What does this research mean for the field?

Assuming fixed sensitivity and specificity for continuous diagnostic tests in clinical threshold models creates an undertesting bias that artificially narrows the testing window and leads to systematic underuse of diagnostic testing. Novelty: ClaimNovelty.CONTRADICTORY. Consensus alignment: ConsensusAlignment.CHALLENGES_CONSENSUS.

What question did this study set out to answer?

To evaluate how assuming fixed sensitivity and specificity in threshold models affects clinical decision-making for continuous and ordinal diagnostic tests.

August 19, 2026Medical Decision MakingOpen Access

The Undertesting Bias in Clinical Decision Making: The Role of Test Dichotomization

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Authors

MMMurat C. Mungan

Discussion

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Overview

Theoretical decision analysis demonstrates test dichotomization narrows testing windows in clinical decision making, suggesting continuous test thresholds prevent undertesting bias.

Key Points

To evaluate how assuming fixed sensitivity and specificity in threshold models affects clinical decision-making for continuous and ordinal diagnostic tests.
Analyzed classic Pauker-Kassirer threshold decision models that divide pretest probabilities into no-test, test, and treat action zones.
Evaluated the mathematical relationship between pretest probability and optimal sensitivity-specificity cutoffs for continuous and ordinal diagnostic tests.
Treating continuous test outputs as fixed binary variables inflates testing thresholds and deflates test-treatment thresholds.
This distortion artificially narrows the optimal testing window, producing a systematic undertesting bias that undervalues diagnostic testing.

Cite This Study

Murat C. Mungan (2026) studied this question.

synapsesocial.com/papers/6a8562eb03308d306e2d5f42 https://doi.org/10.1177/0272989x261471178

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August 19, 2026Medical Decision MakingOpen Access

The Undertesting Bias in Clinical Decision Making: The Role of Test Dichotomization

View Full Paper

Ask AI

Bookmark

Authors

MMMurat C. Mungan

Discussion

Member takes

Overview

Theoretical decision analysis demonstrates test dichotomization narrows testing windows in clinical decision making, suggesting continuous test thresholds prevent undertesting bias.

Key Points

To evaluate how assuming fixed sensitivity and specificity in threshold models affects clinical decision-making for continuous and ordinal diagnostic tests.
Analyzed classic Pauker-Kassirer threshold decision models that divide pretest probabilities into no-test, test, and treat action zones.
Evaluated the mathematical relationship between pretest probability and optimal sensitivity-specificity cutoffs for continuous and ordinal diagnostic tests.
Treating continuous test outputs as fixed binary variables inflates testing thresholds and deflates test-treatment thresholds.
This distortion artificially narrows the optimal testing window, producing a systematic undertesting bias that undervalues diagnostic testing.

Cite This Study

Murat C. Mungan (2026) studied this question.

synapsesocial.com/papers/6a8562eb03308d306e2d5f42 https://doi.org/10.1177/0272989x261471178

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