Abstract Background MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to use a wide range of health and social care data to support better policy making. As part of the project evaluation, we have used Q-methodology, a well established approach, to understand the perspectives of the individual participants on their needs and how the MIDAS system is meeting them, at its current stage of development. Methods We defined a concourse of 36 statements relevant to project implementation and goals, by working from a logic model for the evaluation, and structured interviews with project participants. This was delivered online to participants. Analyses were done in the qmethod package. The first q-sort was done at 14 months into the project. Results 16 people took part, 6 developers, 5 managers, 2 health professionals and 3 others. Three factors 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. There were significant differences in perspectives between different groups of participants. In particular, two of the developers held opposite perspectives to most other participants on the third perspective identified. This was drawn to the attention of the participants, and a more intensive process of communication was set-up, seeking to reduce the divergence. Conclusions A Q-methodological approach to evaluating the implementation of a large and complex health ICT system showed considerable divergence between the perspectives of users, developers, and managers. Such divergences can lead to project failure. Q-methodology is a valuable tool has seldom been used in public health research. Keywords: Q-Methodology, Public Health, Data Analytics, Decision Support.
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