Utilization and Health Outcomes for Veterans with Expanded Health Care Accessâ¯

背景：改善获得高质量护理的机会是VHA的首要任务。然而，访问是很难的 措施，特别是在不断变化的美国医疗保健格局中。VHA目前专注于感知 满意度通过调查问题衡量，或通过管理数据衡量等待时间。等待时间 指标在《选择法案》和《使命法案》中都受到了相当大的关注，但专家们认识到，等待 时代是不完美的；它们不仅难以解释，而且很少从社区获得 供应商，阻碍了任何VHA与非VA的比较。VHA领导负责实施选择和 使命行动需要更好的基于证据的访问措施，这样他们才能评估他们计划的影响。 我们无法衡量可获得性，这威胁到VHA作为医疗保健提供者的未来。没有新的指标 跟踪接入方面的差距或改进，VHA可能会投资于错误的计划，从而引发批评 认为私有化将确定项目的重要性/影响：我们的目标是制定新的措施 访问权限。这些新措施将提供有关VHA服务差距的因果信息，同时还显示 扩大准入对退伍军人健康的潜在影响。我们的研究利用自然 以任意管理规则的形式进行试验，使退伍军人能够在VHA之外获得医疗服务 医疗保险和退伍军人社区护理(VACC)的形式。接近规则门槛的退伍军人是相似的，但 一些人根据规则获得访问权限，而另一些人则不能。我们可以利用这些信息来理解 这一增加的准入如何改变卫生保健的利用和健康结果。我们的研究结果将有助于 国家和地方的VHA领导人正在努力解决如何在有限的预算下最好地改善服务的问题。 创新：进行大规模随机临床试验以发现Access对 利用情况和健康结果。相关研究将遗漏重要的混杂因素，而且众所周知 相关性不等于因果关系，这是VHA领导人最需要的。取而代之的是，我们将小说 利用自然实验并找出增长的因果效应的计量经济学技术 进入。然后，此方法的结果可用作VHA和非VA访问的衡量标准 关心。这与HSR&D在获得护理、与使命法案相关的研究方面的优先事项直接一致， 以及在各种条件或护理环境中推进卫生服务研究方法。具体目标：目标1： 找出医疗保险资格对退伍军人利用率和健康的因果影响，并确定程序和 受影响最大的诊断组。目标2：找出VACC对退伍军人利用率的因果影响 健康，并发现受影响最大的程序和诊断。目标3：确定将 向VHA领导人提供关键信息。方法：在目标1和目标2中，我们将应用计量经济学 称为回归不连续设计的技术。我们将收集一份近乎完整的VHA和非退伍军人管理局的普查 所有最近的资深VHA用户的记录，允许精确的基于索赔的利用率、运行状况和 死亡率。在目标1中，这种方法利用了65岁时发生的医疗保险资格的急剧变化 了解医疗保险对利用率和健康的影响。Aim 2使用了同样的方法，但我们不是65岁，而是 使用驾驶距离规则找出退伍军人管理局社区护理对利用率和健康的影响。为了实现这些目标 我们将检查总体效果和程序，以及诊断的特定效果。在目标3中，我们采取了一个 与运营合作伙伴合作并应用机器学习技术的组合方法 异质处理效果，以确定和检查可用于政策的指标和措施 队形。下一步和实施：通过AIM 3与运营合作伙伴合作，我们将 确定实施从我们的结果得出的措施和指标的机会和障碍。这 信息将是制定与VHA演变为退伍军人护理提供者和支付者相关政策的关键 同时确保退伍军人在退伍军人管理局和非退伍军人管理局得到高质量的护理。

Background: Improving access to high-quality care is a top priority for VHA. However, access is difficult to measure, especially in the ever-changing U.S. health care landscape. VHA currently focuses on perceived satisfaction measured from survey questions, or wait times measured with administrative data. The wait time metric has received considerable focus in both the Choice and MISSION Acts, yet experts recognize that wait times are imperfect; they are not only challenging to interpret, but they are rarely available from community providers, hindering any VHA to non-VA comparisons. VHA leaders tasked with implementing the Choice and MISSION Acts desire better evidence-based access measures so they can evaluate their program’s impact. Our inability to measure access threatens the future of VHA as a health care provider. Without new metrics that track gaps or improvements in access, VHA is likely to invest in the wrong initiatives, fueling critics who will argue that privatization will fix the programs Significance/Impact: Our objective is to develop new measures of access. These new measures will provide causal information on gaps in VHA services, while also showing the potential impact that expanded access would have on Veterans’ health. Our study leverages natural experiments in the form of arbitrary administrative rules that enable Veterans to access care outside VHA in the forms of Medicare and VA Community Care (VACC). Veterans close to the rule thresholds are similar, yet some gain access based on the rule, while the others do not. We can leverage this information to understand how this added access changes health care utilization and health outcomes. Our results will be useful to national and local VHA leaders as they grapple with how to best improve access with a limited budget. Innovation: It is not feasible to perform a large-scale randomized clinical trial to find the effect of access on utilization and health outcomes. Correlational studies will miss important confounders, and as everyone knows correlation does not equal causation, which is what VHA leaders need most. Instead, we apply novel econometric techniques to take advantage of natural experiments and find the causal effects of increasing access. The results from this approach can then be used as a measure of access for both VHA and non-VA care. This is directly aligned with HSR&D's priorities on access to care, research related to the MISSION Act, and advancing health services research methods across conditions or care settings. Specific Aims: Aim 1: Find the causal impact of Medicare eligibility on Veteran utilization and health, and identify procedures and diagnosis groups that are most affected. Aim 2: Find the causal impact of VACC on Veteran utilization and health, and find the procedures and diagnoses most affected. Aim 3: Identify subgroup analyses that would give crucial information to VHA leaders. Methodology: In Aims 1 and 2, we will apply an econometric technique called regression discontinuity design. We will gather a near complete census of VHA and non-VA records for all recent Veteran VHA users, allowing for precise claims-based measures of utilization, health, and mortality. In Aim 1, this approach leverages the sharp change in Medicare eligibility that occurs at age 65 to find the effect of Medicare on utilization and health. Aim 2 uses the same approach, but instead of age 65, we use the driving distance rules to find the effect of VA Community Care on utilization and health. For these aims we will examine both overall effects and procedure and diagnosis specific effects. In Aim 3, we take a combined approach of working with operational partners and applying machine learning techniques for heterogenous treatment effects to identify and examine metrics and measures that can be used for policy formation. Next Steps and Implementation: By working with operational partners through Aim 3, we will identify opportunities and barriers to implementing measures and metrics derived from our results. This information will be key to setting policy related to VHA’s evolution into a provider and payer of Veteran care while ensuring that Veterans receive high-quality care in both VHA and non-VA settings.