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.

Clinical risk assessment of modelled situations in a pharmaceutical decision support system: a modified e-Delphi exploratory study.

BACKGROUND: Pharmaceutical decision support systems (PDSSs) use reasoning software to match patient data to modelled situations likely to cause drug-related problems (DRPs) or adverse drug events. To aid decision-making, modelled situations must be linked to well-defined systemic clinical risks. AIM: To obtain expert consensus on the level of clinical risk for patients associated with each modelled situation that could be addressed using a PDSS. METHOD: A two-round e-Delphi survey was conducted from February to April 2022, involving 20 experts from four French-speaking countries. Participants had to rate modelled situations on two five-point Likert scales, assessing the likelihood of clinical consequences and their severity. The degree of consensus was determined as the proportion of participants providing risk scores in line with the median. The combined median scores for likelihood and severity provided the level of risk according to the Clinical Risk Situation for Patients (CRiSP) scale, formalized via validated tools. RESULTS: The expert panel achieved consensus (≥ 75% agreement) on 48 out of 52 modelled clinical situations. Among these, 45 were categorized as high or extreme risk. The most common DRP identified was overdosing, accounting for 22% of cases. Furthermore, DRPs involving cardiovascular, psychiatric, and endocrinological drug classes were prevalent, constituting 45, 13, and 9% of cases, respectively. CONCLUSION: Through consensus, our study identified 45 modelled clinical situations associated with high or extreme risks. This study highlights the interest of using PDSSs to prevent harm in patients and, on a large scale, document the impact of the pharmacist in preventing, intercepting and managing iatrogenic drug risk.

Magazines in waiting areas of hospital: a forgotten microbial reservoir?

The hospital environment is a potential source of microbial contamination. Thus, the magazines in hospital's waiting rooms are handled by patients and visitors whose health and hygiene conditions can vary widely. In this context, we had measured the microbial load on the surface of magazines. Fifteen magazines from 5 waiting rooms of hospital are sampled by agar prints at the areas taken in hand. The agar plates are incubated at 30̊C for 72h. The colonies are counted and identified by MALDI-TOF mass spectrometry (Vitek®-MS). The extraction efficiency of bacteria by the agar print method on the magazines is calculated. All the samples highlight a varied bacterial flora: 32CFU/agar in mean. Isolated bacteria come principally from the skin flora (>60%), but we also isolate potentially pathogenic micro-organisme like S. aureus, E. faecalis, A. viridans and Aspergillus sp. as well as oropharyngeal flora bacteria like A. iwolfii and M. osloensis and fecal like B. stercoris. Some species rarely described in hospital are also isolated such as P. yeei or K. sedentarius. The extraction efficiency of the sampling method on a magazine is 36%. Our study, which is the first to be interested in the bacterial contamination of magazines in hospital, could make them consider as microbial reservoir to be controlled, especially for the most fragile patients. New bacterial identification techniques as the MALDI-TOF allow to reveal the presence of rarely described and often underestimated species.