Patient and physician predictors of patient receipt of therapies recommended by a computerized decision support system when initially prescribed broad-spectrum antibiotics: a cohort study.
OBJECTIVE
Antibiotic computerized decision support systems (CDSSs) were developed to guide antibiotic decisions, yet prescriptions of CDSS-recommended antibiotics have remained low. Our aim was to identify predictors of patients' receipt of empiric antibiotic therapies recommended by a CDSS when the prescribing physician had an initial preference for using broad-spectrum antibiotics.


METHODS
We conducted a prospective cohort study in a 1 500-bed tertiary-care hospital in Singapore. We included all patients admitted from October 1, 2011 through September 30, 2012, who were prescribed piperacillin-tazobactam or carbapenem for empiric therapy and auto-triggered to receive antibiotic recommendations by the in-house antibiotic CDSS. Relevant data on the patient, prescribing and attending physicians were collected via electronic linkages of medical records and administrative databases. To account for clustering, we used multilevel logistic regression models to explore factors associated with receipt of CDSS-recommended antibiotic therapy.


RESULTS
One-quarter of the 1 886 patients received CDSS-recommended antibiotics. More patients treated for pneumonia (33.2%) than sepsis (12.1%) and urinary tract infections (7.1%) received CDSS-recommended antibiotic therapies. The prescribing physician - but not the attending physician or clinical specialty - accounted for some (13.3%) of the variation. Prior hospitalization (odds ratio [OR] 1.32, 95% CI, 1.01-1.71), presumed pneumonia (OR 6.77, 95% CI, 3.28-13.99), intensive care unit (ICU) admission (OR 0.38, 95% CI, 0.21-0.66), and renal impairment (OR 0.70, 95% CI, 0.52-0.93) were factors associated with patients' receipt of CDSS-recommended antibiotic therapies.


CONCLUSIONS
We observed that ICU admission and renal impairment were negative predictors of patients' receipt of CDSS-recommended antibiotic therapies. Patients admitted to ICU and those with renal impairment might have more complex clinical conditions that require a physician's assessment in addition to antibiotic CDSS.
Department of Clinical Epidemiology, Institute of Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, United States Angela_Chow@ttsh.com.sg.
Angela L P
AL
Chow
Department of Infectious Diseases, Institute of Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
David C
DC
Lye
Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, United States Center for Health Policy Research, University of California, Los Angeles (UCLA), Los Angeles, United States.
Onyebuchi A
OA
Arah
D000046:Academic Medical Centers; D000368:Aged; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D015780:Carbapenems / Q000627:therapeutic use; D015331:Cohort Studies; D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D004363:Drug Utilization; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D057970:Inappropriate Prescribing; D007362:Intensive Care Units; D007674:Kidney Diseases; D008297:Male; D008875:Middle Aged; D010343:Patient Admission; D010397:Penicillanic Acid / Q000031:analogs & derivatives / Q000627:therapeutic use; D010878:Piperacillin / Q000627:therapeutic use; D000077725:Piperacillin, Tazobactam Drug Combination; D010818:Practice Patterns, Physicians'; D012846:Singapore
D000900:Anti-Bacterial Agents; D015780:Carbapenems; D000077725:Piperacillin, Tazobactam Drug Combination; D010397:Penicillanic Acid; D010878:Piperacillin
antibiotic prescribing; antibiotic resistance; decision support system; empiric therapy; patient factors; physician factors