Evaluating the Effects of HACRP

评估 HACRP 的效果

• 批准号: 10412009
• 负责人: Andrew M Ryan
• 金额: $ 7.75万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10412009
• 关键词: Evaluating; Effects; HACRP

Project Summary Hospital acquired conditions (HACs) are common, costly, and deadly. Despite recent reductions, HACs still occur at a rate of 121 events per 1,000 discharges. Building on previous payment reforms to reduce HACs, the Centers for Medicare and Medicaid Services initiated the Hospital Acquired Condition Reduction Program (HACRP). However, the effect of expanding incentives for patient safety under the new HACRP is unknown. The objective of the current proposal is to understand the impact of the HACRP on patient and system outcomes and the specific strategies used by successful hospitals to improve under the program. Our proposal will address the following three aims: Aim 1: Evaluate the effects of the Hospital Acquired Condition Reduction Program on patient outcomes. We will evaluate the effects of the HACRP on both targeted measures (e.g. patient safety indicators) and downstream outcomes (e.g. 30-day mortality and readmission). We will examine how much administrative changes (e.g. increases in coded severity and changes to denominator criteria) explain the impact of the HACRP. We hypothesize that the HACRP will lead to decreases in targeted measures but will have an attenuated effect on downstream outcomes. We also hypothesize that hospitals with more revenue at risk under the program and hospitals that are engaged in more value-based reforms will experience greater improvements in targeted outcomes; Aim 2: Evaluate the effects of the Hospital Acquired Condition Reduction Program on spending. We will evaluate the effects of the HACRP on 30-day total episode spending as well as spending related to the index hospitalization, physician services, readmissions, hospital outpatient care, and post-acute care services. We hypothesize that the HACRP will lead to decreases in total episode spending as well as the downstream components of episode spending; Aim 3: Evaluate the factors responsible for improvement under the Hospital Acquired Condition Reduction Program. We will perform a case study analysis of hospitals in Michigan that participate in the Michigan Value Collaborative, a partnership between BlueCross BlueShield of Michigan and 75 acute care hospitals in Michigan working to improve quality and value. We hypothesize that hospitals that are engaged in systematic quality improvement efforts will experience greater improvements on both targeted performance measures and downstream patient outcomes. Our study is significant because our findings will be used to inform decision makers at the CMS about the impact of new reimbursement mechanisms on quality, safety, and spending. Our findings will also provide hospitals and clinician leaders with actionable insights about how to improve HACs. Our study is innovative because it uses unique data linkages, provider collaboratives, and multiple methods to evaluate upstream and downstream effects of a key policy reform.

项目概要 医院获得性疾病 (HAC) 很常见、成本高昂且致命。尽管最近有所减少，但 HAC 仍然 每 1,000 次放电中发生 121 次事件。在之前减少 HAC 的支付改革的基础上， 医疗保险和医疗补助服务中心启动了医院获得性病症减少计划 （HACRP）。然而，根据新的 HACRP 扩大患者安全激励措施的效果尚不清楚。 当前提案的目标是了解 HACRP 对患者和系统的影响 成果以及成功医院在该计划下用于改进的具体策略。我们的建议 将实现以下三个目标： 目标 1：评估医院获得性疾病的影响 关于患者结果的减少计划。我们将评估 HACRP 对目标的影响 措施（例如患者安全指标）和下游结果（例如 30 天死亡率和再入院）。 我们将检查有多少管理变更（例如，编码严重性的增加和对 分母标准）解释 HACRP 的影响。我们假设 HACRP 将导致减少 采取有针对性的措施，但对下游结果的影响会减弱。我们还假设 该计划下收入较高的医院以及从事更多基于价值的医院 改革的目标成果将取得更大改善；目标 2：评估效果 医院获得性病症减少计划的支出。我们将评估 HACRP 的效果 30 天的总发作支出以及与指数住院、医生服务相关的支出， 再入院、医院门诊护理和急性期后护理服务。我们假设 HACRP 将引领 总剧集支出以及剧集支出的下游部分减少；目标 3： 评估医院获得性病情减少下的改善因素 程序。我们将对参与密歇根价值计划的密歇根州医院进行案例研究分析 Collaborative，密歇根州 BlueCross BlueShield 与密歇根州 75 家急症护理医院之间的合作伙伴关系 密歇根州致力于提高质量和价值。我们假设从事系统性治疗的医院 质量改进工作将在有针对性的绩效衡量和 下游患者的结果。我们的研究意义重大，因为我们的研究结果将用于指导决策 CMS 的制造商了解新的报销机制对质量、安全和支出的影响。我们的 研究结果还将为医院和临床医生领导者提供有关如何改进 HAC 的可行见解。 我们的研究具有创新性，因为它使用独特的数据链接、提供商协作和多种方法来 评估关键政策改革的上游和下游影响。