BACKGROUND: Patients hospitalized for a given condition may be receiving other treatments for other contemporary conditions or comorbidities. The use of such observational clinical data for pharmacological hypothesis generation is appealing in the context of an emerging disease but particularly challenging due to the presence of drug indication bias.
OBJECTIVE: With this study, our main objective was the development and validation of a fully data-driven pipeline that would address this challenge. Our secondary objective was to generate pharmacological hypotheses in patients with COVID-19 and demonstrate the clinical relevance of the pipeline.
METHODS: We developed a pharmacopeia-wide association study (PharmWAS) pipeline inspired from the PheWAS methodology, which systematically screens for associations between the whole pharmacopeia and a clinical phenotype. First, a fully data-driven procedure based on adaptive least absolute shrinkage and selection operator (LASSO) determined drug-specific adjustment sets. Second, we computed several measures of association, including robust methods based on propensity scores (PSs) to control indication bias. Finally, we applied the Benjamini and Hochberg procedure of the false discovery rate (FDR). We applied this method in a multicenter retrospective cohort study using electronic medical records from 16 university hospitals of the Greater Paris area. We included all adult patients between 18 and 95 years old hospitalized in conventional wards for COVID-19 between February 1, 2020, and June 15, 2021. We investigated the association between drug prescription within 48 hours from admission and 28-day mortality. We validated our data-driven pipeline against a knowledge-based pipeline on 3 treatments of reference, for which experts agreed on the expected association with mortality. We then demonstrated its clinical relevance by screening all drugs prescribed in more than 100 patients to generate pharmacological hypotheses.
RESULTS: A total of 5783 patients were included in the analysis. The median age at admission was 69.2 (IQR 56.7-81.1) years, and 3390 (58.62%) of the patients were male. The performance of our automated pipeline was comparable or better for controlling bias than the knowledge-based adjustment set for 3 reference drugs: dexamethasone, phloroglucinol, and paracetamol. After correction for multiple testing, 4 drugs were associated with increased in-hospital mortality. Among these, diazepam and tramadol were the only ones not discarded by automated diagnostics, with adjusted odds ratios of 2.51 (95% CI 1.52-4.16, Q=.1) and 1.94 (95% CI 1.32-2.85, Q=.02), respectively.
CONCLUSIONS: Our innovative approach proved useful in generating pharmacological hypotheses in an outbreak setting, without requiring a priori knowledge of the disease. Our systematic analysis of early prescribed treatments from patients hospitalized for COVID-19 showed that diazepam and tramadol are associated with increased 28-day mortality. Whether these drugs could worsen COVID-19 needs to be further assessed.

BACKGROUND: Assessing the effectiveness of in-service training courses in order to achieve the desired goals and reduce the waste of costs and opportunities in the system is necessary. The purpose of this study was to determine the effectiveness of the \"pharmacopeia home health\" course considering its importance in different aspects using the Kirkpatrick model.
METHODS: The present study was a quasi-experimental conducted at community health workers (CHWs) on three levels of reaction, learning, and behavior. In each phase, a valid questionnaire was used to measure the outcome according to the Ministry of Health guidelines with pretest and posttest measurements. The data were analyzed through SPSS 23, using descriptive statistics and repeated measures test and general linear model.
RESULTS: The results of the study showed that at the level of reaction in terms of content and holding, conditions of implementation were favorable. Findings at the level of learning showed that the training course was only effective in enhancing the knowledge and awareness about drug maintenance and had no significant effect on other areas. In the third level, the results of the CHWs\' performance showed that in some areas, the results were influenced by the demographic variables.
CONCLUSIONS: The present study showed the effectiveness of education in different areas using on the Kirkpatrick model. Given the lack of impact of education in some areas in the present study and on the other, it is necessary to consider cooperative learning methods in order to develop the effectiveness of the courses.

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