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<\/p>\nAs the name itself suggests, the definition \u201creal world evidence\u201d (RWE) indicates scientific evidence derived from the real world, i.e. the output of analysis of data coming from a patient\u2019s daily life (\u201creal world data\u201d, RWD).<\/p>\n
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RWD are originated from numerous sources, among which electronic health records, administrative logs (e.g. for reimbursements or activity monitoring), pathology registers and non-clinical sources capable of providing information on the state of health (e.g., mobile and\/or wearable devices).<\/p>\n
An RWE-based approach favors research from several points of view, improving the planning of processes from the clinical, management and financial point of view.<\/strong><\/p>\n An example of the above described situation comes from the issues stemming from inadequate planning<\/a>, which affect clinical trials causing delays- or even, in extreme cases, the failure of the set objectives.<\/p>\n It is clear how the management of these unforeseen situations affects not only the scientific aspect of a trial, but also the financial one, by significantly impacting the size of the investment necessary to meet the set goals.<\/p>\n A data driven approach to the feasibility analysis for trials allows the execution of estimations that are more precise and helps containing the above listed issues.<\/p>\n This analysis (patients eligibility assessment) is traditionally carried out through surveys for potential investigators. Instruments exist that allow the optimization of the evaluation process.<\/p>\n The availability of research data warehouses (DWH)- i.e. an aggregator of data originating from different sources- facilitates a fast, accurate and reliable assessment.<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n The creation of DWH networks based on a common data model (CDM) bringing together different centers favors a federated approach to research: the sharing of aggregated data and the implementation of semi-automated procedures that can work in all the nodes of the network<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n The exploitation of standard terminologies<\/a>, the use of a common data model<\/a> and the alignment of the data sources to the FAIR principles<\/a>, all of which are covered in other insights on this site, are essential elements to ensure interoperability within a federated infrastructure.<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" As the name itself suggests, the definition \u201creal world evidence\u201d (RWE) indicates scientific evidence derived from the real world, i.e. the output of analysis of data coming from a patient\u2019s daily life (\u201creal world data\u201d, RWD). RWD are originated from numerous sources, among which electronic health records, administrative logs (e.g. for reimbursements or activity monitoring), […]<\/p>\n","protected":false},"author":1,"featured_media":6655,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[188,171,193],"tags":[],"class_list":["post-6674","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-focus","category-news","category-omop-en"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n
![\"\"](\"https:\/\/www.biomeris.it\/wp-content\/uploads\/2024\/05\/datawarehouse.png\")
<\/p>\n![\"\"](\"https:\/\/www.biomeris.it\/wp-content\/uploads\/2024\/05\/reti-dwh.png\")
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