<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Background:</bold> This paper describes the impact evaluation of a large big data platform initiative that is being undertaken in order to increase the probability of its success. The initiative, MIDAS (Meaningful Integration of Data Analytics and Services), is a European health-based Horizon 2020 project comprising a consortium of members from various universities, research institutions, and government agencies.<bold>Objectives:</bold> The purpose of the paper is to present a pioneering platform that will support healthcare policymakers in their decision-making by enabling greater and more efficient use of their data. The goal is to present and evaluate the results of the MIDAS project across four countries.<bold>Methods/Approach:</bold> The literature is replete with examples of worthwhile technology projects that have failed due to user resistance. In order to avoid such failure, and ensure the success of the final MIDAS platform, a detailed impact evaluation is being undertaken at timed periods of development.<bold>Results:</bold> This paper describes the impact evaluation process, outlining the use of Q-methodology and the development of a 36-item concourse using the HTMLQ system for that purpose.<bold>Conclusions:</bold> This research contributes to the overall understanding of how impact evaluation can be undertaken at timed periods during the development of an innovative technology for organisational purposes.</abstract>

Background: This paper describes the impact evaluation of a large big data platform initiative that is being undertaken in order to increase the probability of its success. The initiative, MIDAS (Meaningful Integration of Data Analytics and Services), is a European health-based Horizon 2020 project comprising a consortium of members from various universities, research institutions, and government agencies.Objectives: The purpose of the paper is to present a pioneering platform that will support healthcare policymakers in their decision-making by enabling greater and more efficient use of their data. The goal is to present and evaluate the results of the MIDAS project across four countries.Methods/Approach: The literature is replete with examples of worthwhile technology projects that have failed due to user resistance. In order to avoid such failure, and ensure the success of the final MIDAS platform, a detailed impact evaluation is being undertaken at timed periods of development.Results: This paper describes the impact evaluation process, outlining the use of Q-methodology and the development of a 36-item concourse using the HTMLQ system for that purpose.Conclusions: This research contributes to the overall understanding of how impact evaluation can be undertaken at timed periods during the development of an innovative technology for organisational purposes.

Impact Evaluation of an Emerging European Health Project – the MIDAS Model

Business Systems Research Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Impact Evaluation of an Emerging European Health Project \u2013 the MIDAS Model"}

Background: This paper describes the impact evaluation of a large big data platform initiative that is being undertaken in order to increase the probability of...

Impact Evaluation of an Emerging European Health Project – the MIDAS Model

Published Online: Apr 13, 2020

Page range: 142 - 150

Received: Sep 12, 2019

Accepted: Jan 15, 2020

DOI: https://doi.org/10.2478/bsrj-2020-0010

Keywords
MIDAS, health-based project, decision support systems, data mining

© 2020 Justin Connolly et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Impact Evaluation of an Emerging European Health Project – the MIDAS Model

Published Online: Apr 13, 2020

Page range: 142 - 150

Received: Sep 12, 2019

Accepted: Jan 15, 2020

DOI: https://doi.org/10.2478/bsrj-2020-0010

KeywordsMIDAS, health-based project, decision support systems, data mining

© 2020 Justin Connolly et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
MIDAS, health-based project, decision support systems, data mining