Reusing data: Retrospective vs prospective studies
Health data plays a critical role in nearly all aspects of medical research. It enables the early detection of diseases, contributes to our understanding of disease mechanisms, and supports the development of innovative treatment methods. Furthermore, by preventing disease and promoting public health, health data can extend the reach of effective medical treatments worldwide. The ultimate goal is not just to cure diseases, but also to improve the quality of life for people everywhere.
To be clear, collaboration on health data is not sharing of curated datasets from a common governmental or institutional repository or applying for access from a data holder. Collaboration means to design the study together, collect data together, analyse the data together, discuss the results together, and turn the insights into impact together through publication or clinical practice.
Medical research is inherently collective and often requires large volumes of data, especially in cases of rare diseases and pandemic response. Collaboration enhances scientific synergies by linking complementary skills, and facilitates more comprehensive analysis of health data. Reproducibility and transparency are also crucial for the integrity of science.
Many of the debates about data sharing and reusing data for research focus on how to deal with retrospective data. While retrospective studies are important for understanding past trends and treatment outcomes, most of today's research are prospective approaches. Retrospective data often serves as comparative material in these studies, underscoring the need for seamless integration of both types of data in research processes.
Practical challenges
Despite clear benefits, collaborating on health data presents significant challenges, particularly regarding privacy and data integrity. Privacy regulations classify health data as sensitive data, and are thus subject to strict privacy regulation. But we need to there has to be a balanceing act between privacy and the societal benefits to be obtained from leveraging the data for research.
“Health crises, such as the COVID-19 pandemic, show that efficient sharing of personal health data is crucial to ensure that locally conducted research can be used at the world level. We need a solution that maximises the individual and societal benefits to be obtained from research participants’ contributions in order to improve the diagnosis and treatment for patients in both global regions and beyond” (Federation of European Academies of Medicine, 2021).
Diverse data collection methods and processing require robust solutions for data sharing and analysis. Currently, the common ways of collecting and sharing prospective health data in collaborative settings often come with data privacy risks caused by sharing, merging, cleaning and structuring datasets from different sites.
Practical solution
By contrast, Ledidi Core represents a practical, safe and user friendly solution that allows researchers and clinicians to work together to collect and analyse sensitive datasets using privacy-preserving multiparty analysis.
This effectively allows clinicians and researchers to share insights instead of data, preserving the privacy of patients while providing insights from both retrospective and prospective data to improve health outcomes. This is enabled by working in a single platform that combines study design, data capture and analysis with granular access management controls.
Ledidi Core is a next-generation healthcare research environment (Gartner, 2023) that overcomes practical challenges for clinicians and researchers to interact with health data, enabling real-time global collaboration without compromises on patient privacy and data security. Experience the world’s most versatile health registry and research platform today.