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Did you notice the deceptive and distorted time (X) axis? The time axis is non-linear / irregularly spaced. Early years (1966–1995) are heavily compressed, but later years (especially ~2015–2024) are significantly stretched out. Note that this is Not logarithmic scaling on the time axis. A true log time axis would compress recent years (the opposite of what’s happening here).

This kind of manipulation is common in misleading charts for a few reasons:

To downplay explosive recent growth. By squeezing the early decades and expanding the last 10–15 years, the steep upward curve in the 2010s–2020s looks gentler and more "gradual" than it really is. On a uniform axis (as in the corrected version I show below), the acceleration after ~2010–2015 becomes much more visually dramatic.
To fit more data points in recent years. The chart labels many specific years after 2000 (2001, 2003, 2005, etc.), which requires more horizontal space. Designers sometimes unevenly space the axis instead of using a clean linear scale + fewer labels.
Visual deception / cherry-picking presentation. People (advocates, government reports, media, etc.) sometimes use this trick to make long-term trends look less alarming. Medicaid spending grew extremely slowly for decades, then accelerated sharply — especially after major policy changes like the Affordable Care Act expansion and post-COVID effects. A uniform axis makes that "hockey stick" shape obvious.

The irony is this article is trying to make the case for the horrific explosive growth of Medicaid. The author should have used a linear time axis to show the explosion of spending:

What really jumps out is that red exponential regression curve fit line. Talk about "unsustainable"!