The Launch of the iCoDE-2 Standard Project: Integration of Connected Diabetes Device Data Into the Electronic Health Record.

INTRODUCTION: Diabetes Technology Society virtually hosted the first meeting of the Integration of Connected Diabetes Device Data Into the Electronic Health Record #2 (iCoDE-2) Standards Project on May 31, 2023, via Zoom. METHODS: Clinicians, patients, data aggregators, informaticists, manufacturers, attorneys, and cybersecurity experts discussed dosing data currently available from insulin delivery devices and data aggregators and the types of information that patients and clinicians want to see. This information along with technical and regulatory aspects of (1) data standards and (2) integration into the electronic health record (EHR) are the basis of iCoDE-2. RESULTS: Six sessions were hosted discussing themes including (1) What's Currently Available: The Continuous Glucose Monitor Experience; (2) What's Currently Available: The Aggregator Experience; (3) What's Currently Available: The Insulin Pump Experience; (4) What's Currently Available: The Insulin Pen Experience; (5) What Do Clinicians and Patients Want Out of iCoDE-2 Data?; and (6) Technical and Regulatory Aspects of Data Aggregation. CONCLUSION: Additional working group meetings to discuss data standard and clinical workflow will be held to create additional technical specifications and clinical workflows to aid in insulin dosing data integration into the EHR. A mid-project meeting will convene in the second half of 2023.

Characteristics and Results of Pediatric Medical Device Studies: 2017-2022.

OBJECTIVES: The development of medical devices for children faces unique challenges that have contributed to a paucity of devices specifically designed and tested for children. Increased knowledge on research activities for pediatric devices can guide optimal study design and ensure timely dissemination of clinical findings. METHODS: We performed a cross-sectional analysis of interventional studies registered on ClinicalTrials.gov, initiated January 1, 2017, through December 12, 2022, evaluating a Food and Drug Administration-regulated class II or III device, and enrolling any pediatric patients (aged ≤17 years). Data were extracted from ClinicalTrials.gov on study characteristics and from Devices@FDA on device features. For completed studies, we determined whether results were reported in a peer-reviewed publication as of December 27, 2022. RESULTS: Among 482 studies, 406 (84.2%) examined a class II device and 76 (15.8%) a class III device. The most common device types were diabetes-related devices (N = 57, 11.8%) and monitors and measurement devices (N = 39, 8.1%). Most studies were single-center (N = 326, 67.6%), used a nonrandomized (N = 255, 52.9%), open label (N = 350, 72.6%) design, and were funded by academic institutions (N = 278, 57.7%) or industry (N = 142, 29.5%). A total of 291 (60.4%) studies included a primary outcome of only efficacy without safety endpoints. Among completed studies, more than half (N = 64, 51.6%) enrolled <50 participants and 71.0% (N = 88) <100. After median follow-up of 3.0 years, results were available in publications for 27 (21.8%) completed studies. CONCLUSIONS: Our findings serve to inform programs and initiatives seeking to increase pediatric-specific device development. In addition to considerations on ensuring rigorous trial design, greater focus is needed on timely dissemination of results generated in pediatric device studies.

Use of Continuous Glucose Monitors in the Hospital: The Diabetes Technology Society Hospital Meeting Report 2023.

The annual Virtual Hospital Diabetes Meeting was hosted by the Diabetes Technology Society on April 14 and 15, 2023, with the goal of reviewing the progress made in the hospital use of continuous glucose monitors (CGMs). Meeting topics included (1) Nursing Issues, Protocols, Order Sets, and Staff Education for Using CGMs, (2) Implementing CGM Programs for Use in the Wards, (3) Quality Metrics and Financial Implications of CGMs in the Hospital, (4) CGMs in the Critical Care Setting, (5) Special Situations: Labor/Delivery and Hemodialysis, (6) Research Session on CGMs in the Hospital, (7) Starting a CGM on Hospitalized Patients, (8) Automated Insulin Delivery Systems in the Hospital, (9) CGMs in Children, (10) Data Integration of CGMs for Inpatient Use and Telemetry, (11) Accuracy of CGMs/Comparison with Point-of-care Blood Glucose Testing, and (12) Discharge Planning with CGMs. Outcome data as well as shared collective real-life experiences were reviewed, and expert recommendations for CGM implementation were formulated.

Twenty-first century management of diabetes with shared telemedicine appointments.

This commentary article discusses the benefits of utilizing telemedicine to conduct shared medical appointments for people with type 1 diabetes and type 2 diabetes. We conducted a literature review of articles about shared medical appointments or group medical visits in people with diabetes with associated clinical data. We identified 43 articles. Models of this approach to care have demonstrated positive outcomes in adults and children with type 1 diabetes. Shared telemedicine appointments also have the potential to improve diabetes self-management, reduce the treatment burden, and improve psychosocial outcomes in adults with type 2 diabetes. Ten key recommendations for implementation are presented to guide the development of shared telemedicine appointments for diabetes. These recommendations can improve care for diabetes.

Synthesis of PMMA Microspheres with Tunable Diameters: Evaluation as a Template in the Synthesis of Tin Oxide Coatings.

The synthesis of polymethyl methacrylate (PMMA) spheres with different sizes has been a challenge. PMMA has promise for future applications, e.g., as a template for preparing porous oxide coatings by thermal decomposition. Different amounts of SDS as a surfactant are used as an alternative to control PMMA microsphere size through the formation of micelles. The objectives of the study were twofold: firstly, to determine the mathematical relationship between SDS concentration and PMMA sphere diameter, and secondly, to assess the efficacy of PMMA spheres as templates for SnO2 coating synthesis and their impact on porosity. The study used FTIR, TGA, and SEM techniques to analyze the PMMA samples, and SEM and TEM techniques were used for SnO2 coatings. The results showed that PMMA sphere diameter could be adjusted by varying the SDS concentration, with sizes ranging from 120 to 360 nm. The mathematical relationship between PMMA sphere diameter and SDS concentration was determined with a y = axb type equation. The porosity of SnO2 coatings was found to be dependent on the PMMA sphere diameter used as a template. The research concludes that PMMA can be used as a template to produce oxide coatings, such as SnO2, with tunable porosities.

The Need for Data Standards and Implementation Policies to Integrate Insulin Delivery Data Into the Electronic Health Record.

Integration of insulin dosing data into the electronic health record (EHR), combined with other patient-generated health care data, would facilitate the use of wirelessly connected insulin delivery systems, including smart insulin pens, insulin pumps, and advanced hybrid closed-loop systems. In 2022, Diabetes Technology Society developed the Integration of Continuous Glucose Monitoring Data into the EHR (iCoDE) Project, which is the first consensus standard for integrating data from a wearable device into the EHR. The iCoDE Standard is a comprehensive guide for any health care delivery organization or hospital for automatically integrating continuous glucose monitoring data into the EHR. Diabetes Technology Society is following iCoDE with the Integration of Connected Diabetes Device Data into the EHR (iCoDE-2) Project, to similarly provide guidance for integrating insulin delivery data into the EHR alongside continuous glucose monitoring data.

Advancing Equity in Medical Device Development for Children.

This Viewpoint reviews activities to increase pediatric medical device development, assesses ongoing challenges, and recommends strategies to strengthen pediatric programs.

Inpatient medical management of severe pediatric obesity: Literature review and case reports.

Pediatric obesity rates continue to rise steeply with significant adverse effects on health outcomes across the lifespan. Significant obesity can affect the efficacy, side effects, and ability to use certain treatment, medication, or imaging modalities needed in the evaluation and management of acute pediatric conditions. Inpatient settings are rarely used as an opportunity for weight counseling and thus there is a paucity of clinical guidelines on how to manage severe obesity in the inpatient setting. We present a literature review and three patient cases with single-center protocol for non-surgical management of severe obesity in children admitted for other acute medical reasons. We performed a PubMed review from January 2002 to February 2022 utilizing keywords: "inpatient," "obesity," and "intervention." For our cases, we identified three patients with severe obesity acutely impacting their health while admitted for medical treatment who concurrently underwent acute, inpatient, weight loss regimens at a single children's hospital. The literature search yielded 33 articles describing inpatient weight loss treatments. Three patients met case criteria, all three of which demonstrated a decrease in their weight in excess percent of the 95th percentile after inpatient weight-management protocol implementation (% reduction BMIp95: 16%-30%). This highlights obesity acutely limits or impacts specific medical care required during inpatient admissions in pediatric patients. It also suggests that implementation of an inpatient weight-management protocol during admission may provide an opportune setting to support acute weight loss and overall improved health outcomes in this high-risk cohort.

High-risk Therapeutic Devices Approved by the US Food and Drug Administration for Use in Children and Adolescents From 2016 to 2021.

This cohort study examines the characteristics of high-risk therapeutic devices approved by the US Food and Drug Administration for use in children and adolescents between 2016 and 2021.

Use of Continuous Glucose Monitors by People Without Diabetes: An Idea Whose Time Has Come?

BACKGROUND: Continuous glucose monitor (CGM) systems were originally intended only for people with diabetes. Recently, there has been interest in monitoring glucose concentrations in a variety of other situations. As data accumulate to support the use of CGM systems in additional states unrelated to diabetes, the use of CGM systems is likely to increase accordingly. METHODS: PubMed and Google Scholar were searched for articles about the use of CGM in individuals without diabetes. Relevant articles that included sufficient details were queried to identify what cohorts of individuals were adopting CGM use and to define trends of use. RESULTS: Four clinical user cases were identified: (1) metabolic diseases related to diabetes with a primary dysregulation of the insulin-glucose axis, (2) metabolic diseases without a primary pathophysiologic derangement of the insulin-glucose axis, (3) health and wellness, and (4) elite athletics. Seven trends in the use of CGM systems in people without diabetes were idenfitied which pertained to both FDA-cleared medical grade products as well as anticipated future products, which may be regulated differently based on intended populations and indications for use. CONCLUSIONS: Wearing a CGM has been used not only for diabetes, but with a goal of improving glucose patterns to avoid diabetes, improving mental or physical performance, and promoting motivate healthy behavioral changes. We expect that clinicians will become increasingly aware of (1) glycemic patterns from CGM tracings that predict an increased risk of diabetes, (2) specific metabolic glucotypes from CGM tracings that predict an increased risk of diabetes, and (3) new genetic and genomic biomarkers in the future.

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BACKGROUND: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. METHODS: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. RESULTS: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. CONCLUSION: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes.

Artificial intelligence can use real-world data to create models capable of making predictions and medical diagnosis for diabetes and its complications. The aim of this commentary article is to provide a general perspective and present recent advances on how artificial intelligence can be applied to improve the prediction and diagnosis of six significant complications of diabetes including (1) gestational diabetes, (2) hypoglycemia in the hospital, (3) diabetic retinopathy, (4) diabetic foot ulcers, (5) diabetic peripheral neuropathy, and (6) diabetic nephropathy.

Development of a social and environmental determinants of health informatics maturity model.

Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps. Methods: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration's Informatics Enterprise Committee, and a publicly available online self-assessment tool. Results: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels. Conclusion: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities.

Social Determinants of Health Factors for Gene-Environment COVID-19 Research: Challenges and Opportunities.

The characteristics of a person's health status are often guided by how they live, grow, learn, their genetics, as well as their access to health care. Yet, all too often, studies examining the relationship between social determinants of health (behavioral, sociocultural, and physical environmental factors), the role of demographics, and health outcomes poorly represent these relationships, leading to misinterpretations, limited study reproducibility, and datasets with limited representativeness and secondary research use capacity. This is a profound hurdle in what questions can or cannot be rigorously studied about COVID-19. In practice, gene-environment interactions studies have paved the way for including these factors into research. Similarly, our understanding of social determinants of health continues to expand with diverse data collection modalities as health systems, patients, and community health engagement aim to fill the knowledge gaps toward promoting health and wellness. Here, a conceptual framework is proposed, adapted from the population health framework, socioecological model, and causal modeling in gene-environment interaction studies to integrate the core constructs from each domain with practical considerations needed for multidisciplinary science.

Proposing a Practical, Simplified Framework for Implementing Integrated Diabetes Data and Technology Solutions.

Diabetes is a uniquely quantifiable disease, and as technology and data have proliferated over the past two decades, so have the tools to manage diabetes. Patients and providers have at their disposal devices, applications, and data platforms that generate immense amounts of data, provide critical insights into a patient's disease, and allow for personalization of treatment plans. However, the proliferation of options also comes with new burdens for providers: selecting the right tool, getting buy-in from leadership, defining the business case, implementation, and maintenance of the new technology. The complexity of these steps can be overwhelming and sometimes lead to inaction, depriving providers and patients of the advantages of technology-assisted diabetes care. Conceptually, the adoption of digital health solutions can be thought of as occurring in five interconnected phases: Needs Assessment, Solution Identification, Integration, Implementation, and Evaluation. There are a number of existing frameworks to help guide much of this process, but relatively little attention has been focused on integration. Integration is a critical phase for a number of contractual, compliance, financial, and technical processes. Missing a step or doing them out of order can lead to significant delays and potentially wasted resources. To address this gap, we have developed a practical, simplified framework for integrating diabetes data and technology solutions that can guide clinicians and clinical leaders on the critical steps in adopting and implementing a new technology.

Dataset on the first weather radar campaign over Lima, Peru.

The first weather radar campaign over Lima, the capital of Peru, a desertic area on the western side of the Peruvian Andes, was carried out to study the occurrence of rain events in summer 2018. The weather radar was installed strategically and was able to overlook three river basins: Rimac, Chillón, and Lurin. An X-band radar (PX-1000) was used, which operates at 9.55 GHz. PX-1000 was built by the Advanced Radar Research Center (ARRC) at the University of Oklahoma (U.S.A.). The radar operated from January 26th to April 1st, 2018, at Cerro Suche located 2910 m ASL and 55 km from the city of Lima. The PX-1000 performed plan-position-indicators (PPI) for elevations starting at 0° up to 20°. The data presented here were obtained using a three-dimensional constant-altitude plan-position-indicator (3D CAPPI), which was generated by high resolution (250 m) nearest point algorithm.

"Doc McStuffins: Doctor for a Day" Virtual Reality (DocVR) for Pediatric Preoperative Anxiety and Satisfaction: Pediatric Medical Technology Feasibility Study.

BACKGROUND: Preoperative anxiety is a common occurrence among children and is associated with a host of maladaptive postoperative behaviors. Consequently, increased attention has been placed on interventions to reduce preoperative anxiety and its associated outcomes. Child Life preparation prior to surgery includes evidence-based practices such as age-appropriate distraction and therapeutic play. Virtual reality (VR) is a promising addition to the Child Life toolbox to address anxiety prior to surgery. The current study evaluates the implementation and feasibility of a VR experience, "Doc McStuffins: Doctor for a Day Virtual Reality Experience" (DocVR), developed by Disney Junior in collaboration with Children's Hospital Los Angeles, to target pediatric preoperative anxiety. OBJECTIVE: The primary aim of this study was to examine the feasibility and efficacy of DocVR for preoperative anxiety. A secondary aim was to improve patient, caregiver, and health care provider satisfaction with the preoperative experience. METHODS: In this study, 51 patients (age 6-14 years) scheduled for surgery in the ambulatory surgery center and the main operating room at Children's Hospital Los Angeles were approached to participate in Disney's DocVR experience. The patients played the DocVR experience for an average of 18 minutes (3-55 minutes). Irrespective of surgical procedure, patients and their families were eligible, as long as they had no known marked cognitive or visual impairments that would interfere with completing the survey and engaging in the DocVR experience. RESULTS: Patients who tried the DocVR experience (n=51) responded overwhelmingly positively to both the VR technology and to the game itself. Patients experienced a statistically significant decrease in anxiety following DocVR game play (Z=-3.26, P=.001). On the Facial Affective Scale, the percentage of patients who chose the face with the most positive facial expression to represent their affect increased from 23% (12/51) pre-VR to 49% (25/47) post-VR. Furthermore, 97% (38/39) of patients reported feeling more comfortable at the hospital, and 74% (28/38) reported feeling less scared at the hospital after playing the game. The game was enjoyed by 94% (46/49) of patients, and 88% (30/34) of patients reported feeling both "Interested" and "Involved" in the game. CONCLUSIONS: DocVR is a feasible and beneficial VR experience to relieve pediatric preoperative anxiety and improve satisfaction in the preoperative area. The VR experience resulted in a decrease in overall anxiety and an increase in overall positive affect during the preoperative time. Patients also responded positively to the game, confirming their interest in the content and affirming the quality of the DocVR experience. The positive response to the game indicates that DocVR has the potential to make the overall preoperative experience less anxiety-producing and more comfortable, which leads to improved patient satisfaction. Naturally, improved patient outcomes lead to improved caregiver and health care provider satisfaction.

Not just at school: Inclusion of children with autism spectrum disorder in a weight management program in a community pediatric setting.

LAY ABSTRACT: Children diagnosed with autism are likely to be more overweight than children who do not have autism. There are many group programs that help children to be more physically active and improve their eating habits to achieve healthy weight, but most of these programs do not allow children with autism to participate. We studied a program that was specially adapted so children with autism could participate together with peers who do not have autism. The program lasted 8 weeks and was offered in the evening at a large healthcare center in a big city. The children participated with a parent or another adult who takes care of them. We analyzed data that were part of a previous project where we studied how physical activity trackers called Fitbit help overweight children to change their eating and exercise habits so they can achieve healthier weight. Out of 158 families in the study, 15 families had a child or children with autism. We measured changes in the weight of children with and without autism and compared how many of the children completed the program. Children who had autism had similar results in achieving healthy weight and finishing the program compared to their peers without autism. Our study found that when a group weight management program is slightly changed to meet the needs of children with autism, they can successfully participate and benefit similarly to their peers who do not have autism. REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT03215641).