The tool was adapted to the needs and the organizational conditions of the local setting through a collaborative approach between the technology supplier and the adopters. However, prior understanding of statistics was helpful to be able to fully grasp the presented data. The data and the methodology in the analytics tool reflected the complexity of the clinical conditions treated but was presented through an interface that was easy to access and user friendly.

The value of the technology was associated with a clear need to make better use of existing data in QI.

Staff and managers deemed the technology to effectively support ongoing QI efforts by providing timely access to reliable data. The Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework guided the data collection and analysis. Data was collected through three focus group interviews conducted with 16 managers and staff. This qualitative study, based on focus group interviews, was conducted at a Swedish university hospital’s obstetric unit, which used an analytics tool for advanced performance measurement that gave timely and case mix adjusted feedback of performance data to support QI. This study aims to explore factors that influence the adoption of a technology-supported QI programme in an obstetric unit through a complexity informed framework. To enable professionals to use data in QI there is a need to better understand of how to handle this complexity. However, such technology may pose difficulties stemming from the complex interaction with the setting in which it is implemented. Technology for timely feedback of data has the potential to support quality improvement (QI) in health care.

Technology tools for data analysis