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A Lab Value Carries the Decision to Measure It
A formal result shows why physiology and care process cannot generally be separated from one electronic-health-record dataset.
Summary
A formal result shows why physiology and care process cannot generally be separated from one electronic-health-record dataset.
Electronic health records mix a patient's condition with the clinical process that determines what gets measured. This paper proves that a single dataset cannot generally divide the information carried by laboratory values and ordering decisions when untested values are undefined. Cross-site outcome invariance is a falsifiable implication under added assumptions, but observationally equivalent models can disagree about the underlying biology. A worked example produces a 9.6-percentage-point site gap with the biological mechanism unchanged. Identification can return with universal testing or specially structured repeated measurements; absent that, cross-site results test a joint hypothesis, not physiology alone.
Why it matters
A formal result shows why physiology and care process cannot generally be separated from one electronic-health-record dataset.
Limits and context
- This paper proves that a single dataset cannot generally divide the information carried by laboratory values and ordering decisions when untested values are undefined.
- Identification can return with universal testing or specially structured repeated measurements; absent that, cross-site results test a joint hypothesis, not physiology alone.
Key claims
A formal result shows why physiology and care process cannot generally be separated from one electronic-health-record dataset.
Qualification: This paper proves that a single dataset cannot generally divide the information carried by laboratory values and ordering decisions when untested values are undefined.
Evidence: source-2026-11-10-005
Sources
- arXiv preprint 2611.11726, original v1arXiv · primary research
Corrections
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