1. Congruence: normalization is likely if the actors have a shared belief in the process
Lack of use by most practitioners suggests that there was doubt about the value of the tool: ‘I attended the training and thought (Isabel) would be quite useful but not to use on every patient. I didn't really get around to using it because you don't really see many of those patients in that time frame’ (1, Senior female GP)
Doctor/patient relationship: ‘I'd be a bit concerned about the patients’ perception of entering information into a system that gives you an answer. You hear patients say, “Oh I went to see my GP and they looked at a book”’ (2, Junior female GP).
2. Disposal: normalization is likely if the actors have a shared belief in the goals
Practitioners agreed that a decision support system could be useful, but not Isabel as it is currently configured. ‘[Isabel] comes up with the bizarre…not your common garden stuff you see in general practice’ (3, Senior nurse practitioner)
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5. Allocation: normalization is likely if actors’ responsibilities are agreed within contexts
Only the practice managers agreed to participate, not clinicians
Use of the system was at the discretion of the practitioner
Roles were not agreed ‘It would have been good for [the new trainee]….It is more placed as a learning tool…I don't think the GPs would have used it. They would have done it once and then thought…’ (3, Senior nurse practitioner)
6. Performance: normalization is likely if the level to which actors perform is agreed within contexts
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Relational integration 3. Accountability: normalization is likely if actors have the necessary expertise
4. Confidence: normalization is likely if actors believe it falls within their remit
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Contextual integration 7. Execution: normalization is likely if resourcing issues are agreeable between/within contexts
All practices had sufficient IT resources
Time was not adequately resourced, e.g. no extra time was allotted for consultations
8. Realization: normalization is likely if organizational systems between/within contexts are minimally disrupted
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