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Given the inequities in access to health care resources like COVID-19 vaccination, health systems should carefully consider how to reach underrepresented groups. Reflecting on vaccine rollout efforts holds insight on the role of community engagement and informatics support in promoting health equity.

 Existing monitoring of machine-learning-based clinical decision support (ML-CDS) is focused predominantly on the ML outputs and accuracy thereof. Improving patient care requires not only accurate algorithms but also systems of care that enable the output of these algorithms to drive specific actions by care teams, necessitating expanding their monitoring.

Improving child health using health information technology (IT) requires a unique set of functionalities that are built into the electronic health record (EHR) and are used to support patient care. In this article, we review and discuss the milestones preceding the development of a new child health EHR standard and describe the salient features of this contemporary standard.

In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures.

Recognizing that alert fatigue poses risks to patient safety and clinician wellness, there is a growing emphasis on evaluation and governance of electronic health record clinical decision support (CDS). This is particularly critical for interruptive alerts to ensure that they achieve desired clinical outcomes while minimizing the burden on clinicians. This study describes an improvement effort to address a problematic interruptive alert intended to notify clinicians about patients needing coronavirus [...]

Clinical decision support systems (CDSS) can enhance medical decision-making by providing targeted information to providers. While they have the potential to improve quality of care and reduce costs, they are not universally effective and can lead to unintended harm.

 Despite mortality benefits, only 19.9% of U.S. adults are fully vaccinated against the coronavirus disease 2019 (COVID-19). The inpatient setting is an opportune environment to update vaccinations, and inpatient electronic health record (EHR) alerts have been shown to increase vaccination rates.

We developed a prototype patient decision aid, EyeChoose, to assist college-aged students in selecting a refractive surgery. EyeChoose can educate patients on refractive errors and surgeries, generate evidence-based recommendations based on a user's medical history and personal preferences, and refer patients to local refractive surgeons.

Children with medical complexity (CMC) are uniquely vulnerable to medication errors and preventable adverse drug events because of their extreme polypharmacy, medical fragility, and reliance on complicated medication schedules and routes managed by undersupported family caregivers. There is an opportunity to improve CMC outcomes by designing health information technologies that support medication administration accuracy, timeliness, and communication within CMC caregiving networks.

Electronic health records are a significant contributing factor in clinician burnout, which negatively impacts patient care.