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BackgroundDiabetes and its complications are more common in American Indians and Alaska Natives (AI/AN) than other US racial/ethnic populations. Prior reports of diabetic retinopathy (DR) prevalence in AI/AN are dated, and research on diabetic macular edema (DME) is limited. This study characterizes the recent prevalence of DR and DME in AI/AN using primary care-based teleophthalmology surveillance.MethodsThis is a multi-site, clinic-based, cross-sectional study of DR and DME. The sample is composed of AI /AN patients with diabetes (n = 53,998), served by the nationally distributed Indian Health Service-Joslin Vision Network Teleophthalmology Program (IHS-JVN) in primary care clinics of US Indian Health Service (IHS), Tribal, and Urban Indian health care facilities (I/T/U) from 1 November 2011 to 31 October 2016. Patients were recruited opportunistically for a retinal examination using the IHS-JVN during their regular diabetes care. The IHS-JVN used clinically validated, non-mydriatic, retinal imaging and retinopathy assessment protocols to identify the severity levels of non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR), DME, and sight threatening retinopathy (STR; a composite measure). Key social-demographic (age, gender, IHS area), diabetes-related health (diabetes therapy, duration of diabetes, A1c), and imaging technology variables were examined. The analysis calculated frequencies and percentages of severity levels of disease.ResultsPrevalence of any NPDR, PDR, DME, and STR among AI/AN patients undergoing DR teleophthalmology surveillance by IHS-JVN was 17.7%, 2.3%, 2.3%, and 4.2%, respectively. Prevalence was lowest in Alaska and highest among patients with A1c >/ = 8%, duration of diabetes > 10 years, or using insulin.ConclusionsPrevalence of DR in this cohort was approximately half that in previous reports for AI/AN, and prevalence of DME was less than that reported in non-AI/AN populations. A similar reduction in diabetes related end-stage renal disease in the same population and time period has been reported by other researchers. Since these two diabetic complications share a common microvasculopathic mechanism, this coincident change in prevalence may also share a common basis, possibly related to improved diabetes management.

Several studies suggest that telehealth eye care programs that combine retinal imaging, education, and some care management can improve patient adherence to annual, comprehensive eye examinations and follow-up treatments. Little is known, however, about whether such programs relate to other, more distal outcomes that affect diabetic eye disease, such as blood glucose control. This paper assesses the relationship of participation in a diabetes telehealth eye care program with standard, face-to-face eye care as well as improvements in other diabetes-related health outcomes. We conducted a retrospective study using data from electronic medical records of Joslin Diabetes Center (n=13,752). The data span 2 years: baseline and follow-up. Subjects' eye care groups were no eye care, eye care outside of the clinic, standard eye care at the clinic, or participation in the Joslin Vision Network telehealth eye care program. We analyzed the relationship of participation in the telehealth eye care program at baseline to follow-up eye care groups and changes in hemoglobin A1c, low density lipoprotein levels, and systolic blood pressure. The results show that participation in the telehealth eye care program was significantly correlated with whether subjects later obtained standard eye care, improvement in hemoglobin A1c, and improvement in low density lipoprotein. Thus, telehealth eye care programs that incorporate evaluation, education, and care planning are related to use of recommended eye care and improvements in certain diabetes-related health outcomes. Such programs can address the many aspects of care necessary to reduce risk of vision loss due to diabetic retinopathy and other diabetes-related complications. Future research might test hypotheses suggested by sociological and psychological theories regarding causation between participation in a telehealth eye care program and other diabetes care.

Background: Historically, fewer than half of American Indians and Alaska Natives (AI/AN) with diabetes received the annual diabetic retinopathy (DR) examination that is considered the minimum standard of care; this rate is similar to that of the general United States (U.S.) population with diabetes. Solution: The Indian Health Service-Joslin Vision Network (IHS-JVN) Teleophthalmology Program in 2000 to increase compliance with DR standards of care among AI/AN through validated, primary care-based telemedicine. The IHS-JVN provides remote diagnosis of DR severity, with a report including management recommendations that is returned to the patient's primary care provider. The program conforms with the American Telemedicine Association (ATA) Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy. Outcomes: The IHS-JVN has been expanding incrementally since the first patients were recruited in 2000; this expansion coincides with large improvements in the annual DR examination rates reported as part of local, regional, and national regulatory compliance under the Government Performance and Results Act (GPRA). Currently, with 99 clinical implementations in 23 states, IHS-JVN is the largest primary care-based ATA validation category three telemedicine program in the U.S. Summary: This article describes the program's workflow, imaging and reading technologies, diagnostic protocols, reports to providers, training, quality assurance processes, and geographical distribution. In addition to its clinical use, the program has been utilized in research on utilization of diabetic eye care, cost-effectiveness, technology development, and DR epidemiology of the AI/AN population. Potential next steps for this program are discussed.

Estimation of glycemic variability requires frequent measures of glucose and is greatly aided by continuous glucose monitoring (CGM); however, under real-world conditions, missing data or “gaps” of ≥ 10 minutes can occur in CGM data, affecting the reliability of certain estimates. Thus, we determined the magnitude of the gap problem as observed in a cohort of patients with type 2 diabetes and demonstrated an approach to fill the gaps. The approach takes the difference between readings before and after a gap and distributes the difference equally across the number of missing readings, as determined by the sensor's setting for reading frequency. The approach is easy to implement, conservative, and improves estimation of variability measures that reference time, namely, mean of daily differences and continuous overlapping net glycemic action.