Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers

Abstract

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 “Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers” aimed to explore all the potential and the utility of RWD and RWE in offering insights on diseases in a broad spectrum.

Parental executive functions and motivations unveil variations in young children's screen media use

“…Moreover, the outcomes of this investigation are in line with the recent discourse surrounding realworld data, as it encompasses behaviors of children and parents obtained through surveys. These findings contribute valuable insights for informing future healthcare decisions (Magalhães et al, 2022). Leveraging these insights, such interventions can be strategically employed to provide guidance to parents, facilitating the development of cognitive strategies aimed at mitigating excessive screen-based device usage in children.…”

“…The study aligns with recent discourse on real-world data, emphasizing the significance of collecting diverse data sources, including electronic medical records, claims databases, patient-generated data, and surveys. Through rigorous analytics, real-world evidence is generated, offering distinct advantages over traditional healthcare assessments (Magalhães et al, 2022). In this context, the study focuses on capturing data related to various screen behaviors in children and their parents to provide new insights into the health implications for families.…”

Smart Solutions for Diet-Related Disease Management: Connected Care, Remote Health Monitoring Systems, and Integrated Insights for Advanced Evaluation

“…Assessing user experiences and opinions facilitates the identification of possible problems, usability issues, and areas in need of development. Good user experiences are frequently correlated with the monitoring system's overall accuracy and efficacy; • Real-world use cases: It is important to assess data accuracy in real-world situations, such as the everyday lives of patients and hospital environments [113]. Given the dynamic nature of managing diet-related diseases, knowing how effectively smart devices function in real-world settings guarantees their applicability and efficacy in a range of healthcare settings; • Validation by healthcare professionals: It is essential that healthcare professionals participate in the evaluation process.…”

The Constrained-Disorder Principle Assists in Overcoming Significant Challenges in Digital Health: Moving from “Nice to Have” to Mandatory Systems

“…Over the last decade, numerous systems have been associated with biases that evolve from the data type used [ 129 ]. Many current ML systems are based on existing data, not looking for relevant data [ 130 , 131 ]. It is common for algorithms to be trained using data from tertiary settings instead of primary care, which does not represent mild diseases well.…”