Refining gold from existing data

Abstract

Purpose of review The purpose is to review the arguments for increasing use of existing data in health research. Recent Findings The reuse of data in observational, exploratory and outcome studies, as well as in confirming other findings, is being justified on epistemological grounds as the major path to new knowledge and to the generalizing of findings to “real world” populations. It is also justified on grounds of cost, power and efficiency, even though data reuse comes with real informatics, scientific culture, societal and regulatory issues. Summary Data reuse is becoming more compelling. When contemplating new research for any purpose other than RCTs for efficacy, it is prudent to consider whether partnership with existing data holders should be part of the optimal research plan.

The reuse of public datasets in the life sciences: potential risks and rewards

“…Recently, GEO has been used in a case study to improve dataset reusability with a literature recommendation system (Patra et al, 2020) and is highly recommended over other databases for the submission of RNA-Seq datasets (Bhandary et al, 2018). In medical research, information loss stems from large amounts of gathered data remaining inaccessible for reuse by a wider audience (sometimes even the authors) after the initial publication (Wade, 2014). Moreover, the development of new tools and methods leads to the possibility of extracting more information from a given dataset than was feasible at the time of publication.…”

“…Integration of data from different sources, for example, of exRNA metadata, biomedical ontologies and Linked Data technologies can facilitate interpretation and hypotheses generation by providing independent biological context (Subramanian et al, 2015). In medicine, reuse of data collected as a by-product of health care has the potential to transform the practice of medicine and its delivery, which is a compelling argument of reuse benefits outweighing the risks (Wade, 2014;Safran, 2017). For example, reuse can help eliminate bottlenecks in biomedical research at all translational levels and data-mining (the hypothesis-free search for patterns in data) can reveal potential starting points for experimental medical research (Wade, 2014).…”

“…In medicine, reuse of data collected as a by-product of health care has the potential to transform the practice of medicine and its delivery, which is a compelling argument of reuse benefits outweighing the risks (Wade, 2014;Safran, 2017). For example, reuse can help eliminate bottlenecks in biomedical research at all translational levels and data-mining (the hypothesis-free search for patterns in data) can reveal potential starting points for experimental medical research (Wade, 2014). Another method of reuse is meta-analysis, which can elucidate new patterns and produce novel hypotheses-inaccessible from the analysis of any individual dataset.…”

“…In plant phenotyping, reuse and meta-analysis is challenging as data comes from different experimental sites, plant species and experimental conditions, while including many different data types (Papoutsoglou et al, 2020). This non-comparability is also repeated in medical research (Wade, 2014). Therefore, for any valid comparison between datasets from different databases or for integration of databases themselves, conditions specific to the data type and field have to be satisfied.…”

SPIRIT: Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data

“…On the other hand, this "information explosion" can open up undreamed-of possibilities of secondary use, defined as the (re)use of clinical routine data outside direct care for multiple purposes [2]. Clinical routine data are considered extremely precious [3,4] and secondary use can be beneficial for almost all stakeholders in the healthcare sector, including policymakers, public health officials, scientists, clinicians, citizens, and industry. But of course, secondary use impli-cates new challenges and problems [5].…”