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[This corrects the article DOI: 10.1093/jamiaopen/ooab119.].

To evaluate whether a natural language processing (NLP) algorithm could be adapted to extract, with acceptable validity, markers of residential instability (ie, homelessness and housing insecurity) from electronic health records (EHRs) of 3 healthcare systems.

The coronavirus disease 2019 pandemic has resulted in large-scale changes to incorporate telemedicine for the delivery of care. People with cystic fibrosis (CF) have care considerations that pose challenges to telemedicine; they include frequent visits for pulmonary disease progression, medication management, and evaluation by a multidisciplinary team of providers. We share our center's experience with video visits replacing in-person clinic evaluation, using quality improvement strategies to create a replicable workflow [...]

Clinical decision support systems (CDSSs) use alerts to enhance medication safety and reduce medication error rates. A major challenge of medication alerts is their low acceptance rate, limiting their potential benefit. A structured overview about modulators influencing alert acceptance is lacking. Therefore, we aimed to review and compile qualitative and quantitative modulators of alert acceptance and organize them in a comprehensive model.

In 2009, Schattauer Verlag in Stuttgart, Germany first published the Applied Clinical Informatics (ACI) Journal. ACI has served since its inception as an official journal of the International Medical Informatics Association. Later, the American Medical Informatics Association and the European Federation for Medical Informatics named ACI as an official journal. This manuscript describes the history of the journal from its inception to present day including publication measures, challenges, and successes.

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.

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 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.

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.