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The objective of this study is the conceptual design, implementation and evaluation of a system for generic, standard-compliant data transfer into electronic health records (EHRs). This includes patient data from clinical research and medical care that has been semantically annotated and enhanced with metadata. The implementation is based on the single-source approach. Technical and clinical feasibilities, as well as cost-benefit efficiency, were investigated in everyday clinical practice.

The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.

To study the newly adopted International Classification of Diseases 11th revision (ICD-11) and compare it to the International Classification of Diseases 10th revision (ICD-10) and International Classification of Diseases 10th revision-Clinical Modification (ICD-10-CM).

Accurate documentation in the medical record is essential for quality care; extensive documentation is required for reimbursement. At times, these 2 imperatives conflict. We explored the concordance of information documented in the medical record with a gold standard measure.

Computerized clinical decision support systems (CCDSSs) promise improvements in care quality; however, uptake is often suboptimal. We sought to characterize system use, its predictors, and user feedback for the Electronic Asthma Management System (eAMS)-an electronic medical record system-integrated, point-of-care CCDSS for asthma-and applied the GUIDES checklist as a framework to identify areas for improvement.

Use of medical scribes reduces clinician burnout by sharing the burden of clinical documentation. However, medical scribes are cost-prohibitive for most settings, prompting a growing interest in developing ambient, speech-based technologies capable of automatically generating clinical documentation based on patient-provider conversation. Through a systematic review, we aimed to develop a thorough understanding of the work performed by medical scribes in order to inform the design of such technologies.

Nursing time represents one of the highest costs for most health services. We conducted a systematic review of the literature on the impact of health information technology on nurses' time.

Predictive analytics are potentially powerful tools, but to improve healthcare delivery, they must be carefully integrated into healthcare organizations. Our objective was to identify facilitators, challenges, and recommendations for implementing a novel predictive algorithm which aims to prospectively identify patients with high preventable utilization to proactively involve them in preventative interventions.

This study aimed to explore the association between demographic variables, such as race and gender, and patient consent policy preferences for health information exchange as well as self-report by VHA enrollees of information continuity between Veterans Health Administration (VHA) and community non-VHA heath care providers.