Agreement Between Emergency Department Admission and Hospital Discharge Diagnoses; A Retrospective Observational Study.

INTRODUCTION

An accurate emergency department (ED) diagnosis is critically important for providing proper treatment during the so-called "Golden Hour." This study aimed to evaluate the agreement between admitting and discharge diagnoses in ED.

METHOD: This retrospective cross-sectional study was conducted over the course of 6 months in the emergency department (ED) of a tertiary care center. The main aim of the study was to evaluate the agreement between admission and hospital discharge diagnoses. The patients were categorized into two groups based on whether the admitting and discharge diagnoses were matched or mismatched. The reasons for diagnostic discrepancies, as well as their impact on patient outcomes, were assessed.

RESULTS

A total of 6812 cases with mean age of 43.2 ± 17.9 (range: 1-95 years) years were included (59.30% male). The admitting and discharge diagnoses were matched in 5585 (81.99%) cases and mismatched in 1227 (18.01%) cases (7.2% were completely unmatched). The proportion of mismatched diagnoses did not differ significantly between males and females (p = 0.0977). Mismatched diagnoses were significantly more common in 0-15 years age group (37.86%), and the lowest proportion was seen in patients aged 15-65 years (9.65%) (p < 0.001). The most frequent reason for diagnostic discrepancy was "writing chronic disease as discharge diagnosis (relabeling)," (37.08%). Other contributing factors included radiological tests after hospital admission (20.37%), physical examination findings (18.1%), additional laboratory tests (15.81%), and other causes (8.57%). A change in diagnosis impacted the clinical outcomes of 103 (8.39%) patients.

CONCLUSION

Diagnostic agreement between ED and discharge diagnoses was observed in 81.99% of cases, with a 7.2% complete mismatch rate. The most frequent causes were discharge relabeling and delayed investigations. These discrepancies had measurable impacts on management, hospital stay, and mortality.