Threshold Approach to Clinical Decision Making (Pauker-Kassirer)
This method helps doctors decide when to order a test, start treatment, or wait, based on how likely a patient is to have a disease and the risks and benefits of testing and treatment.
At a glance
Use when
Making diagnostic and treatment decisions under uncertainty, especially when test risks or treatment harms are significant
Avoid when
When key parameters (e.g., test accuracy, treatment benefit) are unknown or highly uncertain
Inputs
Pretest probability of disease, test sensitivity and specificity, treatment benefit, treatment risk or harm
Outputs
Testing threshold, test-treatment threshold, recommended clinical action (test, treat, or withhold)
How it works
Using decision analysis, the method defines two probability thresholds: a 'testing threshold' below which treatment is withheld, and a 'test-treatment threshold' above which treatment is given without further testing. Diagnostic testing is recommended only when the probability of disease lies between these two thresholds. Thresholds are calculated using test sensitivity, specificity, treatment benefit, and treatment risk.
- HTA domains
- Clinical Effectiveness, Organisational aspects, Patient and Social Aspects
- Assumptions
- Test and treatment effects are independent; utilities (benefits/harms) are quantifiable; clinician has a reasonable estimate of disease probability
- Strengths
- Provides a structured, quantitative framework for clinical decisions; clarifies trade-offs between testing and treatment; improves decision transparency
- Limitations
- Requires accurate estimates of test performance and treatment outcomes; may be complex for bedside use without tools; assumes linear utility scaling
- Also known as
- Pauker-Kassirer method, Threshold model, Testing-treatment threshold model
Questions this answers
References & sources
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