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The Information Paradox: Researching Health Service Information Systems Development

The Information Paradox: Researching Health Service Information Systems Development
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Author(s): Said Shahtahmasebi (The Good Life Research Centre Trust, New Zealand & University of Kentucky, USA)
Copyright: 2017
Pages: 16
Source title: Public Health and Welfare: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1674-3.ch002

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Abstract

This paper is based on a 2008 chapter (Shahtahmasebi, 2008) exploring the availability of information for public health policy purposes which argued its ineffectiveness to add insight and inform the process of policy development. Processes are dynamic by nature which politicians and professionals often neglect in addressing public health issues. The Chapter argued that whilst information is a major currency within health systems a lack of understanding of what constitutes information has disguised available data as small change. Since 2008, against a backdrop of reorganisations, restructuring, buzzwords, and coupled with the rapid advancement in technology the issues remain the same but are somewhat more complicated due to the feedback effect of dynamic processes. For example, a curious persistence of various governments with electronic health records has done nothing to address the gap in “information” or incompatibility in the information systems developed and managed by various care agencies. Furthermore, changing information to “intelligence” (e.g. Public Health Intelligence Units) or “observatories” to carry out similar tasks of reporting health outcomes using the same routine data will not solve the problem. This paper proposes a re-evaluation of the author's focus on informatics and suggests a move away from a technological “solution” based approach to a human behaviour-led approach that utilises the full potential of technologies to address important issues. To this end, this paper proposes a conceptual model to improve access, over and above clinical data, to health data.

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