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Electronic health records (EHRs) contain valuable patient information, yet certain aspects of care remain infrequently documented and difficult to extract. Identifying these rarely documented elements requires advanced informatics approaches to uncover clinical documentation patterns that would otherwise remain inaccessible for research and quality improvement.

Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the impact of AI scribes on clinicians, patients and organizations.

Electronic health record (EHR) usage measures may quantify physician activity at scale and predict practice settings with high risk for physician burnout, but their relation to experiences are poorly understood.

Background While Electronic Health Record (EHR)-based tools for refugee health screening exist, supports for other immigrant children has lagged. Reasons include lack of time, difficulty determining screening eligibility, and lack of awareness of screening recommendations. EHR-based tools to promote immigrant child health screening (ICHS) can address these challenges, but guidance is needed for tools that are usable by clinicians and acceptable to immigrant families. Objectives Develop useful EHR-based tools to [...]

The patient-facing ASTHMAXcel mobile platform has been linked to improved asthma knowledge, decreased asthma-related healthcare utilization (emergency department (ED) visits, hospitalizations), and reduced prednisone use among adult and pediatric patient populations.

Approximately 10% of patients have a documented penicillin "allergy"; however, up to 95% have subsequent negative testing. These patients may receive suboptimal antibiotics, leading to longer hospitalizations and higher costs, rates of resistant and nosocomial infections, and all-cause mortality. To mitigate these risks in children, we implemented an inpatient penicillin allergy delabeling protocol and integrated into the electronic health record (EHR) through a mixed methods approach of clinical decision support [...]

Cancer staging is integral to ensuring cancer patients receive appropriate risk adapted therapy. Discrete cancer staging using a structured staging form helps ensure accurate staging, provides a single source of truth for staging information and allows for reporting to regulatory authorities. Our institution created pediatric oncology specific discrete staging forms that have been shared with the broader Epic community. By November 2023, baseline utilization of the staging form for patients [...]

Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness. Guidelines recommend screening for infants with gestational age at birth < 31 weeks or birthweight ≤ 1500g. However, ensuring timely screening during readmissions after birth is challenging.

Objectives Improve concordance between patient end-of-life preferences and code status orders by incorporating data from a state registry with Clinical Decision Support (CDS) within the electronic health record (EHR) to preserve patient autonomy and ensure that patients receive care that aligns with their wishes. Methods Leveraging a Health Information exchange (HIE) interface between the New York State Medical Orders for Life-Sustaining Treatment (eMOLST) registry and the EHR of our academic [...]

This systematic literature review aims to critically evaluate the use of mathematical and simulation models within emergency departments (EDs) and assess their potential to improve the quality of care. This review emphasises the critical need for quality enhancement in healthcare systems, specifically focusing on EDs. This review incorporates studies investigating the quality of care provided in ED settings, employing assorted mathematical and simulation models for adult populations. Based on the [...]