Across the United States, only 3% of eligible patients participate in clinical research. One challenge of engaging patients in clinical research is that most people obtain their healthcare outside of major Academic Medical Centers (AMCs), whereas most research occurs within major AMCs. This situation limits the number and diversity of research participants. To increase both the number and diversity of research participants, and the number of clinical practices participating in research, we propose a technology-based model architecture which makes minimal risk clinical research accessible and scalable outside of AMCs. Our approach, Precision Accelerated Clinically Embedded Research (PACER), leverages emerging health care computing technologies to automatically identify eligible patients for a particular study and to incorporate a question or low-risk physical exam seamlessly into the clinical workflow with minimal time commitment for clinicians, staff, and patients. The PACER model is inspired by a thought experiment: “If you could ask every person with a particular medical condition or on a certain medication who walked into a doctor’s office anywhere in the country today just one question, how would research change?” Recent advances in health care information technology, such as the Fast Health Interoperability Resources (FHIR) standards and Clinical Decision Support (CDS) Hooks, make it possible to support the PACER approach across organizations and disparate EHRs. Besides describing the PACER model architecture and how it could be implemented, we identify potential ethical issues, as well as sociotechnical aspects of implementing PACER that should be considered in future work.