{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T20:54:18Z","timestamp":1767905658659,"version":"3.49.0"},"reference-count":15,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T00:00:00Z","timestamp":1657238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Real world data (RWD) and real-world evidence (RWE) plays an increasingly important role in clinical research since scientific knowledge is obtained during routine clinical large-scale practice and not experimentally as occurs in the highly controlled traditional clinical trials. Particularly, the electronic health records (EHRs) are a relevant source of data. Nevertheless, there are also significant challenges in the correct use and interpretation of EHRs data, such as bias, heterogeneity of the population, and missing or non-standardized data formats. Despite the RWD and RWE recognized difficulties, these are easily outweighed by the benefits of ensuring the efficacy, safety, and cost-effectiveness in complement to the gold standards of the randomized controlled trial (RCT), namely by providing a complete picture regarding factors and variables that can guide robust clinical decisions. Their relevance can be even further evident as healthcare units develop more accurate EHRs always in the respect for the privacy of patient data. This editorial is an overview of the RWD and RWE major aspects of the state of the art and supports the Special Issue on \u201cDigital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers\u201d aimed to explore all the potential and the utility of RWD and RWE in offering insights on diseases in a broad spectrum.<\/jats:p>","DOI":"10.3390\/ijerph19148364","type":"journal-article","created":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T11:37:08Z","timestamp":1657280228000},"page":"8364","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers"],"prefix":"10.3390","volume":"19","author":[{"given":"Teresa","family":"Magalh\u00e3es","sequence":"first","affiliation":[{"name":"Department of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"},{"name":"Center for Health Technology and Services Research (CINTESIS), 4200-450 Porto, Portugal"},{"name":"MTG Research and Development Lab, 4200-604 Porto, Portugal"},{"name":"TOXRUN\u2014Toxicology Research Unit, University Institute of Health Sciences, Advanced Polytechnic and University Cooperative (CESPU), CRL, 4585-116 Gandra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7430-6297","authenticated-orcid":false,"given":"Ricardo Jorge","family":"Dinis-Oliveira","sequence":"additional","affiliation":[{"name":"Department of Public Health and Forensic Sciences, and Medical Education, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"},{"name":"MTG Research and Development Lab, 4200-604 Porto, Portugal"},{"name":"TOXRUN\u2014Toxicology Research Unit, University Institute of Health Sciences, Advanced Polytechnic and University Cooperative (CESPU), CRL, 4585-116 Gandra, Portugal"},{"name":"UCIBIO-REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0998-6000","authenticated-orcid":false,"given":"Tiago","family":"Taveira-Gomes","sequence":"additional","affiliation":[{"name":"Center for Health Technology and Services Research (CINTESIS), 4200-450 Porto, Portugal"},{"name":"MTG Research and Development Lab, 4200-604 Porto, Portugal"},{"name":"Department of Community Medicine, Information and Decision in Health, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"},{"name":"Faculty of Health Sciences, University Fernando Pessoa (FCS-UFP), 4249-004 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100797","DOI":"10.1016\/j.imr.2021.100797","article-title":"A brief introduction to research based on real-world evidence: Considering the Korean National Health Insurance Service database","volume":"11","author":"Ahn","year":"2022","journal-title":"Integr. 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