Flash Glucose Monitoring System for People with Type 1 or Type 2 Diabetes: A Health Technology Assessment.
Bibliographic record
Abstract
BACKGROUND: People with diabetes manage their condition by monitoring the amount of glucose (a type of sugar) in their blood, typically using a method called self-monitoring of blood glucose. Flash glucose monitoring is another method of assessing glucose levels; it uses a sensor placed under the skin and a separate touchscreen reader device. We conducted a health technology assessment of flash glucose monitoring for people with type 1 or type 2 diabetes, which included an evaluation of effectiveness and safety, the budget impact of publicly funding flash glucose monitoring, and patient preferences and values. METHODS: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane risk-of-bias tool for randomized controlled trials and the Cochrane ROBINS-I tool for nonrandomized studies, and we assessed the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search, and we analyzed the net budget impact of publicly funding flash glucose monitoring in Ontario for people with type 1 diabetes and for people with type 2 diabetes requiring intensive insulin therapy who are eligible for coverage under the Ontario Drug Benefit program. To contextualize the potential value of flash glucose monitoring, we spoke with adults with diabetes and parents of children with diabetes. RESULTS: Six publications met the eligibility criteria for the clinical evidence review. Compared with self-monitoring of blood glucose, people who used flash glucose monitoring spent on average 1 hour more in the target glucose range (95% confidence interval [CI] 0.41-1.59) and 0.37 hours (22 minutes) less in a high glucose range (95% CI -0.69 to -0.05) (GRADE: Moderate). Among adults with well-controlled type 1 diabetes, flash glucose monitoring was more effective than self-monitoring of blood glucose in reducing glucose variability (GRADE: Moderate). Flash glucose monitoring was more effective than self-monitoring of blood glucose in reducing the average time spent in hypoglycemia (-0.47 h [95% CI -0.73 to -0.21]) and the average number of hypoglycemia events (-0.16 [95% CI -0.29 to -0.03]) among adults with type 2 diabetes requiring intensive insulin therapy (GRADE: Moderate). Our certainty in the evidence for the effectiveness of flash glucose monitoring for other clinical outcomes, such as quality of life and severe hypoglycemia events, is low or very low. We identified no studies on flash glucose monitoring that included pregnant people, people with diabetes who did not use insulin, or children younger than 13 years of age.We identified two studies for the economic evidence review: one cost analysis and one cost-utility analysis. The cost analysis study, conducted from the perspective of United Kingdom's National Health Service, found that flash glucose monitoring reduced costs when self-monitoring of blood glucose was performed 10 times daily but was more expensive when self-monitoring of blood glucose was performed 5.6 times daily. The cost-utility analysis had methodological limitations and was not applicable to the context of Ontario's health care system.Our 5-year budget impact analysis found that flash glucose monitoring may lead to a net budget increase ranging from $14.6 million ($2.9 million for type 1 diabetes and $11.7 million for type 2 diabetes) in year 1, at an uptake rate of 15%, to $38.6 million ($7.7 million for type 1 diabetes and $30.9 million for type 2 diabetes) in year 5, at an uptake rate of 35%. In this analysis, we assumed that people with type 1 diabetes who self-monitor their blood glucose levels would perform six blood glucose tests daily and that people with type 2 diabetes would perform four blood glucose tests daily. For people switching from self-monitoring of blood glucose using the maximum number of blood glucose test strips for reimbursement (3,000 strips yearly) to flash glucose monitoring, the net budget impact of using flash glucose monitoring is likely to be small.Adults with diabetes and parents of children with diabetes with whom we spoke reported positively on their experiences with flash glucose monitoring, reporting they believed that flash glucose monitoring helped them control their blood glucose levels, resulting in physical, social, and emotional benefits. The cost of flash glucose monitoring was the largest barrier to its use. CONCLUSIONS: Based on an assessment of several glycemic outcomes, moderate-quality evidence shows that flash glucose monitoring improves diabetes management among adults with well-controlled type 1 diabetes and adults with type 2 diabetes requiring intensive insulin therapy. We estimate that publicly funding flash glucose monitoring in Ontario for people with type 1 diabetes and for people with type 2 diabetes requiring intensive insulin therapy who are eligible for coverage under the Ontario Drug Benefit program would result in additional costs of between $14.6 million and $38.6 million annually over the next 5 years. Adults with diabetes and parents of children with diabetes with whom we spoke reported that flash glucose monitoring helped them or their children control their blood glucose levels, resulting in physical, social, and emotional benefits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".