Aim: Despite disruptions caused by the COVID-pandemic, prior studies suggest some improvements in glycemic control. We investigated whether this improvement was equitable and seen across socioeconomic status (SES) groups in youth with T1D. Method: Using EHR-extracted visit and CGM data, we geocoded patient addresses linked with census-tract derived education from the 20American Community Survey and a composite measure of SES, the Neighborhood Deprivation Index (NDI) . Analyses included youth ≤18 years old using CGM with T1D duration ≥6 months (age <6 yrs) or ≥1 yr (age ≥6 yrs) . We performed t-tests and regressions comparing SES and CGM metrics during the pandemic (4/1/20-3/15/21) with pre-pandemic (4/1/19-3/15/20) . Results: The pre-pandemic sample had 641 youth (52% female, age 12.5±3.5, T1D 6.2±3.5 yrs) and the pandemic sample had 650 youth (52% female, age 13.5±3.6, T1D 6.8±3.8 yrs) ; 86% were common to both samples. Addresses allowed for geocoding of 98%; 44% of youth lived in low education census tracts where ≥30% of adults in the census tract had no more than a high school education. Mean CGM-derived glucose management indicator (GMI) improved during the pandemic for both those living in lower (8.07±0.05% pre vs. 7.91±0.% during, p<0.05) and higher SES education tracts (7.82±0.% pre vs. 7.69±0.% during) . There was similar improvement in GMI in lower vs. higher SES education tracts (0.16±.vs. 0.13±.06) . Other CGM metrics similarly improved during the pandemic, mean CGM glucose decreased by 6.7 mg/dL and 5.4 mg/dL in low and high SES education tract patients respectively (both p<.05) . Those living in the most deprived NDI areas had the highest GMI both pre and during the pandemic (p<0.05) and demonstrated similar or greater improvements than those from Iess deprived areas. Conclusion: Equitable improvements in CGM metrics during the pandemic was evident in youth with T1D. Future studies can assess how changes in healthcare delivery during the pandemic can reduce disparities and sustain benefits to all patients. Disclosure S.Ojukwu: None. A.Adam: None. T.Kaushal: None. L.J.Tinsley: None. L.K.Volkening: None. C.Chen: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding National Institutes of Health (K12DK094721, P30DK036836)
The pandemic required altering care delivery to a hybrid model of telehealth and in-person visits. We evaluated if SES disparities during the pandemic impacted clinical visit adherence and CGM device use in youth with T1D. Retrospective EHR captured data on youth with T1D, ≤18 years old, with ≥1 clinical visit both pre-pandemic (9/15/18-3/15/20) and during the pandemic (4/1/20-12/22/21) . Patient addresses were geocoded to link with census tract SES measures from the 20American Community Survey. Low education status defined as ≥30% of residents having HS or lower education and low income as median household income ≤$40,000. Poisson and logistic regression models assessed appointment adherence and CGM device use, respectively, during the pandemic vs. pre-pandemic. Models were adjusted for age, gender, baseline A1c, and T1D duration. In both periods, 689 youth (age 13.8±3.3 years; male 49%; T1D duration 7.4 ±3.6 years) had clinical encounters. There were more visits in the pandemic vs. pre-pandemic (8 [IQR 5-11] vs. 6 [IQR 5-9], p<.001) . In adjusted models, youth living in tracts with low education or low income had 1.16x (95% CI 1.06-1.27, p-.002) and 1.20x (95% CI 1.09-1.32, p<.001) ,respectively, greater rates of increased visits during the later time period vs. those not living in lower education or income tracts. W/R to CGM use, 57% (n=392) used CGM pre-pandemic and 21% (n=83) stopped using CGM during the pandemic. In adjusted models, youth in tracts with low vs. high education had 2.81-fold increased odds (95% CI 1.56-5.07, p<.001) of stopping CGM during the pandemic. Similarly, youth from low vs. high income tracts had 2.49-fold increased odds (95% CI 1.39-4.46, p<.001) of stopping CGM. These data indicate variability in appointment adherence and CGM use during the pandemic based on census SES status. Vulnerable youth by SES factors appear to benefit from hybrid care model W/R to maintaining visits, although such youth appear more likely to stop CGM. Further research is needed further reduce health disparities. Disclosure A.Adam: None. C.Chen: None. S.Ojukwu: None. T.Kaushal: None. L.J.Tinsley: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc.
Aim: Providers may avoid offering pump therapy to teens with EF challenges (planning, organization). We assessed whether the association of pump use and A1c is modified by EF status, adjusting for relevant factors. Methods: EF was assessed by parent proxy-report using Behavior Rating Inventory of Executive Function (BRIEF). T-score ≥60 defined risk of EF problems for Global Executive Composite (GEC), Behavioral Regulation Index (BRI), and Metacognition Index (MI). Parents also completed the Diabetes Family Conflict Scale (DFCS). T-tests stratified by EF status compared A1c by pump use and non-use. Generalized linear models were adjusted (Tukey) for variables with p<.1 in univariate analysis. Results: Teens (N=169, 54% male) had mean age 14.9±1.3 yrs, diagnosis age 7.5±3.6 yrs, A1c 8.5±1%, 69% pump use, 9% CGM use, and 31% with GEC ≥60. With GEC <60, A1c was similar in pump users and non-users (8.3 vs 8.6%, p=.25); with GEC ≥60, A1c was lower in pump users vs non-users (8.5 vs 9.2%, p=.009). Similar A1c patterns were seen when stratified by EF problems in BRI or MI. In multivariate analysis, with GEC <60, A1c did not differ in pump users vs non-users (8.4 vs 8.6%, p=.36), adjusting for DFCS; a similar pattern was seen with BRI <60 (p=.26) and MI <60 (p=.25). With GEC ≥60, there was a trend towards lower A1c in pump users vs non-users (8.1% vs 8.7%, p=.07), adjusting for income and CGM use. With BRI ≥60, A1c was lower in pump users vs non-users (7.8 vs 8.4%, p=.03), adjusting for CGM use and DFCS score. With MI ≥60, A1c was not significantly different in pump users vs non-users (8.0% vs 8.4%, p=.25), adjusting for income, CGM use, and DFCS score. With elevated GEC, BRI, or MI scores in above multivariate analyses, A1c was lower in CGM users vs non-users (all p<.05). Conclusion: The association of diabetes technology use with lower A1c in those with elevated BRIEF scores suggests a need to re-evaluate provider reluctance to recommend use of diabetes technologies in teens presenting with potential EF problems. Disclosure R.J.Vitale: None. L.K.Volkening: None. L.J.Tinsley: None. L.M.Laffel: Advisory Panel; Medtronic, Lilly Diabetes, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Roche Diagnostics, Provention Bio, Inc., Consultant; Dexcom, Inc., Janssen Pharmaceuticals, Inc., Medscape. Funding National Institutes of Health (P30DK036836, R01DK095273); JDRF (2-SRA-2014-253-M-B); Iacocca Family Foundation
Aim: YA with T1D have high risk of rising A1c and loss to follow up. To understand factors associated with visit frequency, we compared characteristics of YA with T1D seen in pediatric vs adult diabetes clinics in the pre- and pandemic periods. Methods: EMR data included YA, aged 18-30 yrs, with T1D in pediatric and adult clinics during the pre- and pandemic (4/1/19 to 3/15/20 and 3/30/20 to 3/15/21, respectively), for both inperson and telehealth visits. Results: There were 1,762 YA (54% male), aged 24.0±3.6 yrs, with T1D duration 13.4±6.3 yrs and A1c 8.2±1.6%; 61% were pump treated; 64% used CGM. Pre-pandemic, almost all visits were inperson while most pandemic visits were virtual. During the pandemic, proportion of virtual visits was greater in pediatric vs adult care (99% vs 90%, p<.001). Overall, pre-pandemic visit frequency was 3.5±3.4, reduced to 3.1±4.1 (p<.0001) during pandemic. Pre-pandemic visit frequency was higher in those with higher A1c (r =.18, p<.001) in pediatric and adult care. During pandemic, YA visit frequency was preserved across A1c groups only for those in pediatric care (Figure 1). Pandemic visit frequency was lower in adult care regardless of sex, pump, CGM or A1c. Conclusion: Maintaining visit frequency may mitigate glycemic deterioration in YA with T1D. Pediatric care likely maintained visit frequency through use of telehealth, highlighting need for hybrid care to optimize outcomes. Disclosure A. Shapira: None. L. J. Tinsley: None. E. Toschi: Advisory Panel; Eli Lilly and Company. L. M. Laffel: Advisory Panel; Medtronic, Lilly Diabetes, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Roche Diagnostics, Provention Bio, Inc., Consultant; Dexcom, Inc., Janssen Pharmaceuticals, Inc., Medscape. Funding Thomas J. Beatson, Jr. Foundation
Care management efforts focused on patients not achieving quality goals can improve performance in value-based care quality programs, but may pose challenges for integration into routine clinical care. We evaluated a 12-month NP-led care management pilot program (CMPP) to improve outcomes for adults with T2DM and A1c>9% (N=62, 40% male) covered under a value-based care quality program and receiving care at a diabetes center. Visits were scheduled as billable encounters between routine clinical visits. Diabetes quality outcomes (A1c≤9%, BP<140/90, and annual retinal screening) were assessed by CMPP participation. For this pilot program, p<0.05 and p<0.10 defined significance and trend, respectively. The CMPP began in November 2020 with 43% (n=27) participation; participants and non-participants had no baseline differences in age, diabetes duration, or baseline attainment of diabetes quality metrics. CMPP participants had more visits compared to non-participants over the 12 month pilot period (10.4 vs. 4.0, p<.001); 62% of participant visits were virtual vs 47% among non-participants (p=.01). At 12 months, CMPP participants had a significant improvement in % A1c≤9% and trended towards improved annual retinal screening. This integrated NP-led CMPP leveraging virtual care may improve diabetes quality outcomes. Future efforts will focus on scaling and implementation in primary care. Disclosure L.J.Tinsley: None. K.D.Ariyabuddhiphongs: None. E.Halprin: None. J.Beaulieu: None. M.Moreau: None. A.Millan-ferro: None. J.Rizzotto: None. B.Cronin: None. S.N.Mehta: None.
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