| Sumario: | BACKGROUND: American Indians and Alaska Natives (AI/ANs) experience disparities in diabetes-related morbidity and mortality. The Indian Health Service (IHS) and Tribal health programs provide education, case management, and advanced practice pharmacy (ECP) services for patients with diabetes to improve health outcomes. OBJECTIVE: The purpose of this study was to evaluate patient outcomes associated with the use of ECP services by AI/AN adults with diabetes by comparing the outcomes of ECP users with those of nonusers. METHODS: We analyzed fiscal year (FY) 2011-2013 data for AI/AN adults with diabetes from the IHS Improving Health Care Delivery Data Project, which includes data on nearly 30% of the IHS service population. The diabetes and cardiovascular disease (CVD) measures were used to create 3 study cohorts: all adults with diabetes; and 2 subgroups, adults with diabetes without CVD and adults with both diabetes and CVD. The analyses were conducted for each study cohort. Using an observational study design and propensity score models that employed inverse probability weighting, to control for the nonrandom assignment of patients to the treatment group, we evaluated FY2013 outcomes for patients who used ECP services during FY2012, controlling for baseline characteristics in FY2011. The outcomes for ECP users were compared with those for patients who obtained usual care (ie, patients who did not use ECP services), using multivariable regressions. Baseline characteristics included age, sex, health coverage, and health status measures. Other characteristics included in the propensity model were drive times to ECP services and county-level measures of educational attainment and household income from the American Community Survey. Health outcomes included high hemoglobin A1c (HbA1c), systolic blood pressure (SBP), and low-density lipoprotein cholesterol (LDL-C) levels; onset of CVD and end-stage renal disease (ESRD) among those who did not have those conditions; and use of hospital emergency and inpatient services. RESULTS: The study population included 28 578 adults with diabetes. During FY2012, 41.0% of adults with diabetes had ≥1 ECP visits. ECP use, compared with no use, among adults with diabetes was associated with lower odds of high SBP (odds ratio [OR], 0.85; 95% CI, 0.79-0.93; P < .001) and high LDL-C (OR, 0.89; 95% CI, 0.84-0.98; P < .01). Among adults with diabetes without CVD, ≥3 ECP visits vs no visits was associated with lower odds of CVD onset (OR, 0.79; 95% CI, 0.63-0.99; P < .05). ECP was associated with lower odds of ESRD onset (OR, 0.60; 95% CI, 0.39-0.93; P < .05) among adults with both diabetes and CVD. ECP use, compared with no use, among adults with diabetes was also associated with lower odds of having ≥1 hospitalizations (OR, 0.80; 95% CI, 0.71-0.89; P < .001) and having ≥1 potentially preventable hospitalizations (OR, 0.79; 95% CI, 0.64-0.91; P < .05). ECP use was also associated with fewer hospital emergency visits and inpatient days. Despite differences in morbidity between adults with diabetes by CVD status (ie, with and without CVD), some evidence of a positive association between ECP use and patient outcomes (ie, significant improvement) was found among those with and without CVD for 5 of the 7 outcomes examined in both populations. When examining the level (or dose) of ECP service use, we found that for 5 of the 9 total outcomes studied, higher levels of ECP use (ie, ≥3 visits) were associated with greater improvement in patient outcomes. CONCLUSIONS: ECP use was associated with improvements in blood pressure and cholesterol control, lower onset of CVD and ESRD, and lower use of hospital emergency and inpatient services. These results may inform IHS, Tribes, and other organizations in allocating resources for ECP and other services to address the needs of AI/AN adults with diabetes. LIMITATIONS: Study limitations included the use of an observational study design and a propensity score model to control for observed differences between ECP users and nonusers. An assumption associated with the use of a propensity score model is that all potential confounders are included in the analysis, or that possible unobservable factors are correlated with the observable factors. We conducted analyses to assess the sensitivity of our findings to model specifications to address, in part, this potential limitation.
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