Benchmarking and improvement opportunities for data management practices in health research

Dr Michelle Krahe1, Julie Toohey2, Malcolm Wolski3, Professor Paul Scuffham4,5, Professor Sheena Reilly1,5

1Health Group, Griffith University, Gold Coast, Australia
2Library and Learning Services, Griffith University, Gold Coast, Australia
3eResearch Services, Griffith University, Nathan, Australia
4Centre for Applied Health Economics, Griffith University, Nathan, Australia
5Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia

Introduction

Research Data Management (RDM) best practice is imperative to higher academic institutions involved in the development of training programs that support researchers. Therefore, understanding researcher RDM practices will help articulate planning strategies for services and support, and highlight areas for future investment and development. This study sought to understand the current RDM practices of health and medical researchers from an academic institution in Australia.

Methods

Participants were drawn from a research institute and invited to complete an online survey to about: RDM practices, data storage and retention, data sharing practices and RDM training and development.

Results

Overall, our evaluation indicates that RDM practices which varied greatly, are likely to be influenced by level of experience or RDM practices carried out within teams or by supervisors. Only 1 in 3 researchers had a data management plan, almost 70% sourced their data from surveys and 53% collected consent for specific data use. The majority (80%) collected data using personal storage devices and 65% stored their data on removable media. Willingness to share data with colleagues, and the public significantly increased after being published (p<0.05). Collaboration, advancing knowledge and public benefit were the top reasons for sharing data.

Conclusion

Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data lifecycle, is effective in informing RDM services and support. This study recognises that targeted institutional strategies will strengthen researcher capacity, instill good research practice, and overall improve health informatics and research data quality.


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