TY - JOUR AB - Purpose Big Data is likely to have significant implications for the way in which services are planned, organised or delivered as well as the way in which we evaluate them. The increase in data availability creates particular challenges for evaluators in the field of integrated care and the purpose of this paper is to set out how we may usefully reframe these challenges in the longer term.Design/methodology/approach Using the characteristics of Big Data as defined in the literature, the paper develops a narrative around the data and research design challenges and how they influence evaluation studies in the field of care integration.Findings Big Data will have significant implications for how we conduct integrated care evaluations. In particular, dynamic modelling and study designs capable of accommodating new epistemic foundations for the phenomena of social organisations, such as emergence and feedback loops, are likely to be most helpful. Big Data also generates opportunities for exploratory data analysis approaches, as opposed to static model development and testing. Evaluators may find research designs useful that champion realist approaches or single-n designs.Originality/value This paper reflects on the emerging literature and changing practice of data generation and data use in health care. It draws on organisational theory and outlines implications of Big Data for evaluating care integration initiatives. VL - 27 IS - 3 SN - 1476-9018 DO - 10.1108/JICA-05-2019-0017 UR - https://doi.org/10.1108/JICA-05-2019-0017 AU - Kaehne Axel PY - 2019 Y1 - 2019/01/01 TI - Big Data and what it means for evaluating integrated care programmes T2 - Journal of Integrated Care PB - Emerald Publishing Limited SP - 249 EP - 258 Y2 - 2024/03/28 ER -