Analysing organisational context: case studies on the contribution of absorptive capacity theory to understanding inter-organisational variation in performance improvement.

BACKGROUND Organisational context is frequently cited as an important consideration when implementing and evaluating quality improvement interventions in healthcare, but limited guidance is available on which aspects of context are most influential or modifiable. This paper examines how internal and external contextual factors mediate organisational-level performance improvement through applying the knowledge-based theory of absorptive capacity (AC). METHODS Three healthcare case studies are presented. Each case is a UK National Health Service organisation that had been identified as having performance problems. Qualitative data were collected through semi-structured interviews with general and clinical managers within the organisation and members of external teams supporting or overseeing performance improvement (n=22). Interview data were analysed using an existing AC framework from the literature. RESULTS The organisation with the highest AC showed the quickest and most comprehensive performance improvement. Internal characteristics including strategic priorities, processes for managing information, communication and orientation to learning and development impacted on the organisation's ability to engage successfully with external stakeholders and make use of available knowledge. This enabled the organisation to thrive despite the challenging external environment. Lower levels of AC appeared to delay or limit the improvement trajectory. CONCLUSIONS Developing a more detailed and nuanced understanding of how context influences improvement is an important step towards achieving more effective and sustainable quality improvement programmes in healthcare. AC, with its focus on knowledge and organisational learning, provides a useful way to explore the relationship between context and quality improvement and represents a potentially valuable area for future research and development.