A new way to view CGM data that focuses on patterns, not perfection.
Abstract
Visualizing glucose data by the hour—rather than by day—can reveal clearer, more supportive insights into blood sugar patterns. By focusing on when changes occur, not just how much, this approach promotes understanding, reduces anxiety, and encourages progress over perfection.
Key Points
- Hourly View Adds Clarity: Highlights when glucose shifts happen, such as after meals or overnight.
- Flexible Range Options: Lets users switch between 70–180 mg/dL and 70–140 mg/dL views.
- Supportive Visual Design: Uses a green-blue color scale to promote curiosity, not judgment.
- Encourages Reflection: Focuses on patterns that can inform better self-care, without pressure.
- Personal Insight: Shows how understanding post-meal spikes led to more confidence and fewer surprises.
- Interactive Visualization Available: Readers can explore their own patterns using the linked CGM chart.
Introduction
Traditional Time in Range (TIR) charts often summarize glucose control as a single percentage per day, offering little insight into when glucose levels shift. This approach, while familiar, can obscure important patterns—such as whether fluctuations occur after meals or during sleep—and sometimes lead to unnecessary judgment about glycemic control.
Instead of summarizing daily control as a single number, an hour-by-hour view reveals when glucose levels shift—bringing patterns like post-meal spikes or overnight stability into focus.
By pairing dynamic thresholds with time-specific detail and reframing visual cues, this approach moves from static reporting to interactive exploration. The result is a clearer, more actionable view of glucose data—one that emphasizes understanding, not perfection.
Rethinking Glucose Visualizations
The old Time in Range (TIR) (70–180 mg/dL) and Time in Tight Range (TITR) (70–140 mg/dL) daily charts gave a snapshot of control—but not much context. These visualizations didn’t show when highs or lows happened or whether patterns repeated over time. Both have now been replaced by a single, more flexible visualization.
What the Old Charts Missed
Both charts lacked time-specific detail. A day could look "in range," but without knowing whether spikes happened after meals or overnight, it's hard to make informed changes. And while TITR in particular raised concerns about being too judgmental, even the standard TIR chart failed to provide deeper insight.
A Shift in Thinking
The shift came after listening to Natalie Bellini, DNP, on the Diabetes Dialogue podcast she co-hosts with Diana Isaacs, PharmD. Natalie’s comments about toggling between ranges while reviewing data with patients sparked an idea: instead of focusing on compliance, focus on patterns and possibilities.
She said, With diabetes, we don’t treat to what’s normal. We treat to what’s possible. [paraphrased] That stuck with me.
With diabetes, we don’t treat to what’s normal. We treat to what’s possible.
Introducing: Time in Range by Hour
The new visualization breaks glucose data into hourly segments and lets users switch between the 70–180 mg/dL and 70–140 mg/dL ranges. This offers a much more granular view of what’s happening and when.
For example, instead of learning that glucose was out of range for 20% of the day, we can now see that:
- Glucose remained in range overnight and early morning
- Post-meal spikes occurred in the afternoon
- Levels returned to target range by evening
This pattern fits what I expected and is far more actionable than a single daily percentage.
Explore the visualizations:
Continuous Glucose Monitor (CGM) Visualizations
A Better Use of Color
The new chart uses a reversed green-blue diverging color scale:
- Greener = more time in range
- Bluer = less time in range
This shifts the focus away from framing results as “bad” and toward highlighting areas for curiosity and possible improvement without judgment.
More Insight, Less Anxiety
Showing when glucose levels shift creates a more emotionally neutral way to review patterns by focusing on reflection, not perfection.
This is the draft section to add to the existing article before the Closing Thoughts section. Please evaluate.
Example Visualizations
These real-world examples illustrate the concepts discussed above.
- Time in Range by hour for individual days
- Multi-day aggregation across 7, 14, 30, and 90 days
- Coefficient of variation by hour to show stability versus variability
- How daily noise smooths out into consistent patterns over time
Prefer to explore examples directly? See the interactive visualizations below.
Hourly Time in Range Example Visualizations at Tableau Public
Guide to Example Visualizations
Closing Thoughts
The right chart doesn’t just show the data. It shows what the data means. Shifting from daily summaries to hourly trends, and from rigid targets to flexible insights, brings both clarity and compassion to glucose analysis.
Seeing when glucose rises after meals gave me fewer surprises and more confidence. Post-meal spikes are expected—and progress matters more than perfection. I hope this flexible, reflective approach helps others living with type 2 diabetes.
For more on the technical side of this approach, see the companion article at:
https://jcsanalytics.com/index.php?view=article&id=47:how-an-hour-by-hour-view-transforms-time-in-range-insights&catid=15
