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Traditional methods often miss pregnancy-related issues. We developed an algorithmic approach for abdominal pain assessment and pregnancy testing to address this. We conducted a Quality Improvement project involving problem identification, algorithm development, implementation, and evaluation. Pre- and post-intervention data revealed significant increases in pregnancy testing, notably in ages 15-25 (99.8% rise). Our algorithm elevates early pregnancy detection, minimizing missed diagnoses. 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