A Complex Intervention to Prevent Medication-Related Hospital Admissions.

BACKGROUND: Children are often treated off-label and are at a disadvantage in pharmacotherapy. The aim of this study was to implement and evaluate a quality assurance measure (PaedPharm) for pediatric pharmacotherapy whose purpose is to reduce medication-related hospitalizations among children and adolescents. METHODS: PaedPharm consisted of the digital pediatric drug information system PaedAMIS, pediatric pharmaceutical quality circles (PaedZirk), and an adverse drug event (ADE) reporting system (PaedReport). The intervention was implemented in a cluster-randomized trial (DRKS 00013924) in 12 regions, with a pediatric and adolescent medicine clinic in each and a total of 152 surrounding private practitioners, in 6 sequences over 8 quarters. In addition to the proportion of ADE-related hospital admissions (primary endpoint), comprehensive process evaluation included other endpoints such as coverage, user acceptance, and relevance to practice. RESULTS: 41 829 inpatient admissions were recorded, of which 5101 were patients of physicians who participated in our study. 4.1% of admissions were ADE-related under control conditions, and 3.1% under intervention conditions (95% CI: [2.3; 5.9] and [1.8; 4.5], respectively). A model-based comparison yielded an intervention effect of 0.73 (population-based odds ratio; [0.39; 1.37]; p = 0.33). PaedAMIS achieved moderate user acceptance and PaedZirk achieved high user acceptance. CONCLUSION: The introduction of PaedPharm was associated with a decrease in medication-related hospitalizations that did not reach statistical significance. The process evaluation revealed broad acceptance of the intervention in outpatient pediatrics and adolescent medicine.

How paediatric drug development and use could benefit from OMICs: A c4c expert group white paper.

The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates and infants, is limited by a paucity of good-quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts by complementary information about targeted and nontargeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating, allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a subdivision into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as are the type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, noninvasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (eg liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, such as artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to the identification complex phenotypes and subpopulations of patients to improve the development of medicines for children with potential economic advantages.