Applying Systematic Review Methodologies to Business Studies exploring the Five Safes Framework

Systematic reviews are a cornerstone of evidence-based practices, traditionally developed within the medical discipline to ensure high-quality and reliable evidence selection. The methodology underpinning systematic reviews in medicine leverages controlled vocabularies, subject indexing, taxonomies, and standardized protocols to achieve structured and reproducible results. However, when applied to business studies, significant challenges emerge due to the lack of comparable structure, including the absence of controlled vocabularies. This paper investigates these challenges through a two-part study.

The first part of the study undertakes a systematic review of research using the Five Safes governance framework, focusing on data management strategies and their efficacy. Employing the PICO framework, the study conceptualizes research as the population, the Five Safes framework as the intervention, and examines outcomes such as data management quality, accessibility, reuse potential, and citation metrics. Comprehensive Boolean search strategies are used across databases such as ASSIA, EMBASE, and EconLit to identify relevant literature, yielding 1,459 articles. Following deduplication and screening, 1,244 articles are analyzed.

The second part reflects on the methodological contrasts between conducting systematic reviews in business studies versus health sciences. Key themes include the adaptability of systematic review protocols, challenges in defining search taxonomies for business studies, and the impact of interdisciplinary practices on data governance frameworks.

By explicitly exploring projects that employ the Five Safes, this study highlights the governance framework’s role in ensuring data accessibility, privacy, and safe reuse. The findings underscore the need for adapting systematic review methodologies to accommodate the less-structured nature of business studies literature. Furthermore, this research contributes to the growing dialogue on interdisciplinary data governance and provides practical recommendations for applying rigorous review methods in non-medical fields.