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Allowing students to access and document in electronic medical records (eMRs) during clinical placements is viewed as critical for ensuring that graduates have a high level of digital proficiency prior to entering the workforce. Limited studies have explored student access to eMRs in health disciplines outside of medicine and nursing.

Helping parents quit smoking is a public health priority. However, parents are rarely, if ever, offered tobacco use treatment through pediatric settings. Clinical decision support (CDS) systems developed for the workflows of pediatric primary care may support consistent screening, treatment, and referral.

The widespread adoption of electronic health records and a simultaneous increase in regulatory demands have led to an acceleration of documentation requirements among clinicians. The corresponding burden from documentation requirements is a central contributor to clinician burnout and can lead to an increased risk of suboptimal patient care.

Electronic clinical quality measures (eCQMs) from electronic health records (EHRs) are a key component of quality improvement (QI) initiatives in small-to-medium size primary care practices, but using eCQMs for QI can be challenging. Organizational strategies are needed to effectively operationalize eCQMs for QI in these practice settings.

Order sets are a clinical decision support (CDS) tool in computerized provider order entry systems. Order set use has been associated with improved quality of care. Particularly related to opioids and pain management, order sets have been shown to standardize and reduce the prescription of opioids. However, clinician-level barriers often limit the uptake of this CDS modality.

Within the German "Network University Medicine," a portal is to be developed to enable researchers to query on novel coronavirus disease 2019 (COVID-19) data from university hospitals for assessing the feasibility of a clinical study.

Inpatient portals are recognized to provide benefits for both patients and providers, yet the process of provisioning tablets to patients by staff has been difficult for many hospitals.

A learning health care system (LHS) uses routinely collected data to continuously monitor and improve health care outcomes. Little is reported on the challenges and methods used to implement the analytics underpinning an LHS. Our aim was to systematically review the literature for reports of real-time clinical analytics implementation in digital hospitals and to use these findings to synthesize a conceptual framework for LHS implementation.

Anesthesiologists integrate numerous variables to determine an opioid dose that manages patient nociception and pain while minimizing adverse effects. Clinical dashboards that enable physicians to compare themselves to their peers can reduce unnecessary variation in patient care and improve outcomes. However, due to the complexity of anesthetic dosing decisions, comparative visualizations of opioid-use patterns are complicated by case-mix differences between providers.

Hospitals are increasingly replacing pagers with clinical texting systems that allow users to use smartphones to send messages while maintaining compliance for privacy and security. As more institutions adopt such systems, the need to understand the impact of such transitions on team communication becomes ever more significant.