Role; Science; Site; Socioeconomic Status; Source; Statistical Models; Testing; United States; Variant; Veterans; base; care outcomes; clinical risk; deprivation; evidence base; expectation; high risk population; improved; innovation; inpatient service; mortality; novel; novel strategies; operation; patient population; payment; performance tests; policy implication; predictive modeling; programs; residence; sex; tool

Anticipated Impacts of Veterans' Care: The project will develop and test novel approaches to risk- adjustment that include Veterans' sociodemographic factors into assessments of VAMC-level hospital mortality. This contribution is significant because rigorous outcomes measurement is central to VA's strategy to improve care for Veterans, assess quality across sites, and benchmark performance to the private-sector. If risk-adjustment fails to account for sociodemographic determinants of mortality that are known to vary across VA providers, then excluding these factors may penalize VA sites that disproportionately serve vulnerable patients and generate incorrect inferences about the quality of VA care. Since VA uses performance results for accountability purposes and to make determinations about allocation of resources, it is essential that VA uses the most robust risk-adjustment methods available. Given emerging momentum to consider sociodemographic characteristics for risk-adjustment purposes, there is a pressing need to develop an empirical evidence base about the implications of such adjustments. Project Background: Nearly all hospitals in the United States, including all VA Medical Centers (VAMCs), report mortality rates for hospitalized patients, and performance on these outcomes measures often carry high stakes. Hospital mortality constitutes two domains of the Strategic Analytic Information and Learning (SAIL) model that VA employs to evaluate the quality and efficiency of care provided across all VAMCs. Valid hospital outcome measures must adequately account for differences in clinical risk. Without adequate risk-adjustment, performance reports may erroneously penalize facilities that serve high-risk populations, or, even worse, incentivize facilities to admit low-risk patients. Much of the prior concern with risk-adjustment has involved the source of the data, the selection of appropriate covariates, or the optimal approach to statistical modeling. Substantially fewer studies have examined the role of socioeconomic status and other sociodemographic factors in risk-adjustment, though these factors predict worse post-discharge outcomes and vary markedly across facilities. Project Objective: The overarching goal of this project is to develop and test novel risk-adjustment approaches that incorporate Veterans' sociodemographic characteristics into assessments of hospital mortality. Our aims are: (1) describe VAMC-level variations in the sociodemographic characteristics of Veterans hospitalized with heart failure and pneumonia; (2) assess the performance of risk-adjustment models that do and do not include sociodemographic characteristics; and (3) evaluate the impact of incorporating sociodemographic data on the relative performance of VA Medical Centers. Project Methods: We propose a retrospective, observational study that will develop and compare alternative risk-adjustment models predicting mortality within thirty days of admission for heart failure and pneumonia. We will then test the performance of models that do and do not incorporate sociodemographic characteristics and assess the impact of including sociodemographic characteristics on profiling VAMC-level hospital mortality rates for heart failure and pneumonia. Aim 1 will assess how the sociodemographic characteristics of Veterans admitted with heart failure and pneumonia vary across VAMCs. Aim 2 will compare the existing claims-based VA/CMS risk-adjusted mortality models for heart failure and pneumonia with models that incorporate claims and novel sociodemographic data; and determine the contribution of sociodemographic characteristics to mortality models that include both claims-based diagnoses and clinical covariates derived from the VA's electronic health record. Aim 3 extends these analyses by determining whether relative quality rankings of VA medical centers change when sociodemographic factors are included in mortality risk-adjustment models. .

退伍军人护理的预期影响：该项目将开发和测试新的风险管理方法， 将退伍军人的社会人口学因素纳入VAMC级医院评估的调整 mortality.这一贡献是重要的，因为严格的结果测量是VA战略的核心， 改善对退伍军人的护理，评估各个地点的质量，并将绩效基准与私营部门相比较。如果 风险调整未能解释死亡率的社会人口学决定因素，这些决定因素在不同的国家和地区之间存在差异。 VA提供商，然后排除这些因素可能会惩罚VA网站，不成比例地服务于脆弱的 患者，并产生关于VA护理质量的错误推断。由于VA将性能结果用于 问责的目的，并作出有关资源分配的决定，这是至关重要的，VA使用 最可靠的风险调整方法鉴于考虑社会人口因素的新势头， 为了风险调整的目的，迫切需要建立一个经验证据基础 这种调整的影响。 项目背景：美国几乎所有的医院，包括所有的VA医疗中心（VAMC）， 报告住院患者的死亡率，这些结果指标的表现往往很高， 赌注。医院死亡率构成战略分析信息和学习（SAIL）的两个领域 VA用于评估所有VAMC提供的护理质量和效率的模型。有效医院 结果测量必须充分考虑临床风险的差异。如果没有适当的风险调整， 业绩报告可能会错误地惩罚为高风险人群服务的设施，甚至更糟的是， 鼓励机构接纳低风险患者。之前对风险调整的大部分关注都涉及到 数据的来源、适当协变量的选择或统计建模的最佳方法。 很少有研究探讨社会经济地位和其他社会人口因素的作用。 风险调整的因素，尽管这些因素预测更差的出院后结果， 在设施。 项目目标：本项目的总体目标是开发和测试新的风险调整 将退伍军人的社会人口学特征纳入医院评估的方法 mortality.我们的目标是：（1）描述VAMC水平的变化，在社会人口特征， 因心力衰竭和肺炎住院的退伍军人;（2）评估风险调整模型的性能 包括和不包括社会人口特征;（3）评估纳入的影响 关于VA医疗中心相对表现的社会人口统计数据。 项目方法：我们提出了一个回顾性的，观察性的研究，将开发和比较替代 风险调整模型预测心力衰竭和肺炎入院后30天内的死亡率。我们 然后将测试模型的性能，这些模型包含和不包含社会人口特征， 评估包括社会人口学特征对VAMC级医院死亡率的影响 心力衰竭和肺炎的发病率目标1将评估退伍军人的社会人口特征 因心力衰竭和肺炎入院的患者在VAMC中各不相同。目标2将比较现有的基于索赔的 心力衰竭和肺炎的VA/CMS风险调整死亡率模型，包括索赔模型 和新的社会人口数据;并确定社会人口特征的贡献， 死亡率模型，包括基于索赔的诊断和来自VA的临床协变量 电子健康记录。目的3通过确定VA的相对质量等级来扩展这些分析， 当死亡风险调整模型中包括社会人口因素时，医疗中心发生变化。 .