The Neighborhood Deprivation Index and Provider Geocoding Identify Critical Catchment Areas for Diabetes Outreach.

PURPOSE: In designing a Project ECHO™ type 1 diabetes (T1D) program in Florida and California, the Neighborhood Deprivation Index (NDI) was used in conjunction with geocoding of primary care providers (PCPs) and endocrinologists in each state to concurrently identify areas with low endocrinology provider density and high health risk/poverty areas. The NDI measures many aspects of poverty proven to be critical indicators of health outcomes. METHODS: The data from the 2013-2017 American Community Survey (ACS) 5-year estimates were used to create NDI maps for California and Florida. In addition, geocoding and 30-minute drive-time buffers were performed using publicly available provider directories for PCPs and endocrinologists in both states by Google Geocoding API and the TravelTime Search Application Programming Interface (API). RESULTS: Based on these findings, we defined high-need catchment areas as areas with (1) more than a 30-minute drive to the nearest endocrinologist but within a 30-minute drive to the nearest PCP; (2) an NDI in the highest quartile; and (3) a population above the median (5199 for census tracts, and 1394 for census block groups). Out of the 12 181 census tracts and 34 490 census block groups in California and Florida, we identified 57 tracts and 215 block groups meeting these criteria as high-need catchment areas. CONCLUSION: Geospatial analysis provides an important initial methodologic step to effectively focus outreach efforts in diabetes program development. The integration of the NDI with geocoded provider directories enables more cost-effective and targeted interventions to reach the most vulnerable populations living with T1D.

Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management.

BACKGROUND: Continuous glucose monitoring (CGM) offers multiple data features that can be leveraged to assess glucose management. However, how diabetes healthcare professionals (HCPs) actually assess CGM data and the extent to which they agree in assessing glycemic management are not well understood. METHODS: We asked HCPs to assess ten de-identified CGM datasets (each spanning seven days) and rank order each day by relative glycemic management (from "best" to "worst"). We also asked HCPs to endorse features of CGM data that were important in making such assessments. RESULTS: In the study, 57 HCPs (29 endocrinologists; 28 diabetes educators) participated. Hypoglycemia and glycemic variance were endorsed by nearly all HCPs to be important (91% and 88%, respectively). Time in range and daily lows and highs were endorsed more frequently by educators (all Ps < .05). On average, HCPs endorsed 3.7 of eight data features. Overall, HCPs demonstrated agreement in ranking days by relative glycemic control (Kendall's W = .52, P < .001). Rankings were similar between endocrinologists and educators (R2 = .90, Cohen's kappa = .95, mean absolute error = .4 [all Ps < .05]; Mann-Whitney U = 41, P = .53). CONCLUSIONS: Consensus in the endorsement of certain data features and agreement in assessing glycemic management were observed. While some practice-specific differences in feature endorsement were found, no differences between educators and endocrinologists were observed in assessing glycemic management. Overall, HCPs tended to consider CGM data holistically, in alignment with published recommendations, and made converging assessments regardless of practice.

Perspectives on the role of exercise in the treatment of pediatric type 1 diabetes.

BACKGROUND: Studies demonstrate that children with type 1 diabetes may not be meeting exercise recommendations. This, coupled with the lack of data on the determinants of exercise promotion in youth, may indicate a need for additional focus on exercise guidelines and promotion in youth with type 1 diabetes. OBJECTIVE: The objective of this study is to understand provider perspectives regarding exercise promotion in children with type 1 diabetes. SUBJECTS AND METHODS: An online survey regarding perspectives on exercise was emailed to Pediatric Endocrine Society members. RESULTS: Of the 84 respondents, 85.5% believe counseling regarding exercise recommendations is a priority. However, 87.8% did not identify Office of Disease Prevention and Health Promotion (ODPHP) guidelines correctly and 79.3% did not identify American Diabetes Association (ADA) guidelines correctly. Providers who exercised regularly (P = .009) and providers who identified ODPHP guidelines correctly (P = .004) were more likely to identify ADA guidelines correctly. Providers who identified ADA guidelines correctly were 4.21 times (OR 4.21; 95% CI 1.30-13.7) more likely to make good recommendations and those who discussed recommendations at diagnosis were 6.10 times (OR 6.10; 95% CI 1.76-21.2) more likely to make good recommendations. CONCLUSION: To our knowledge, this study is the first to investigate provider perspectives of exercise promotion in children with type 1 diabetes. We found provider recommendations were not consistent with ADA exercise guidelines and most providers were not fully aware of the recommendations. Future research should address increasing provider education regarding exercise guidelines and developing exercise promotion tools.

Association between provider specialty and healthcare costs and glycemic control for patients with diabetes.

AIMS: To analyze the association between provider, healthcare costs, and glycemic control for patients with diabetes mellitus (DM). MATERIALS AND METHODS: This cross-sectional study identified adults with type 1 or 2 DM (T1D, T2D) in the Optum database. The main independent variable was provider (endocrinologist or primary care). Regression analysis compared total medical and pharmacy costs, adjusting for health status and other patient differences, by provider. RESULTS: For all patients, HbA1C improvement was greater, and medical costs significantly lower with an endocrinologist rather than a primary care provider. The largest HbA1C improvement (4%) occurred for insulin-dependent patients seen by endocrinologists. Significant medical savings with endocrinologist management occurred within the Medicare Advantage population in every sub-group of patients, with 14% lower costs ($4,767) for patients with T1D, 11% lower costs ($3,160) for patients with macro- and microvascular complications, and 10% lower costs ($2,237) for insulin-dependent patients. Within the commercial insurance population, medical costs were reduced by ≥9% in every sub-group of patients, with a 20% reduction ($8,450) for patients with micro- and macrovascular complications. Overall total costs (medical and pharmacy) were 8% ($1,541) higher for patients receiving endocrinologist rather than primary care, although endocrinologist care resulted in a 9% reduction (-$3,710) in costs for Medicare Advantage patients with T1D. Total medical costs (excluding pharmacy costs) may be a more accurate indicator of costs associated with patients in various stages of DM. LIMITATIONS: There was insufficient data to develop risk-adjustment payments for pharmacy costs based on disease severity. The cross-sectional design identifies associations and not cause-effect relationships. CONCLUSION: DM management by an endocrinologist was associated with greater HbA1C improvement and significantly lower medical costs. Total costs were higher with an endocrinologist, but for patients with T1D lower costs were seen, ranging from 2-9% regardless of insurance type.

The Berlin Declaration: A call to action to improve early actions related to type 2 diabetes. How can specialist care help?

Diabetes is a major global epidemic and places a huge burden on healthcare systems worldwide. The complications of type 2 diabetes (T2D) and related hospitalizations are major contributors to this burden, and there is strong evidence that the risk for these can be reduced by early action to identify and prevent progression of people at high risk of T2D and ensure tight glycemic control in those with established disease. In response to this, the Berlin Declaration was developed by four working groups of experts and ratified by healthcare professionals from 38 countries. Its aim is to act as a global call to action for early intervention in diabetes, in addition to providing short-, medium- and long-term targets that should be relevant to all nations. The Berlin Declaration focuses on four aspects of early action, and proposes actionable policies relating to each aspect: early detection, prevention, early control and early access to the right interventions. In addition, a number of treatment targets are proposed to provide goals for these policies. To ensure that the suggested policies are enacted in the most effective manner, the support of specialist care professionals is considered essential.

Primary care and chronic disease: the intersection of comfort and specialty involvement - a cross-sectional study.

BACKGROUND: Primary care referrals to specialty physicians play an integral role in patient care and health care costs. Multiple factors play into the primary care physician's decision to refer, including comfort managing particular conditions. As the burden of chronic disease climbs, the relationship between patients, primary care physicians and specialists in accurately diagnosing, managing and treating chronic conditions needs clarity. The objective of this study is to assess the relationship between specialty physician involvement and the care of three chronic conditions: diabetes mellitus (DM), chronic kidney disease (CKD) and systemic lupus erythematosus (SLE). METHODS: To achieve this objective, we performed a cross-sectional study of 2013 MarketScan data (875 million billing records) for three chronic medical conditions. Participants were identified in the dataset by having received a diagnosis code for DM, CKD or SLE in an outpatient care setting during 2013. The study compared proportions of outpatient visits with specialty physicians in endocrinology, nephrology and rheumatology for patients with DM, CKD and SLE respectively. RESULTS: Data included 1 615 609 visits with the diagnosis of DM, 158 424 visits with the diagnosis of CKD and 103 910 visits with SLE. Diabetic patients met endocrinologists (10.2%) at a smaller proportion of their visits than patients with CKD saw nephrologists (41.2%, P < 0.0001). Further, CKD patients met with nephrologists (41.2%) at a significantly fewer proportion of outpatient visits than SLE patients saw rheumatologists (51.8%, P < 0.0001). CONCLUSIONS: Differences in primary care physicians' comfort with diagnosis, therapy and adherence to published guidelines affect the rate with which primary care providers seek specialty consultation.