Algorithm-Enabled, Personalized Glucose Management for Type 1 Diabetes at the Population Scale: Prospective Evaluation in Clinical Practice.
2022; 7 (2): e27284
BACKGROUND: The use of continuous glucose monitors (CGMs) is recommended as the standard of care by the American Diabetes Association for individuals with type 1 diabetes (T1D). Few hardware-agnostic, open-source, whole-population tools are available to facilitate the use of CGM data by clinicians such as physicians and certified diabetes educators.OBJECTIVE: This study aimed to develop a tool that identifies patients appropriate for contact using an asynchronous message through electronic medical records while minimizing the number of patients reviewed by a certified diabetes educator or physician using the tool.METHODS: We used consensus guidelines to develop timely interventions for diabetes excellence (TIDE), an open-source hardware-agnostic tool to analyze CGM data to identify patients with deteriorating glucose control by generating generic flags (eg, mean glucose [MG] >170 mg/dL) and personalized flags (eg, MG increased by >10 mg/dL). In a prospective 7-week study in a pediatric T1D clinic, we measured the sensitivity of TIDE in identifying patients appropriate for contact and the number of patients reviewed. We simulated measures of the workload generated by TIDE, including the average number of time in range (TIR) flags per patient per review period, on a convenience sample of eight external data sets, 6 from clinical trials and 2 donated by research foundations.RESULTS: Over the 7 weeks of evaluation, the clinical population increased from 56 to 64 patients. The mean sensitivity was 99% (242/245; SD 2.5%), and the mean reduction in the number of patients reviewed was 42.6% (182/427; SD 10.9%). The 8 external data sets contained 1365 patients with 30,017 weeks of data collected by 7 types of CGMs. The rates of generic and personalized TIR flags per patient per review period were, respectively, 0.15 and 0.12 in the data set with the lowest average MG (141 mg/dL) and 0.95 and 0.22 in the data set with the highest average MG (207 mg/dL).CONCLUSIONS: TIDE is an open-source hardware-agnostic tool for personalized analysis of CGM data at the clinical population scale. In a pediatric T1D clinic, TIDE identified 99% of patients appropriate for contact using an asynchronous message through electronic medical records while reducing the number of patients reviewed by certified diabetes care and education specialists by 43%. For each of the 8 external data sets, simulation of the use of TIDE produced fewer than 0.25 personalized TIR flags per patient per review period. The use of TIDE to support telemedicine-based T1D care may facilitate sensitive and efficient guideline-based population health management.
View details for DOI 10.2196/27284
View details for PubMedID 35666570
Overcoming Barriers to Diabetes Technology in Youth with Type 1 Diabetes and Public Insurance: Cases and Call to Action.
Case reports in endocrinology
2022; 2022: 9911736
Advancements in diabetes technology such as continuous glucose monitoring (CGM), insulin pumps, and automated insulin delivery provide opportunities to improve glycemic control for youth with type 1 diabetes (T1D). However, diabetes technology use is lower in youth on public insurance, and this technology use gap is widening in the US. There is a significant need to develop effective interventions and policies to promote equitable care. The dual purpose of this case series is as follows: (1) describe success stories of the CGM Time in Range Program (CGM TIPs), which removed barriers for initiating CGM and provided asynchronous remote glucose monitoring for youth on public insurance, and (2) advocate for improving CGM coverage by public insurance. We describe a series of six youths with T1D and public insurance who obtained and sustained use of CGM with assistance from the program. Three youths had improved engagement with the care team while on CGM and the remote monitoring protocol, and three youths were able to leverage sustained CGM wear to obtain insurance coverage for automated insulin delivery systems. CGM TIPs helped these youths achieve lower hemoglobin A1c and improved time in range (TIR). Despite the successes, expansion of CGM TIPs is limited by stringent barriers for CGM approval and difficult postapproval patient workflows to receive shipments. These cases highlight the potential for combining diabetes technology and asynchronous remote monitoring to support continued use and provide education to improve glycemic control for youth with T1D on public insurance and the need to reduce barriers for obtaining CGM coverage by public insurance.
View details for DOI 10.1155/2022/9911736
View details for PubMedID 35273814
Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health.
OBJECTIVE: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review.RESEARCH DESIGN AND METHODS: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review.RESULTS: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2±0.20 to 1.3±0.24minutes per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n=58) have associated 8.8 percentage points (pp) (95% CI=0.6-16.9pp) greater time-in-range (70-180mg/dL) glucoses compared to 25 control patients who did not qualify at twelve months after T1D onset.CONCLUSIONS: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range. This article is protected by copyright. All rights reserved.
View details for DOI 10.1111/pedi.13256
View details for PubMedID 34374183
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