Improving Outcomes for Diverse Diabetic Populations
Improving Outcomes for Diverse Diabetic Populations
The limitations of this research are rooted in three key areas: (1) lack of clinical relevance of the change in non-A1C clinical diabetes indicators; (2) variability of practice models and care delivery among the 25 communities; and (3) transience and poverty-related challenges of the diverse populations of patients in these disproportionately affected communities.
While improvements in LDL-C, triglycerides, and total cholesterol were statistically significant, they were associated with a small effect size. Additionally, a variety of factors may have influenced the ability to observe a statistically or clinically relevant response in clinical indicators other than A1C. Baseline mean measures for systolic blood pressure, diastolic blood pressure, LDL-C, and HDL-C were less than ADA treatment goals, and this may have had an impact on clinical improvements. The 12-month study period may have been too short to observe a meaningful reduction in BMI. Health care teams encountered many patient barriers, including economic, social, and cultural factors, that interfered with patients' abilities to prioritize their health and focus on achieving broader health goals beyond blood sugar control.
Each community was encouraged to use or expand established interdisciplinary practice models or to develop new models to meet their unique needs and circumstances. As a result, wide variability exists among practices in how pharmacists interact with patients and health care team members. Additionally, variability in the types of patient and provider incentives employed across communities limits making comparative conclusions regarding the relative effectiveness of incentives.
Because of the patient barriers described above, 453 patients were lost to follow-up. Patients frequently missed appointments when they could not find or afford transportation. Addresses and contact numbers changed routinely for patients with transient living arrangements (e.g., moving among shelters and homes of family members) and disconnected phones. Future research that integrates transportation incentives and other proactive means for maintaining connection with patients at risk for homelessness or without reliable transportation could provide solutions and guidance generalizable to similar populations.
Limitations
The limitations of this research are rooted in three key areas: (1) lack of clinical relevance of the change in non-A1C clinical diabetes indicators; (2) variability of practice models and care delivery among the 25 communities; and (3) transience and poverty-related challenges of the diverse populations of patients in these disproportionately affected communities.
While improvements in LDL-C, triglycerides, and total cholesterol were statistically significant, they were associated with a small effect size. Additionally, a variety of factors may have influenced the ability to observe a statistically or clinically relevant response in clinical indicators other than A1C. Baseline mean measures for systolic blood pressure, diastolic blood pressure, LDL-C, and HDL-C were less than ADA treatment goals, and this may have had an impact on clinical improvements. The 12-month study period may have been too short to observe a meaningful reduction in BMI. Health care teams encountered many patient barriers, including economic, social, and cultural factors, that interfered with patients' abilities to prioritize their health and focus on achieving broader health goals beyond blood sugar control.
Each community was encouraged to use or expand established interdisciplinary practice models or to develop new models to meet their unique needs and circumstances. As a result, wide variability exists among practices in how pharmacists interact with patients and health care team members. Additionally, variability in the types of patient and provider incentives employed across communities limits making comparative conclusions regarding the relative effectiveness of incentives.
Because of the patient barriers described above, 453 patients were lost to follow-up. Patients frequently missed appointments when they could not find or afford transportation. Addresses and contact numbers changed routinely for patients with transient living arrangements (e.g., moving among shelters and homes of family members) and disconnected phones. Future research that integrates transportation incentives and other proactive means for maintaining connection with patients at risk for homelessness or without reliable transportation could provide solutions and guidance generalizable to similar populations.
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