Improving empirical antibiotic treatment: prospective, nonintervention testing of a decision support system

Abstract

Objectives. Develop a problem-orientated and databased 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 ϭ 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 Ͻ 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 gramnegative 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.

A causal probabilistic network for optimal treatment of bacterial infections

“…Databases that are available to us include data on approximately 4,000 bacteremic patients seen at Beilinson Campus (Petah-Tiqva, Israel) [6] and about 1,000 bacteremic patients detected in the County of Northern Jutland, Denmark [8]; about 1,400 patients suspected of harboring a moderate to severe bacterial infection [10]; about 400 young women with urinary complaints [27], [28]; and 250 patients with urinary tract infections [29]. The details on each patient included demographic data, underlying disorders, presentation of infection, pathogen and its susceptibility to antibiotics, treatment, and outcome.…”

“…The main determinant of the pathogen is the site of infection (e.g., urinary tract or the lungs), in addition to other factors, such as the place of acquisition of the pathogen causing the infection (hospital or community), defects in the patient's defense mechanisms, etc. [10]. The patterns of susceptibility to antibiotics differ from region to region and from hospital to hospital.…”

“…The DSS outperformed the attending physicians at guessing the pathogen of the infection and its susceptibility to antibiotics. It reduced the percentage of inappropriate treatments by half, while prescribing fewer broad-spectrum and costly antibiotics [10].…”

“…Nevertheless, it seemed likely that better use of knowledge and data through a computerized DSS can improve the management of patients with severe bacterial infections, while reducing the use of broad-spectrum and costly antibiotics [10], [18], [19]. To obviate the problems of the previous DSSs, we decided to build a normative system, where a causal probabilistic network (CPN) was used to calculate the probability distributions for the relevant output variables and decision theory was used to balance the therapeutic benefit of antibiotic therapy against the detriments associated with antibiotic drugs.…”

Management of Intra-Abdominal Infections

“…Computerized decision support programs and computer-assisted implementation methods have been found to be useful in many studies of antibiotic therapy [219][220][221]. In one cluster randomized trial of three hospitals from Israel, Germany, and Italy, a computerized decision support system significantly increased the rate of appropriate empirical antibiotic treatment of infections, with an adjusted odd ratio of 1.48 [222].…”