Abstract Patients are increasingly leaving the hospital sooner and continuing therapies historically only administered in hospitals in their homes. One of the first of such therapies was the home administration of intravenous antibiotics, referred to as outpatient parenteral antimicrobial therapy (OPAT). Many patients discharged on OPAT require unplanned hospital readmissions and visits to the emergency department within the first 30 days of discharge. Because this population routinely suffers from a wide range of medical and surgical problems, it presents a unique opportunity to efficiently study a range of health outcomes in a vulnerable population. The emerging ubiquity of personal computing devices provides new opportunities to collect health-related data outside traditional clinical environments. The promise of collecting meaningful data increases if survey questions can be paired with “objective” information collected from sensors capable of collecting health-related data. To date, our CTSA hub at The University of Iowa has designed, tested and deployed custom m-health software to aggregate information from subjects using SMS, web-based tools, and mobile apps. We have also integrated information directly from sensors (step counters, blood pressure cuffs, scales, thermometers) into our custom software so that we can remotely collect objective health-related data from research subjects. In this proposal we will use our m-health platform to shift health- related measurements and data collection previously only available in hospitals into research subjects' homes. In addition, we will use our approach to measure health-related outcomes among patients discharged on OPAT. The overarching goal of our research is to develop easy-to-use informatics tools that are not disease specific. With these tools, we hope to enable the efficient collection of important clinical data from patients outside traditional research and clinical settings. First, we will assess the feasibility of using our mobile-health approach to gather clinical data from patients in their homes following discharge from the hospital on OPAT. Second, we will determine subject and researcher perspectives regarding the utility of our approach. Third, we will estimate the sample size necessary to power a study to determine the utility of remotely-collected patient-reported data for predicting hospital readmissions among patients discharged on OPAT. Completion of these aims will allow us to determine the potential for using m-health tools in a real-world setting to gather not only patient-reported outcomes, but also data from sensors to help answer a wide range of clinical research questions.