A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring.

Background Disparities in Insulin Pump Use Among Spanish-Speaking Children With Type 1 Diabetes Compared to Their Non-Hispanic White Peers: Mixed Methods Study Objective We aimed to investigate the use of insulin pumps and continuous glucose monitoring (CGM) devices among Spanish-language–preferring children in our clinic population and to identify specific barriers to technology use. Methods First, we assessed rates and patterns of diabetes technology use (eg, insulin pumps and CGM devices) in a sample of 76 children (38 Spanish-language preferring and 38 non-Hispanic White). We compared rates of technology use, average length of time between diabetes diagnosis and initiation of insulin pump or CGM device, and rates of discontinuation of these devices between the Spanish-language–preferring and non-Hispanic White children. Second, to understand specific barriers to technology use, we compared responses to a questionnaire assessing decision-making about insulin pumps. Results Spanish-language–preferring patients had lower rates of insulin pump use, even after controlling for age, gender, age at diagnosis, and type of health insurance. Spanish-language–preferring participants were more likely to report concerns over learning to use an insulin pump and were more likely to discontinue using an insulin pump after starting one. Conclusions These data confirm demographic disparities in insulin pump use among children with T1D and provide new insights about insulin pump discontinuation among Spanish-language–preferring children. Our findings suggest a need for improved patient education about insulin pump technology in general and improved support for Spanish-language–preferring families with T1D after initiation of pump therapy.

https://diabetes.jmir.org/2023/1/e45890/PDF

Disparities in Insulin Pump Use Among Spanish-Speaking Children With Type 1 Diabetes Compared to Their Non-Hispanic White Peers: Mixed Methods Study

Racial and ethnic disparities in healthcare delivery for acutely ill children are pervasive in the United States; it is unknown whether differential critical care utilization exists.Retrospective study of the Pediatric Health Information System (PHIS) database.Multicenter database of academic children's hospitals in the United States.Children discharged from a PHIS hospital in 2019 with one of the top ten medical conditions where PICU utilization was present in greater than or equal to 5% of hospitalizations.None.Race and ethnicity categories included Asian, Black, Hispanic, White, and other. Primary outcomes of interest were differences in rate of PICU admission, and for children requiring PICU care, total hospital length of stay (LOS). One-quarter (n = 44,200) of the 178,134 hospital discharges included a PICU admission. In adjusted models, Black children had greater adjusted odds ratio (aOR [95% CI]) of PICU admission in bronchiolitis (aOR, 1.08 [95% CI, 1.02-1.14]; p = 0.01), respiratory failure (aOR, 1.18 [95% CI, 1.10-1.28]; p < 0.001), seizure (aOR, 1.28 [95% CI, 1.08-1.51]; p = 0.004), and diabetic ketoacidosis (DKA) (aOR, 1.18 [95% CI, 1.05-1.32]; p = 0.006). Together, Hispanic, Asian, and other race children had greater aOR of PICU admission in five of the diagnostic categories, compared with White children. The geometric mean (± sd) hospital LOS ranged from 47.7 hours (± 2.1 hr) in croup to 206.6 hours (± 2.8 hr) in sepsis. After adjusting for demographics and illness severity, non-White children had longer LOS in respiratory failure, pneumonia, DKA, and sepsis.The need for critical care to treat acute illness in children may be inequitable. Additional studies are needed to understand and eradicate differences in PICU utilization based on race and ethnicity. 

Race, Ethnicity, and Intensive Care Utilization for Common Pediatric Diagnoses: U.S. Pediatric Health Information System 2019 Database Study.

Diabetes technologies, including continuous glucose monitors, insulin pumps, and automated insulin delivery systems offer the possibility of improving glycemic outcomes, including reduced hemoglobin A1c, increased time in range, and reduced hypoglycemia. Given the rapid expansion in the use of diabetes technology over the past few years, and touted promise of these devices for improving both clinical and psychosocial outcomes, it is critically important to understand issues in technology adoption, equity in access, maintaining long-term usage, opportunities for expanded device benefit, and limitations of the existing evidence base. We provide a brief overview of the status of the literature—with a focus on psychosocial outcomes—and provide recommendations for future work and considerations in clinical applications. Despite the wealth of the existing literature exploring psychosocial outcomes, there is substantial room to expand our current knowledge base to more comprehensively address reasons for differential effects, with increased attention to issues of health equity and data harmonization around patient-reported outcomes. 

Psychosocial Aspects of Diabetes Technologies: Commentary on the Current Status of the Evidence and Suggestions for Future Directions

Abstract Aims There are marked inequities in clinical outcomes and rates of diabetes technology use among youth with type 1 diabetes (T1D). The quantitative data from our mixed methods cohort study identified significant improvements in glycaemia and quality of life in participants. We aimed to use qualitative methods to provide further insight into our quantitative findings in the setting of underlying health disparities. Methods Fifteen publicly insured, insulin pump‐naïve non‐Hispanic Black youth aged 6–21 years with T1D and baseline haemoglobin A 1c (HbA 1c ) ≥86 mmol/mol (10%) and their parents participated in a mixed methods cohort study. Semi‐structured interviews were conducted separately with parents and youth after completion of 6 months of HCL use. Three topic areas were explored: (1) Experience using HCL, (2) barriers to HCL and (3) facilitators to accessing HCL. Semantic content analysis and consensus coding involving two team members were used to generate themes. Thematic saturation was achieved. Results Youth (Median age 14.9 years, 67% female) and parents (92% female) were interviewed. Youth and their parents reported that access to HCL provides a new outlook on living with T1D, although managing T1D is still hard. They felt that diabetes technology is most helpful for those struggling with management. Participants experienced barriers to access including misconceptions of HCL systems, clinician bias and systemic racism. They suggested these barriers can be overcome by offering diabetes technology education for all people with T1D, increasing awareness of HCL in the community and providing resources to overcome barriers created by social determinants of health. Conclusions The voices of historically minoritised youth with suboptimal T1D control and their parents provide important, previously unreported experiences and perspectives on barriers and facilitators to using HCL that will shape interventions to improve equity in access to diabetes technology. 

Improving equity in diabetes technology use: Voices of youth and their parents

Objective: To evaluate changes in insulin pump use over two decades in a national U.S. sample. Research Design and Methods: We used data from the SEARCH for Diabetes in Youth study to perform a serial cross-sectional analysis to evaluate changes in insulin pump use in participants <20 years old with type 1 diabetes by race/ethnicity and markers of socioeconomic status across four time periods between 2001 and 2019. Multivariable generalized estimating equations were used to assess insulin pump use. Temporal changes by subgroup were assessed through interactions. Results: Insulin pump use increased from 31.7% to 58.8%, but the disparities seen in pump use persisted and were unchanged across subgroups over time. Odds ratio for insulin pump use in Hispanic (0.57, confidence interval [95% CI] 0.45-0.73), Black (0.28, 95% CI 0.22-0.37), and Other race (0.49, 95% CI 0.32-0.76) participants were significantly lower than White participants. Those with ≤high school degree (0.39, 95% CI 0.31-0.47) and some college (0.68, 95% CI 0.58-0.79) had lower use compared to those with ≥bachelor's degree. Those with public insurance (0.84, 95% CI 0.70-1.00) had lower use than those with private insurance. Those with an annual household income <$25K (0.43, 95% CI 0.35-0.53), $25K-$49K (0.52, 95% CI 0.43-0.63), and $50K-$74K (0.79, 95% CI 0.66-0.94) had lower use compared to those with income ≥$75,000. Conclusion: Over the past two decades, there was no improvement in the racial, ethnic, and socioeconomic inequities in insulin pump use, despite an overall increase in use. Studies that evaluate barriers or test interventions to improve technology access are needed to address these persistent inequities.

A Longitudinal View of Disparities in Insulin Pump Use Among Youth with Type 1 Diabetes: The SEARCH for Diabetes in Youth Study.

Objective With the high prevalence of pediatric obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D). Methods We studied 2,966 youth with diabetes in the prospective SEARCH study (diagnosis age [≤]19 years) to develop prediction models to identify participants with fasting c-peptide [≥]250 pmol/L ([≥]0.75ng/ml) after >3 years (median 74 months) of diabetes duration. Models included clinical measures at baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL-C), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS). Results Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with c-peptide [≥]0.75 ng/ml (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under receiver operator curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope=0.995-0.999). Models retained high performance for predicting retained c-peptide in older youth with obesity (AUCROC 0.88-0.96), and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92). Conclusion Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with type 2 diabetes.

Clinical prediction models combining routine clinical measures identify participants with youth-onset diabetes who maintain insulin secretion in the range associated with type 2 diabetes: The SEARCH for Diabetes in Youth Study

OBJECTIVE
With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D).


RESEARCH DESIGN AND METHODS
We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS).


RESULTS
Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995-0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88-0.96) and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92).


CONCLUSIONS
Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D.

Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study.

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A Longitudinal View of Disparities in Insulin Pump Use Among Youth with Type 1 Diabetes: The SEARCH for Diabetes in Youth Study.

Clinical prediction models combining routine clinical measures identify participants with youth-onset diabetes who maintain insulin secretion in the range associated with type 2 diabetes: The SEARCH for Diabetes in Youth Study

Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study.