Clinicians involved in clinical care generate daily volumes of important data. This data is important for continuity of care, referrals to specialists and back to the patient's medical home. The same data can be used to generate alerts to improve the practice and to generate care activities to ensure that all appropriate care services are provided for the patient given their known medical histories using electronic quality (eQuality) monitoring. For many years we have used patient records as a data source for human abstraction of clinical research data. With the advent of electronic health record (EHR) data we can now make use of computable EHR data that can perform retrospective research studies more rapidly and lower the activation energy necessary to ask the next important question using electronic studies (eStudies). Barriers to these eStudies include: the lack of interoperable data between and among practices, the lack of computable definitions of measures, the lack of training of health professionals to use Ontology based Informatics tools that allow the execution of this type of logic, common methods need to be developed to distribute computable best practice rules to ensure rapid dissemination of evidence, better translating research into practice.