Q-Method Evaluation of a European Health Data Analytic End User Framework

2019 ENTRENOVA Conference Proceedings

13 Pages Posted: 11 Dec 2019

See all articles by Andrew Boilson

Andrew Boilson

Dublin City University

Stephanie Gauttier

University of Twente - Faculty of Behavioural Sciences

Regina Connolly

Dublin City University

Paul Davis

Dublin City University

Justin Connolly

Dublin City University

Dale Weston

Government of the United Kingdom - Public Health England

Anthony Staines

Dublin City University

Date Written: September 12, 2019

Abstract

MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate the utilisation of a wide range of health and social care data to support better policy making. Our aim is to explore the use of Q-methodology as part of the evaluation of the implementation of the MIDAS project. Q-methodology is used to identify perspectives and viewpoints on a particular topic. In our case, we defined a concourse of statements relevant to project implementation and goals, by working from a logic model previously developed for the evaluation, and structured interviews with project participants. A 36-item concourse was delivered to participants, using the HTMLQ system. Analysis was done in the q-method package. Participants had a range of professional backgrounds, and a range of roles in the project, including developers, end-users, policy staff, and health professionals. The q-sort is carried out at 14 months into the project, a few months before the intended first release of the software being developed. Sixteen people took part, 6 developers, 5 managers, 2 health professionals and 3 others. Three factors (distinct perspectives) were identified in the data. These were tentatively labelled ‘Technical optimism’, ‘End-user focus’ and ‘End-user optimism’. These loaded well onto individuals, and there were few consensus statements. Analysis of these factors loaded well onto individuals with a significant number of consensus statements identified.

Keywords: Q-Methodology, Realist Evaluation, Public Health Systems, Data Analytics, ICT, Innovation, Decision Support Systems

JEL Classification: I18

Suggested Citation

Boilson, Andrew and Gauttier, Stephanie and Connolly, Regina and Davis, Paul and Connolly, Justin and Weston, Dale and Staines, Anthony, Q-Method Evaluation of a European Health Data Analytic End User Framework (September 12, 2019). 2019 ENTRENOVA Conference Proceedings. Available at SSRN: https://ssrn.com/abstract=3490516 or http://dx.doi.org/10.2139/ssrn.3490516

Andrew Boilson (Contact Author)

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Stephanie Gauttier

University of Twente - Faculty of Behavioural Sciences ( email )

Netherlands

Regina Connolly

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Paul Davis

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Justin Connolly

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

Dale Weston

Government of the United Kingdom - Public Health England ( email )

Anthony Staines

Dublin City University ( email )

Ireland 9
Dublin 9, leinster 9
Ireland

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