The Right Stuff: Getting the right data at the right time and using that data to drive evidence-based practice and policy

When researchers are embedded within healthcare systems and collaborate with practitioners and operational leaders, they may be able to rapidly identify problems and opportunities that can be addressed to improve quality and affordability. While other industries have well-developed data exploration processes (e.g., banking), healthcare is still developing its methods with widely varying data sources, huge quantities of unstructured data, uncertain precision in measurement, uncertainties about data quality, and complicated and stringent regulations and policies on data access. In recognition of these challenges, the AcademyHealth Learning Health System (LHS) Interest Group (In 2021, Learning Health Systems journal established a formal relationship with AcademyHealth, serving as the official journal of its LHS Interest Group.) released a call for papers in June 2023 to focus on challenges encountered by investigators related to the use of real-world data in embedded research.

We use the term “embedded researcher” to characterize a broad range of people well-trained in research methods using real-world data. Being located inside a health system, they often have privileged access to data and the practitioners who may be observing new situations, problems, or opportunities for improvement. Unlike colleagues only involved in internal quality improvement efforts, embedded researchers also seek to broadly share their findings and create generalizable knowledge. The sharing is less focused on the specific findings—too many things may be unique about the setting, people, and other factors to be directly generalizable. The challenges faced and techniques used to overcome them, however, may offer important lessons for other embedded researchers.

As LHSs mature and internally tackle increasingly complex problems with embedded research, the challenges presented in using real-world data for locally applied health services research are important to understand. Taken together, the papers in this Special Issue offer insights into the frontiers of embedded research as LHSs embark on their own learning journey. Accelerating the transformation of data to knowledge requires an understanding of the underlying data and techniques needed to draw useful lessons from the data. Sharing experiences across teams and settings will help others in anticipating and addressing the challenges they are likely to encounter.