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Rules-Based Electronic Triggers Effectively ID Missed Opportunities in Diagnosis

By Lori Solomon HealthDay Reporter

Medically reviewed by Carmen Pope, BPharm. Last updated on Dec 5, 2024.

via HealthDay

THURSDAY, Dec. 5, 2024 -- Rules-based electronic triggers (e-triggers) are useful for post hoc detection of missed opportunities in diagnosis (MODs) in emergency department visits, according to a study published online Dec. 2 in JAMA Internal Medicine.

Viralkumar Vaghani, M.B.B.S., from the Baylor College of Medicine in Houston, and colleagues assessed the performance of a portfolio of e-triggers for identifying MODs in emergency departments. The analysis included treat-and-release emergency department visits at 1,321 Veterans Affairs health care sites.

The researchers found that 203 trigger-positive records were identified for high-risk stroke, 1,981 for symptom-disease dyads, 170 for high-risk abdominal pain, 116,785 for unexpected emergency department return, 14,879 for unexpected hospital return, and 2,090 for abnormal test results not followed up. From 625 randomly selected patient records, 47 MODs (positive predictive values [PPV], 47.0 percent) were identified for stroke, 31 MODs (PPV, 25.8 percent) for abdominal pain, 11 MODs (PPV, 11.0 percent) for emergency department returns, 23 MODs (PPV, 23.0 percent) for hospital returns, 18 MODs (PPV, 18.0 percent) for symptom-disease dyads, and 55 MODs (PPV, 52.4 percent) for test results. The most common diagnostic process breakdown involved the patient-clinician encounter for 108 of 130 MODs (excluding MODs related to the test result e-trigger). For 20 of 185 total MODs, patients experienced severe harm (10.8 percent), and 54 patients experienced moderate harm (29.2 percent).

"Interventions to target emergency department work system factors are urgently needed to support patient-clinician encounters and minimize harm from diagnostic errors," the authors write.

One author disclosed ties to the health information technology industry.

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Disclaimer: Statistical data in medical articles provide general trends and do not pertain to individuals. Individual factors can vary greatly. Always seek personalized medical advice for individual healthcare decisions.

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