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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.

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.

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.

Many critically ill children are initially evaluated in front-line settings by clinicians with variable pediatric training before they are transferred to a pediatric intensive care unit (PICU). Because clinicians learn from past performance, communicating outcomes of patients back to front-line clinicians who provide pediatric emergency care could be valuable; however, referring clinicians do not consistently receive this important feedback.

The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital.

Provider prescribing practices contribute to an excess of opioid-related deaths in the United States. Clinical guidelines exist to assist providers with improving prescribing practices and promoting patient safety. Clinical decision support systems (CDSS) may promote adherence to these guidelines and improve prescribing practices. The aim of this project was to improve opioid guideline adherence, prescribing practices, and rates of opioid-related encounters through the implementation of an opioid CDSS.

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.

Molecular tumor boards (MTBs) cope with the complexity of an increased usage of genome sequencing data in cancer treatment. As for most of these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process is often performed manually and therefore time consuming and complex due to the heterogeneous and challenging dataset.