Big data promises to revolutionize the way healthcare is delivered: how to measure its impact?
In the BigMedilytics project, the Erasmus University studied the uptake of big data innovations in healthcare. As a result, the best big data technology and healthcare policy practices have been defined covering aspects such as big data policy, new business models, regulations, and technology components.
To this end, researchers from Erasmus University have created a series of videos to share the lessons learned in ten different topics in the framework of the project. The videos, that will be disseminated during the following weeks, will offer a valuable guideline for different kinds of stakeholders across the healthcare and data value chain.
In the first video released, Dr. Sandra Sülz, assistant professor at Erasmus School of Health Policy & Management, explains how big data projects could demonstrate that big data can revolutionize the way healthcare is delivered. This requires a clear understanding of how to measure the cause-and-effect mechanisms. In the video, a conceptual model is presented that enables the identification of a sequence of cause-and-effect relations.
In conclusion, three main lessons can be learned regarding the impact of big data innovations in healthcare:
- To measure the impact of Big data innovations one needs to identify and quantify causal effects.
- Big data innovations do not improve healthcare directly, but improve the information upon which decisions are made.
- Impact can only be attributed to Big data innovations if the counterfactual scenario is known of what had happened if the Big data innovation had not been developed and implemented.