With the advancement of electronic health records (EHRs), health care systems are accumulating data at an alarming rate. Health care data (eg, clinical notes, prescriptions, insurance claims) are increasingly plentiful, accessible, and useful for quality and process improvement, program evaluation, and research. Yet, EHR data also can be chaotic. Such data are often unstandardized, contain inconsistently defined data elements, and tend to be dispersed throughout the medical record, making it difficult to find a desired data element. Improvement science, also called quality improvement (QI), and research studies share the goal of turning these data into insights that can be developed further into interventions that improve treatment options, care delivery, and overall patient health. To meet this objective, different types of projects (both improvement science and research) and different types of data are needed. However, these projects and data are not always immediately...

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