Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach

7 Pages Posted: 19 Nov 2018

See all articles by Justin Connolly

Justin Connolly

Dublin City University

Anthony Staines

Dublin City University

Regina Connolly

Dublin City University

Andrew Boilson

Dublin City University

Paul Davis

Dublin City University

Dale Weston

Public Health England, United Kingdom

Natasha Bloodworth

Public Health England, United Kingdom

Date Written: September 6, 2018

Abstract

Despite advances in technology and medical science, modern health-based projects are open to systemic failure due to many factors. These include I.T. developer’s lack of awareness with regard to end-user needs, poor communication amongst all parties concerned and inappropriate or inadequate tests of the emerging system. Other issues may be external (e.g. political and legal) such as sharing of patient data and issues surrounding consent. The goal of this paper is to take a major health-based European model in current development and explore how it addresses the needs of four institutions in four different countries, and how it will meet their respective needs. The evaluation was designed within a Logic Model, and uses the Framework approach, and Q-Methodology to assess both impact and evaluation. Data will be collected through longitudinal semi-structured interviews and Q-scoring with principal stakeholders and developers at each stage of the project. This approach, recurring interviews with the same key players in the project, will help ensure that there is mutual understanding between I.T. developers and end-users of the system. The final system is meant to provide effective health-based decision support systems for policy makers.

Keywords: MIDAS technology, health-based projects, decision support systems, data mining

JEL Classification: I18

Suggested Citation

Connolly, Justin and Staines, Anthony and Connolly, Regina and Boilson, Andrew and Davis, Paul and Weston, Dale and Bloodworth, Natasha, Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach (September 6, 2018). 2018 ENTRENOVA Conference Proceedings. Available at SSRN: https://ssrn.com/abstract=3283094 or http://dx.doi.org/10.2139/ssrn.3283094

Justin Connolly (Contact Author)

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Anthony Staines

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Regina Connolly

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Andrew Boilson

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Paul Davis

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Dale Weston

Public Health England, United Kingdom ( email )

Natasha Bloodworth

Public Health England, United Kingdom ( email )

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