Correlation between antifungal clinical practices and a new clinical decision support system ANTIFON-CLIC® for the treatment of invasive candidiasis: a retrospective multicentre study.

BACKGROUND: Invasive candidiasis is still recognized as a major cause of morbidity and mortality. To support clinicians in the optimal use of antifungals for the treatment of invasive candidiasis, a computerized decision support system (CDSS) was developed based on institutional guidelines. OBJECTIVES: To evaluate the correlation of this newly developed CDSS with clinical practices, we set-up a retrospective multicentre cohort study with the aim of providing the concordance rate between the CDSS recommendation and the medical prescription (NCT05656157). PATIENTS AND METHODS: Adult patients who received caspofungin or fluconazole for the treatment of an invasive candidiasis were included. The analysis of factors associated with concordance was performed using mixed logistic regression models with department as a random effect. RESULTS: From March to November 2022, 190 patients were included from three centres and eight departments: 70 patients from centre A, 84 from centre B and 36 from centre C. Overall, 100 patients received caspofungin and 90 received fluconazole, mostly (59%; 112/190) for empirical/pre-emptive treatment. The overall percentage of concordance between the CDSS and medical prescriptions was 91% (173/190) (confidence interval 95%: 82%-96%). No significant difference in concordance was observed considering the centres (P > 0.99), the department of inclusion (P = 0.968), the antifungal treatment (P = 0.656) or the indication of treatment (P = 0.997). In most cases of discordance (n = 13/17, 76%), the CDSS recommended fluconazole whereas caspofungin was prescribed. The clinical usability evaluated by five clinicians was satisfactory. CONCLUSIONS: Our results demonstrated the high correlation between current antifungal clinical practice and this user-friendly and institutional guidelines-based CDSS.

Unlicensed/Off-Label Drug Prescriptions at Hospital Discharge in Children: An Observational Study Using Routinely Collected Health Data.

BACKGROUND: Unlicensed and off-label (UL/OL) prescriptions have been associated with an increased risk of drug-related problems. Data of their prevalence at hospital discharge remain insufficient. We aimed to describe the prevalence of UL/OL drugs in outpatient prescriptions at discharge in children. METHODS: We conducted a retrospective study using the routinely collected health data of children at discharge from 2014 to 2016. The primary reference source for determining licensed labelling was the summaries of product characteristics (SPCs) in a French industry-independent formulary named Thériaque. We described the characteristics of UL/OL prescriptions at discharge and looked for predictors of UL/OL prescriptions. RESULTS: We included 2536 prescriptions of 479 children. Licensed, OL, and UL prescriptions accounted for 58.6% (95% CI: 56.7-60.5), 39.2% (95% CI: 37.3-41.1), and 2.3% (95% CI: 1.7-2.9), respectively. A total of 323 (74%) children received at least one UL/OL drug. Among the licensed drugs, bronchodilators (8.8%) and analgesics (8.6%), and among the OL drugs, antibiotics (2.8%), were the most prescribed. The younger age of the children and higher number of drugs they received increased the probability of UL/OL prescriptions (unadjusted p-value of ≤0.05). CONCLUSION: The prevalence of UL/OL prescriptions is about 40% at discharge from a pediatric university hospital in France.

Integrated clinical pharmacy activities into the pediatric kidney graft pathway / Activités de pharmacie clinique intégrées dans le parcours du patient de greffe rénale pédiatrique

The pediatric renal graft pathway is at risk of care discontinuation, even though therapeutic adherence is essential. The objective is to evaluate the integration of clinical pharmacy activities into this care pathway. This feasibility study is divided into three stages: structuring, implementing and evaluation. In pre-transplant, immediate and remote post-transplant, interviews were proposed as well as the pharmaceutical analysis of medication prescriptions. In 8 months duration, 32 patients were included. All patients included in pre-transplant and immediate post-transplant benefited from the activities. At M0, all the prescriptions analyzed resulted in at least one problem detected. Half of the transplanted patients benefited from M1 maintenance, one patient from M3 maintenance and no M6 follow-up could be carried out. This work concludes with the good feasibility and integration of clinical pharmacy activities within the care pathway.

Le parcours de greffe rénale pédiatrique est à risque de rupture de soins car les patients sont polymédiqués alors même que l'adhésion thérapeutique est essentielle. L'objectif est d'évaluer l'intégration d'activités de pharmacie clinique dans ce parcours de soins. Cette étude de faisabilité se décline en trois étapes : structuration, mise en œuvre et évaluation. En pré-greffe, post-greffe immédiate et post-greffe à distance, des entretiens ont été proposés ainsi que l'analyse pharmaceutique des prescriptions médicamenteuses. En huit mois, 32 patients ont été inclus. Tous les patients inclus en pré-greffe et en post-greffe immédiate ont bénéficié des activités. À M0, toutes les prescriptions analysées ont abouti à au moins un problème détecté. La moitié des patients greffés ont bénéficié de l'entretien à M1, un patient de l'entretien à M3 et aucun suivi à M6 n'a pu être réalisé. Ce travail conclut à la bonne faisabilité et intégration des activités de pharmacie clinique au sein du parcours de soins.

Leveraging National Claims and Hospital Big Data: Cohort Study on a Statin-Drug Interaction Use Case.

BACKGROUND: Linking different sources of medical data is a promising approach to analyze care trajectories. The aim of the INSHARE (Integrating and Sharing Health Big Data for Research) project was to provide the blueprint for a technological platform that facilitates integration, sharing, and reuse of data from 2 sources: the clinical data warehouse (CDW) of the Rennes academic hospital, called eHOP (entrepôt Hôpital), and a data set extracted from the French national claim data warehouse (Système National des Données de Santé [SNDS]). OBJECTIVE: This study aims to demonstrate how the INSHARE platform can support big data analytic tasks in the health field using a pharmacovigilance use case based on statin consumption and statin-drug interactions. METHODS: A Spark distributed cluster-computing framework was used for the record linkage procedure and all analyses. A semideterministic record linkage method based on the common variables between the chosen data sources was developed to identify all patients discharged after at least one hospital stay at the Rennes academic hospital between 2015 and 2017. The use-case study focused on a cohort of patients treated with statins prescribed by their general practitioner or during their hospital stay. RESULTS: The whole process (record linkage procedure and use-case analyses) required 88 minutes. Of the 161,532 and 164,316 patients from the SNDS and eHOP CDW data sets, respectively, 159,495 patients were successfully linked (98.74% and 97.07% of patients from SNDS and eHOP CDW, respectively). Of the 16,806 patients with at least one statin delivery, 8293 patients started the consumption before and continued during the hospital stay, 6382 patients stopped statin consumption at hospital admission, and 2131 patients initiated statins in hospital. Statin-drug interactions occurred more frequently during hospitalization than in the community (3800/10,424, 36.45% and 3253/14,675, 22.17%, respectively; P<.001). Only 121 patients had the most severe level of statin-drug interaction. Hospital stay burden (length of stay and in-hospital mortality) was more severe in patients with statin-drug interactions during hospitalization. CONCLUSIONS: This study demonstrates the added value of combining and reusing clinical and claim data to provide large-scale measures of drug-drug interaction prevalence and care pathways outside hospitals. It builds a path to move the current health care system toward a Learning Health System using knowledge generated from research on real-world health data.

A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks. MATERIALS AND METHODS: Data from electronic health records were collated over a period of 18 months. Inferred scores at a patient level (probability of a patient's set of active orders to require a pharmacist review) were calculated using a hybrid approach (machine learning and a rule-based expert system). A clinical pharmacist analyzed randomly selected prescription orders over a 2-week period to corroborate our findings. Predicted scores were compared with the pharmacist's review using the area under the receiving-operating characteristic curve and area under the precision-recall curve. These metrics were compared with existing tools: computerized alerts generated by a clinical decision support (CDS) system and a literature-based multicriteria query prioritization technique. Data from 10 716 individual patients (133 179 prescription orders) were used to train the algorithm on the basis of 25 features in a development dataset. RESULTS: While the pharmacist analyzed 412 individual patients (3364 prescription orders) in an independent validation dataset, the areas under the receiving-operating characteristic and precision-recall curves of our digital system were 0.81 and 0.75, respectively, thus demonstrating greater accuracy than the CDS system (0.65 and 0.56, respectively) and multicriteria query techniques (0.68 and 0.56, respectively). DISCUSSION: Our innovative digital tool was notably more accurate than existing techniques (CDS system and multicriteria query) at intercepting potential prescription errors. CONCLUSIONS: By primarily targeting high-risk patients, this novel hybrid decision support system improved the accuracy and reliability of prescription checks in a hospital setting.

Off-label drug prescriptions in French general practice: a cross-sectional study.

OBJECTIVES: Off-label drug prescribing is a public health and economic issue. The aim of this study was to describe off-label prescription in general practice in France, in terms of frequency and nature, and to identify its main determining factors. DESIGN: Multicentre cross-sectional study SETTING: Twenty-three training general practice offices PARTICIPANTS: All the voluntary patients coming for a medical consultation or visited at home over a cumulative period of 5 days per office between November 2015 and January 2016. METHODS: Eleven interns, acting as observers, collected data. Two reviewers analysed the drugs prescribed by the trainers, in order to identify those prescribed off-label in terms of their indication or the age of the patient. We used a univariate, then a multivariate model, based on hierarchical mixed-effects logistic regression. RESULTS: Among the 4932 drug prescriptions registered, 911 (18.5%[95% CI17.4% to 19.6%]) were off-label, of which 865 (17.6%) due to the indication of the drug and 58 (1.2%) due to the age of the patient. The prescription never mentioned the off-label use, neither was the patient informed of it, as required by the French law. With the multivariate analysis, variables contributing to off-label prescription were the number of drugs (OR=1.05 for each additional drug), the initiation of new drug therapy (OR=1.26) and the non-specific goal of the prescription (OR=1.43); the age of the patient ≤14 years (OR=1.42); the rural location of the physician's practice (OR=1.38) and the low frequency of the visits of national health insurance representatives (OR=0.93). CONCLUSION: Almost one out of five drugs prescribed in French general practice was off-label. It seems necessary to better train physicians in clinical pharmacology, to provide them with more effective drug prescription software, to reinforce postmarketing surveillance and to clearly define off-label use by consensus.

INN or brand name drug prescriptions: a multilevel, cross-sectional study in general practice.

PURPOSE: The prescription in International Nonproprietary Names (INN) is a legal obligation for all physicians in France since January 2015. The objective of this study was to analyze the frequency and main factors of INN drug prescribing in general practice. METHODS: Multicenter cross-sectional study conducted with 11 interns acting as observers of 23 GP trainers between November 2015 and January 2016. Two evaluators analyzed all GPs' drug prescriptions to identify INN or brand name prescriptions. RESULTS: The database included 4957 drugs prescribed during 1647 visits. Of these, 1462 (29.5% [95% CI 28.2-30.8%]) were prescribed only in INN. According to the multivariate analyses, the factors favoring INN prescribing were as follows: at the drug level, its initial prescribing (OR = 1.4), a nonspecific prescribing objective (OR = 1.6), its listing in the generic drug index with (OR = 7.7) or without (OR = 2.9) efficiency objective included in the payment for public health objectives (PPHO) program, and the oral route of administration (OR from 0.4 for the percutaneous route to 0.2 for the pulmonary route); at the patient level, the male gender (OR = 1.3), the age of 15 years or more (OR = 1.9), and the absence of a long-term condition (OR = 1.3); at the physician level, the reception of a public healthcare insurance representative (OR = 4.1), the nonreception of pharmaceutical sales representatives (OR = 3.0), and the urban practice environment (OR = 2.8). CONCLUSIONS: In 2015, less than one third of drugs were prescribed in INN only in general practice. The use of various incentives and regulatory measures is likely to favor the prescription of INNs by practitioners.

[Bariatric surgery, stomas and other digestive tract reductions: Insufficient data and recommendations to adapt medicines regimens in therapeutic practice]. / Chirurgie bariatrique, stomies et autres réductions du tube digestif : trop peu de données et de recommandations pour l'adaptation des thérapeutiques médicamenteuses.

Surgery modifying digestive tract may alter drugs pharmacokinetics. To maintain concentrations of active substance in their therapeutic ranges, a dosage adjustment or change of drug may be necessary. This is particularly important when no pharmacological or pharmacodynamic parameter reflecting the medication effectiveness is easily measurable. Our objective was to gather the information and documentary tools that can guide prescription in these patients with rearranged digestive tract. We searched information on the documentary portals of French agencies, on gray literature, on MEDLINE and in the summaries product characteristics. No information was found on the website of French agencies, sparse data were identified in gray literature. Some document are discordant, most are imprecise. One hundred and ten studies or case reports referenced on MEDLINE describe 79 medications pharmacokinetics after gastrointestinal surgery. Four are not available in France. Six literature reviews were found. Four summaries of product characteristics provided information related to drug absorption. No documentary tool adapted to clinical routine exists. This unsatisfactory situation is a barrier to optimal patients care. Information is available. It is however necessary to gather under an ergonomic shape adapted to clinical routine, bringing the surgery type, pharmacokinetic changes induced and what to do about the dose adjustment.