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Data Integration Protocol In Ten-steps (DIPIT) : a new standard for medical researchers

journal contribution
posted on 2014-10-01, 00:00 authored by Joanna Frith Dipnall, Michael BerkMichael Berk, Felice JackaFelice Jacka, Lana WilliamsLana Williams, Seetal DoddSeetal Dodd, Julie PascoJulie Pasco
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.

History

Journal

Methods

Volume

69

Issue

3

Pagination

237 - 246

Publisher

Elsevier

Location

Amsterdam, The Netherlands

eISSN

1095-9130

Language

eng

Publication classification

C Journal article; C1 Refereed article in a scholarly journal

Copyright notice

2014, Elsevier