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Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population.

The change in performance of machine learning models over time as a result of temporal dataset shift is a barrier to machine learning-derived models facilitating decision-making in clinical practice. Our aim was to describe technical procedures used to preserve the performance of machine learning models in the presence of temporal dataset shifts.

Electronic prescriptions are often created and delivered electronically to the pharmacy while paper-based/handwritten prescriptions may be delivered to the pharmacy by the patients. These differences in the mode of creation and transmission of the two types of prescription could influence the rate at which outpatients fill new prescriptions of previously untried medications.

This study aimed to explore the effect of applying WeChat in the follow-up and health education of children after congenital heart disease (CHD) surgery during the coronavirus disease 2019 (COVID-19) epidemic.

Pilot-testing is important in standards development because it facilitates agile navigation of the gap between needs for and use of standards in real-world settings and can reveal the practicalities of implementation. As the implementation and use of health data standards are usually more complicated than anticipated, the Office of the National Coordinator for Health Information Technology (ONC) routinely oversees and organizes relevant pilot projects.

Electronic health records (EHRs) demand a significant amount of physician time for documentation, orders, and communication during care delivery. Resident physicians already work long hours as they gain experience and develop both clinical and socio-technical skills.

The American College of Obstetricians and Gynecologists (ACOG) provides numerous narrative documents containing formal recommendations and additional narrative guidance within the text. These guidelines are not intended to provide a complete "care pathway" for patient management, but these elements of guidance can be useful for clinical decision support (CDS) in obstetrical and gynecologic care and could be exposed within electronic health records (EHRs). Unfortunately, narrative guidelines do not easily translate [...]

Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data within research data repositories to support local and federated analyses. To address concerns regarding possible data quality (DQ) issues of hospital routine data compared with data specifically collected for scientific purposes, we have previously presented a data quality [...]

Suicide risk prediction models have been developed by using information from patients' electronic health records (EHR), but the time elapsed between model development and health system implementation is often substantial. Temporal changes in health systems and EHR coding practices necessitate the evaluation of such models in more contemporary data.

Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider [...]