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We describe the evaluation of a system to create hospital progress notes using voice and electronic health record integration to determine if note timeliness, quality, and physician satisfaction are improved.

To demonstrate and test the validity of a novel deep-learning-based system for the automated detection of pulmonary nodules.

This quality improvement project evaluated the impact of a tailored, evidence-based training strategy on advanced electronic medical record (EMR) use for Veterans Administration (VA) clinicians experienced in using the EMR. After developing the curriculum, an online needs assessment tool evaluated 20 clinicians' competency gaps. Responses were used to prioritize clinicians' training needs. Clinician informaticists then provided 2-4 h of tailored training to groups of 1-5 clinicians. Compared with baseline scores [...]

Effective sign-outs involve verbal communication supported by written or electronic documentation. We investigated the clinical content overlap between sign-out documentation and face-to-face verbal sign-out communication.

There is little readily available data about the size and characteristics of the healthcare information technology workforce. We sought to update a previous description of the size, growth, and characteristics of this workforce based on the Healthcare Information Management Systems Society (HIMSS) Analytics® Database, a resource that includes hospital size, number of beds, amount of staffing, and an eight-stage model of electronic health record adoption (Electronic Medical Record Adoption Model [...]

The aim of this work is to leverage relational information extracted from biomedical literature using a novel synthesis of unsupervised pretraining, representational composition, and supervised machine learning for drug safety monitoring.

Patient access to health information using electronic patient portals is increasingly common. Portal use has the potential to improve patients' engagement with their health and is particularly important for patients with chronic illness; however, patients' abilities, attitudes, and use of portals are poorly understood.

To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoing research and identify open challenges in building deep learning models of EHRs.

The eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built [...]