Facilitators for using data from a quality registry in local quality improvement work: a cross-sectional survey of the Danish Cardiac Rehabilitation Database

OBJECTIVES: To investigate use of data from a clinical quality registry for cardiac rehabilitation in Denmark, considering the extent to which data are used for local quality improvement and what facilitates the use of these data, with a particular focus on whether there are differences between frontline staff and managers. DESIGN: Cross-sectional nationwide survey study. SETTING, METHODS AND PARTICIPANTS: A previously validated, Swedish questionnaire regarding use of data from clinical quality registries was translated and emailed to frontline staff, mid-level managers and heads of departments (n=175) in all 30 hospital departments participating in the Danish Cardiac Rehabilitation Database. Data were analysed descriptively and through multiple linear regression. RESULTS: Survey response rate was 58% (101/175). Reports of registry use at department level (measured through an index comprising seven items; score min 0, max 7, where a low score indicates less use of data) varied significantly between groups of respondents: frontline staff mean score 1.3 (SD=2.0), mid-level management mean 2.4 (SD=2.3) and heads of departments mean 3.0 (SD=2.5), p=0.006. Overall, department level use of data was positively associated with higher perceived data quality and usefulness (regression coefficient=0.22, p=0.019), management request for data (regression coefficient=0.40, p=0.008) and personal motivation of the respondent (regression coefficient=1.63, p<0.001). Among managers, use of registry data was associated with data quality and usefulness (regression coefficient=0.43, p=0.027), and among frontline staff, reported data use was associated with management involvement in quality improvement work (regression coefficient=0.90, p=0.017) and personal motivation (regression coefficient=1.66, p<0.001). CONCLUSIONS: The findings suggest relatively sparse use of data in local quality improvement work. A complex interplay of factors seem to be associated with data use with varying aspects being of importance for frontline staff and managers.