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

R18DK114757

2017-07-01

2021-06-30