Enhancing pharmaceutical decision support system: evaluating antithrombotic-focused algorithms for addressing drug-related problems.

OBJECTIVES: To evaluate the efficacy of integrating antithrombotic-focused pharmaceutical algorithms (PAs) into a pharmaceutical decision support system (PDSS) for detecting drug-related problems (DRPs) and facilitating pharmaceutical interventions. METHODS: A set of 26 PAs (12.4%) out of a total of 210 were created to model patient situations involving antithrombotics, and their contributions were compared with the entire PDSS system.The observational prospective study was conducted between November 2019 and June 2023 in two health facilities with 1700 beds. Pharmacists, who followed a DRP resolution strategy to support human supervision, analysed alerts generated by these encoded PAs. They registered their interventions and the acceptance by physicians. RESULTS: From 3290 alerts analysed targeting antithrombotics, the pharmacists issued 1170 interventions of which 676 (57.8%) were accepted by physicians. With the 184 other PAs, from 9484 alerts the pharmacists issued 3341 interventions of which 1785 were accepted (53.4%).Results indicate that the detection of DRPs related to antithrombotics usage represents a high proportion of those detected by the PDSS, highlighting the importance of incorporating tailored PA elements at the modelling stage. CONCLUSIONS: The system evolves alongside the physiological changes associated to the patient situations, adapts the alerts and complements the current care. Therefore, we recommend that all PDSS should integrate specific algorithms targeting DRPs associated with antithrombotics to enhance pharmaceutical interventions and improve patient safety.

Pharmaceutical algorithms set in a real time clinical decision support targeting high-alert medications applied to pharmaceutical analysis.

BACKGROUND: Pharmaceutical analysis of the prescription has to prop up the quality of patients' medication management in a context of medication's risk acculturation. But this activity remains highly variable. Medication-related clinical decision support may succeed in reducing adverse drug events and healthcare costs. PURPOSE: This study aims to present AVICENNE as a real time medication-related clinical decision support (rt-CDS) applied to pharmaceutical analysis and its ability to detect Drug related problems (DRP) consecutively resolved by pharmacists. Basic procedures A Medication-related rt-CDS is created by integrating the software PharmaClass® (Keenturtle), 5 health data streams on the patient and Pharmaceutical algorithms (PA). PA are created by modeling the pharmaceutical experiment about DRP and the thread of their criticality. They are partially encoded as computerized rules in Pharmaclass® allowing alerts' issue. An observational prospective study is conducted during 9-months among 1000 beds in 2 health facilities. The first step is to identify alerts as DRP; their resolution follows with clear guidelines worked out for the pharmaceutical analysis. A basis on predictive positive values (PPV) of the PA is being built today helping to know the performance of DRP detection and resolution. Main findings 71 PA are encoded as rules into Pharmaclass®: 40 targeted serious adverse drug events. 1508 alerts are analyzed by pharmacists. Among them 921 DRPs were characterized and 540 pharmaceutical interventions transmitted of which 219 were accepted by prescribers. Three PPV are defined depending on software, pharmacist and patient. Principal conclusion Clinical pharmacy societies should host, share and update a national corpus of PA and exploit its educational interest.

Intravenous single administration of amiodarone and breastfeeding.

Amiodarone treatment is contraindicated during breastfeeding. As the regional pharmacovigilance centre, we were contacted for information relative to the possibility of breastfeeding after single intravenous administration of 450 mg amiodarone to a breastfeeding woman. A monitoring of amiodarone concentration in plasma and milk was performed in the mother. At day 4, milk concentration of amiodarone reached a peak (233 µg/L) and milk to plasma ratio was determined to 3.5. Milk concentration was still detectable at day 10 (132 µg/L). The maximal relative infant dose was estimated to be 0.6% of the maternal weight-adjusted dosage, corresponding to 0.18% of the usual posology used in children by parenteral route. The review of the literature retrieved one publication suggesting that a single intravenous administration of 150 mg of amiodarone to a mother represents a negligible infant risk based on low breast milk concentration. The French National Pharmacovigilance database query did not disclose any case of side effects during breastfeeding after a single dose of amiodarone. A very limited exposition of breastfed newborns to amiodarone, as well as a low risk of side effects, is expected after a single administration of amiodarone to their mothers.