At our third Lecture Series last week, Prof. Till Bärnighausen gave an interesting talk on „Integrating causal inference – from correlation to causation in ‘big data’ in health care and policy“.
The past 30 years have seen a revolution in causal inference in epidemiology and health policy research. New approaches to measurement of health-related data, such as sensors and cell phone data, as well as data linkage across many sources are massively increasing opportunities for causal evaluation of health policies and real-life interventions. The well-attended lecture by Prof. Bärnighausen described emerging methodological and data opportunities to establish causal impacts of health policies and interventions.
