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OBJECTIVE: The aim of this study was to evaluate the influence of various factors on the perceived impact of a patient safety improvement collaborative in the UK, the Safer Patients Initiative (SPI). STUDY DESIGN: A cross-sectional survey design was used. Study setting Twenty National Health Service organizations from the UK that participated in the main phase of the SPI programme, which ran from September 2007 to 2008. PARTICIPANTS: Senior executive leads, clinical operational leads in the four clinical areas targeted by the programme, programme coordinators and any other staff involved in the SPI (n = 635). INTERVENTION: The SPI is a patient safety improvement intervention based on the Breakthrough Series Collaborative model (Institute of Healthcare Improvement, 2004) aimed at improving patient safety in four clinical areas (general ward care, intensive care, perioperative care and pharmacy) through implementing a number of evidence-based clinical practices and a focus on organizational leadership. Outcome measures Participant perceptions of the impact of the programme on their organizations. RESULTS: Exploratory regression analysis showed that programme management, the value assigned to programme methodology and length of data collection contributed the largest variance in perceived impact of the SPI followed by perceived support from junior doctors, inter-professional collaboration, difference of the programme from existing safety improvement practices and organizational readiness. CONCLUSIONS: The resulting model suggests hierarchical importance for a range of variables to support future research concerning the mechanisms by which large-scale organizational programmes, such as the SPI, impact on the care systems they are designed to influence.

Original publication




Journal article


Int J Qual Health Care

Publication Date





173 - 181


Attitude of Health Personnel, Cooperative Behavior, Cross-Sectional Studies, Great Britain, Health Facility Administrators, Humans, Models, Organizational, Program Evaluation, Quality Assurance, Health Care, Regression Analysis, Safety Management, State Medicine