Indications-based prescribing is a medication ordering system in which a clinician selects an indication, and then the electronic health record (EHR) suggests an appropriate medication regimen. This approach was shown to significantly decrease medication ordering errors in a prototype environment. However, the effect of indications-based prescribing on preventing ordering errors has not been rigorously evaluated in a real-world healthcare setting. Antibiotics are the medication class most likely to contain ordering errors, which can lead to significant patient harm. At NewYork-Presbyterian (NYP) a robust antimicrobial indication-based order set was developed to help clinicians identify the appropriate antibiotic, dose, frequency, and duration, based on type of infection and patient-specific characteristics, but it is not widely used. The investigators propose a randomized controlled trial to assess the effectiveness of this indications-based order set for reducing antimicrobial ordering errors.

Inclusion Criteria:

All providers placing inpatient orders on adult patients.

Exclusion Criteria:

Providers placing orders on patients who were ordered for antibiotics >24 hours in the past 72 hours and/or patients with positive cultures during that admission, and/or placing an order from the order set.