Title: Clinician value from big data: creating a path forwards

Authors: Christopher Bain; Jarrel Seah; Bismi Jomon

Addresses: Faculty of IT, Monash University, 900 Dandenong Rd, Caulfield East VIC, 3145, Australia ' Alfred Health, 55 Commercial Rd, Melbourne VIC, 3004, Australia ' Applications and Knowledge Management Department, Alfred Health, 55 Commercial Rd, Melbourne VIC, 3004, Australia

Abstract: Whilst many in healthcare view the arrival of the era of big data as an overwhelmingly positive thing, there are some who refute that claim and increasingly point out the limitations of using big data derived datasets for clinical research in particular. In this paper we examine some of the challenges and constraints regarding access to data for clinicians and researchers, despite the collection and generation of vast amounts of data (big data) in the healthcare industry. We also briefly explore some of the challenges around identifying cohorts from, and performing analysis on, such datasets. As part of this we present on the latest developments with a custom designed search tool (The cohort discovery tool (CDT)) that allows such users flexibility in how they access a vast clinical data repository inside The REASON Discovery Platform^®. We also examine some of the strengths and weaknesses of the tool and factors influencing its uptake by clinicians at its primary site.

Keywords: big data; cohort; REASON; hospital; research; cohort discovery tool; CDT; informatics; clinical data.

DOI: 10.1504/IJEH.2017.085804

International Journal of Electronic Healthcare, 2017 Vol.9 No.4, pp.275 - 293

Received: 11 Jul 2016
Accepted: 13 Sep 2016
Published online: 14 Aug 2017 *

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