Applied clinical informatics · 2026
A Clinical Decision Support System to Optimize Antimicrobial Dosing in Patients with Renal Impairment.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Garcia-Souto Ana, Ibáñez-García Sara, Torroba-Sanz Beatriz, Domínguez-Chaparro Gonzalo, Nuñez-Nuñez Maria, Velasco-García Maria Eugenia, de la Rosa-Triviño Jose Luis, Herranz-Alonso Ana, Sanjurjo-Sáez Maria
Аннотация
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.
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.