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There are several open access health datasets that promote effective retrospective comparative effectiveness research.

Clinical medicine relies on a strong research foundation in order to build the necessary evidence base to inform best practices and improve clinical care, however large-scale RCTs are expensive and sometimes unfeasible. Fortunately, there exists expansive data in the form of electronic health records (EHR).

There are several open access health datasets that promote effective retrospective comparative effectiveness research.

Electronic health records are increasingly useful for conducting secondary observational studies with power that rivals randomized controlled trials.

An Ideal Care System should incorporate fundamental elements of control engineering, such as effective and data-driven sensing, computation, actuation, and feedback.

MIMIC is a Medical Information Mart for Intensive Care and consists of several comprehensive data streams in the intensive care environment, in high levels of richness and detail, supporting complex signal processing and clinical querying that could permit early detection of complex problems, provide useful guidance on therapeutic interventions, and ultimately lead to improved patient outcomes.

Non-clinical factors make a significant contribution to an individual’s health and providing this data to clinicians could inform context, counseling, and treatments.

Electronic Health Records have become an essential tool in clinical research, both as a supplement to existing methods, but also in the growing domains of outcomes research and analytics.

Big Data is defined by its vastness, often with large highly granular datasets, which when combined with advanced analytical and statistical approaches, can power very convincing conclusions (Bourne in Journal of the American Medical Informatics Association 21(2):194–194, 2014). Herein perhaps lies the greatest challenge with using big data appropriately: understanding what is not available. In order to avoid false inferences of causality, it is critical to recognize the influences that might affect the outcome of interest, yet are not readily measurable.

In this chapter, the reader will learn how to convert a clinical question into a pertinent research question, which includes defining an appropriate study design, select a population sample, the exposure and outcome of interest.