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Data Integration Protocol In Ten-steps (DIPIT): a new standard for medical researchers
Joanna F Dipnall1, Michael Berk2, Felice N Jacka3
1IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, Victoria, Australia; Department of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Hawthorn, Victoria, Australia.
Introduction:
The exponential increase in data, computing power and the availability of readily accessible analytical software has allowed organisations around the world to leverage the benefits of integrating multiple heterogeneous data files for enterprise-level planning and decision making. Benefits from effective data integration to the health and medical research community include more trustworthy research, higher service quality, improved personnel efficiency, reduction of redundant tasks, facilitation of auditing and more timely, relevant and specific information. The costs of poor quality processes elevate the risk of erroneous outcomes, an erosion of confidence in the data and the organisations using these data. To date there are no documented set of standards for best practice integration of heterogeneous data files for research purposes. Therefore, the aim of this paper is to describe a set of clear protocol for data file integration (Data Integration Protocol In Ten-steps; DIPIT) translational to any field of research.
Methods And Results:
The DIPIT approach consists of a set of 10 systematic methodological steps to ensure the final data are appropriate for the analysis to meet the research objectives, legal and ethical requirements are met, and that data definitions are clear, concise, and comprehensive. This protocol is neither file specific nor software dependent, but aims to be transportable to any data-merging situation to minimise redundancy and error and translational to any field of research. DIPIT aims to generate a master data file that is of the optimal integrity to serve as the basis for research analysis.
Conclusion:
With linking of heterogeneous data files becoming increasingly common across all fields of medicine, DIPIT provides a systematic approach to a potentially complex task of integrating a large number of files and variables. The DIPIT protocol will ensure the final integrated data is consistent and of high integrity for the research requirements, useful for practical application across all fields of medical research.
