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Recent advances in computer vision and wearable technology have created an opportunity to introduce mobile therapy systems for autism spectrum disorders (ASD) that can respond to the increasing demand for therapeutic interventions; however, feasibility questions must be answered first.

Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.

This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data.

Patient portals specifically designed for the inpatient setting have significant potential to improve patient care. However, little is known about how the users of this technology, the patients, may interact with the inpatient portals. As a result, hospitals have limited ability to design approaches that support patient use of the portal.

Mobile stroke units (MSUs) reduce time to thrombolytic therapy in acute ischemic stroke. These units are widely used, but the clinical information systems underlying MSU operations are understudied.

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use.

Clinical trials are an important research method for improving medical knowledge and patient care. Multiple international and national guidelines stipulate the need for data quality and assurance. Many strategies and interventions are developed to reduce error in trials, including standard operating procedures, personnel training, data monitoring, and design of case report forms. However, guidelines are nonspecific in the nature and extent of necessary methods.

Clinical decision support systems (CDSS) for cervical cancer prevention are generally limited to identifying patients who are overdue for their next routine/next screening, and they do not provide recommendations for follow-up of abnormal results. We previously developed a CDSS to automatically provide follow-up recommendations based on the American Society of Colposcopy and Cervical Pathology (ASCCP) guidelines for women with both previously normal and abnormal test results leveraging information available in [...]

In 2015, the German Federal Ministry of Education and Research initiated a large data integration and data sharing research initiative to improve the reuse of data from patient care and translational research. The Observational Medical Outcomes Partnership (OMOP) common data model and the Observational Health Data Sciences and Informatics (OHDSI) tools could be used as a core element in this initiative for harmonizing the terminologies used as well as facilitating [...]