Effectiveness of advanced practice pharmacy services among American Indian and Alaska Native adults with diabetes

美国印第安人和阿拉斯加原住民成年人中先进实践药房服务的有效性 糖尿病 印第安人健康服务（IHS）为大约220万美国印第安人和阿拉斯加州提供服务。 土著人（AI/AN）。由于人均支出有限，IHS医疗保健资源紧张， 治疗患有糖尿病的AI/AN的不成比例的高成本以及供应商短缺。全因死亡率 AI/AN比非西班牙裔白人高46%，部分原因是与AI/AN相关的死亡率较高。 糖尿病在IHS内部，为糖尿病成人提供高级实践药房（APP）服务， 增加在2008财年，大约1%的糖尿病AI/AN使用APP。 之后，9.6%（n = 4，620）在2013财年至少接受了1次APP访视。到目前为止，IHS还没有机构能力， 充分描述APP服务的提供，也不研究其有效性或成本。 考虑到既需要改善糖尿病患者的结局，又需要有效利用有限的IHS 资源，本研究的目标是描述和评估新兴模式的APP在IHS的有效性 用于治疗糖尿病。自2010年以来，IHS和部落与美国印第安人中心合作， 和阿拉斯加土著健康在科罗拉多大学创建一个纵向数据基础设施与健康 超过640，000名AI/AN的状态、服务利用率和治疗成本数据，这些AI/AN占全球 使用IHS服务的AI/AN。通过改善卫生保健提供数据创建的基础设施 项目，是一个综合现有的电子数据从多个IHS平台，目前包括数据7 2007 - 2013财年，15个项目地点。我们建议通过更新 使用最新数据（2014 - 2017财年）的基础设施来评估AI/AN成年人的APP有效性 糖尿病使用统计技术可能的纵向数据。该研究有三个目标： 1.在研究中心内和使用研究中心的一段时间内，描述成人糖尿病患者的APP交付模式 特征和患者健康风险概况（例如，血糖水平[A1c]，血压[BP]， 胆固醇[CHL]，心血管疾病）。我们预计可能会出现多达3种模型（例如， 有针对性的、有限的和一般的）;以及 2.对于每种APP模型，评估患者APP使用与 成果。在每个模型中，我们预计APP将改善药物依从性和A1c，BP， CHL水平，并减少并发症的发生和可预防的住院时间;以及 3.估计APP交付成本，与其他卫生服务使用减少相关的治疗成本变化， 和成本效益。我们希望APP模式具有成本效益。 1

Effectiveness of advanced practice pharmacy services among American Indian and Alaska Native adults with diabetes The Indian Health Service (IHS) funds services for approximately 2.2 million American Indians and Alaska Natives (AI/ANs).IHS health care resources are strained due to limited per capita spending, the disproportionate high costs of treating AI/ANs with diabetes, and provider shortages. All-cause mortality of AI/ANs is 46% higher than that of non-Hispanic whites, attributable in part to higher mortality associated with diabetes. Within IHS, the provision of advanced practice pharmacy (APP) services for adults with diabetes has increased. During fiscal year (FY) 2008, approximately 1% of AI/ANs with diabetes used APP. Just 5 years later, 9.6% (n=4,620) had at least 1 APP visit in FY2013. To date, IHS has not had the institutional capacity to fully characterize the provision of APP services, nor study its effectiveness or costs. Given the need to both improve outcomes for patients with diabetes and effectively utilize limited IHS resources, this study's goal is to describe and assess the effectiveness of emerging models of APP within IHS for treatment of diabetes. Since 2010, IHS and Tribes have collaborated with the Centers for American Indian and Alaska Native Health at the University of Colorado to create a longitudinal data infrastructure with health status, service utilization, and treatment cost data for over 640,000 AI/ANs who represent nearly 30% of AI/ANs who use IHS services. The infrastructure, created through the Improving Health Care Delivery Data Project, is a synthesis of existing electronic data from multiple IHS platforms and currently includes data for 7 years (FY2007-2013) for 15 project sites. We propose to continue this collaboration by updating the infrastructure with recent data (FY2014-2017) to evaluate APP effectiveness among AI/AN adults with diabetes using statistical techniques made possible by the longitudinal data. The study has 3 aims: 1. Characterize APP delivery models for adults with diabetes within sites and over time using site characteristics and patient health risk profiles (e.g., glycemic level [A1c], blood pressure [BP], cholesterol [CHL], cardiovascular disease). We anticipate that up to 3 models may emerge (e.g., Targeted, Limited, and General); and 2. For each APP model, evaluate the nature and extent of the relationship between patient APP use and outcomes. Within each model, we expect that APP will improve medication adherence and A1c, BP, and CHL levels, and reduce onset of complications and preventable hospital stays; and 3. Estimate APP delivery costs, treatment cost changes associated with lower use of other health services, and cost-effectiveness. We expect the APP models to be cost-effective. 1