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Sequential test selection in the analysis of abdominal pain
F Castro1, L P Caccamo, K J Carter
1Youngstown State University, St. Elizabeth Hospital Medical Center, Ohio, USA.
Summary
This study introduces a novel decision-making model combining physician judgment and probability analysis for sequential diagnostic testing. It optimizes test selection to improve diagnostic accuracy and patient outcomes.
Area of Science:
- Medical Informatics
- Decision Analysis
- Diagnostic Management
Background:
- Physician decision-making in diagnosis often relies on ambiguous clinical information.
- Existing analytical models struggle to incorporate subjective physician judgment.
- Sequential diagnostic testing requires an optimal strategy for test selection.
Observation:
- A patient with upper abdominal pain, not requiring immediate surgery, presented a diagnostic challenge.
- Four diagnostic tests were considered: upper gastrointestinal series (GI), abdominal ultrasonography (US), abdominal computed tomography (CT), and upper gastrointestinal endoscopy (END).
- Criteria for test selection included minimizing risk, discomfort, and cost, while maximizing diagnostic capability.
Findings:
- The Analytic Hierarchy Process (AHP) model integrated physician judgment with probability analysis.
- AHP identified the upper GI series as the optimal first diagnostic test.
- Subsequent Bayesian analysis and reiterated AHP identified abdominal ultrasonography as the optimal second test.
Implications:
- This model enhances diagnostic accuracy by incorporating physician judgment into probabilistic analysis.
- It provides a structured approach for sequential diagnostic test ordering.
- The methodology offers a flexible framework adaptable to evolving clinical information and preferences.