A Clinical Decision Support System to Optimize Antimicrobial Dosing in Patients with Renal Impairment.

OBJECTIVE

This study aimed to develop and validate a targeted set of clinical rules embedded within a clinical decision support system to support safer antimicrobial dosing in patients with impaired renal function and to assist antimicrobial stewardship activities.

METHODS

Clinical rules for renal dose adjustment were developed through a structured literature review and consensus by a multidisciplinary team. The rules were implemented within a clinical decision support system integrated with electronic prescribing, electronic health records, and laboratory data, through HL7 messaging and supported by a NoSQL database architecture. A 9-week pilot validation study was conducted in a tertiary care hospital, during which alerts were reviewed by pharmacists. System effectiveness was assessed by alert review rates, pharmacist interventions, physician acceptance, and positive predictive value.

RESULTS

A total of 58 clinical rules were implemented. During the validation period, 409 alerts were generated for 249 patients, of which 352 alerts (86%) were reviewed by pharmacists. Pharmacist interventions were performed for 190 alerts (54%). Among 156 assessable interventions, 111 (71%) were accepted by physicians, resulting in antimicrobial dose modifications. The overall positive predictive value of the clinical rule set was 0.32. Acceptance rates varied across clinical settings, ranging from 57% in surgical units to 80% in the emergency department.

CONCLUSION

Implementation of a consensus-based bundle of clinical rules within a clinical decision support system generated actionable renal dosing alerts and supported pharmacist-led interventions with high prescriber acceptance. This informatics-enabled approach supports safer antimicrobial dosing decisions in patients with renal impairment and may help reduce the risk of medication-related harm.