Objectives: Develop a problem-orientated and data-based decision support system (DSS) to improve empirical antibiotic treatment, and compare the performance of the system to that of the physician.
Design: The DSS was tested in a prospective, noninterventional, comparative cohort study.
Setting: University hospital in Israel.
Subjects: Consecutive patients (n = 496) in four departments of internal medicine suspected of harboring a moderate to severe bacterial infection.
Interventions: None.
Main outcome measures: The percentage of appropriate empirical antibiotic treatments.
Results: Out of 496 patients included in the study, 219 had positive cultures or serological tests. The physicians prescribed inappropriate empirical antibiotic treatment in 91 of 219 patients (42%); whilst the recommendations of the system were inappropriate in 50 patients (23%) (P < 0.05). Superfluous treatment was prescribed in 15% of patients by the physician, and in 11% by the system. Out of the 91 patients given inappropriate treatment by the physician, the DSS advised treatment to which the pathogens were susceptible in 61 patients. The advantage of the DSS over the physician was most evident in multiresistant gram-negative isolates, enterococci and Staphylococcus aureus. Out of the 277 patients with negative cultures, the DSS advised narrower-spectrum antibiotic treatment than prescribed by the physicians in 27% of patients, and broader-spectrum in 13%.
Conclusion: A problem-orientated, data-based DSS outperformed physicians in the choice of appropriate empirical antibiotic treatment, and recommended less broad-spectrum antibiotics.