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Updated: Oct 8, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Which human factors design issues are influencing system performance in out-of-hours community palliative care?
Sarah Yardley1,2, Huw Williams3, Paul Bowie4,5,6,7
1Marie Curie Palliative Care Research Department, University College London, London, UK.
Objective:
To develop mid-range programme theory from perceptions and experiences of out-of-hours community palliative care, accounting for human factors design issues that might be influencing system performance for achieving desirable outcomes through quality improvement.
Setting:
Community providers and users of out-of-hours palliative care.
Participants:
17 stakeholders participated in a workshop event.
Design:
In the UK, around 30% of people receiving palliative care have contact with out-of-hours services. Interactions between emotions, cognition, tasks, technology and behaviours must be considered to improve safety. After sharing experiences, participants were presented with analyses of 1072 National Reporting and Learning System incident reports. Discussion was orientated to consider priorities for change. Discussions were audio-recorded and transcribed verbatim by the study team. Event artefacts, for example, sticky notes, flip chart lists and participant notes, were retained for analysis. Two researchers independently identified context-mechanism-outcome configurations using realist approaches before studying the inter-relation of configurations to build a mid-range theory. This was critically appraised using an established human factors framework called Systems Engineering Initiative for Patient Safety (SEIPS).
Results:
Complex interacting configurations explain relational human-mediated outcomes where cycles of thought and behaviour are refined and replicated according to prior experiences. Five such configurations were identified: (1) prioritisation; (2) emotional labour; (3) complicated/complex systems; (4a) system inadequacies and (4b) differential attention and weighing of risks by organisations; (5) learning. Underpinning all these configurations was a sixth: (6a) trust and access to expertise; and (6b) isolation at night. By developing a mid-range programme theory, we have created a framework with international relevance for guiding quality improvement work in similar modern health systems.
Conclusions:
Meta-cognition, emotional intelligence, and informal learning will either overcome system limitations or overwhelm system safeguards. Integration of human-centred co-design principles and informal learning theory into quality improvement may improve results.
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