General practitioners’ experiences of a data-driven quality development process

INTRODUCTION: Research shows that structured data use can optimise treatment in general practice clinics. This qualitative feasibility study evaluated a one-year intervention (DataSam) to assess whether increased use of population data can enhance type 2 diabetes treatment and workflows in general practice clinics. METHODS: Audio-recordings of visits from 12 clinics at baseline, six and 12 months and end-of-intervention semi-structured interviews (n = 14) explored data use, workflow changes and implementation challenges. The data analysis was inspired by qualitative content analysis. RESULTS: Clinics were positive about project activities and how structured data use enhanced management and patient overview while optimising treatment and prescribing practices. Most clinics experienced workflow improvements, such as nurses taking on more responsibilities and heightened staff skills, knowledge, job satisfaction and confidence in data-driven decision-making, medications and guidelines. However, approximately half of the clinics faced some implementation challenges, including technical issues and time constraints. Furthermore, some raised concerns about overtreatment, data misuse and de-prioritisation of other diagnoses. CONCLUSIONS: DataSam emphasises the potential of population data to optimise patient care, though further attention to implementation is needed. FUNDING: This study received an internal grant from Steno Diabetes. Centre Copenhagen. TRIAL REGISTRATION: Registered as "not required approval" with the Regional Ethics Committee of the Capital Region (F-22073139).