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Patient cohorts generated by machine learning can be enhanced with clinical knowledge to increase translational value and provide a practical approach to patient segmentation based on a mix of medical, behavioral, and social factors.

Therapeutic duplication, the presence of multiple agents prescribed for the same indication without clarification for when each should be used, can contribute to serious medical errors. Joint Commission standards require that orders contain clarifying information about when each order should be given. In our system, as needed (PRN) acetaminophen and ibuprofen orders are major contributors to therapeutic duplication.

Implementing an electronic health record (EHR) is one of the most disruptive operational tasks a health system can undergo. Despite anecdotal reports of adverse events around the time of EHR implementations, there is limited corroborating research, particularly in pediatrics. We utilized data from Solutions for Patient Safety (SPS), a network of 145+ children's hospitals that share data and protocols to reduce harm in pediatric care delivery, to study the impact [...]

A growing body of literature has linked usability limitations within electronic health records (EHRs) to adverse outcomes which may in turn affect EHR system transitions. NewYork-Presbyterian Hospital, Columbia University College of Physicians and Surgeons (CU), and Weill Cornell Medical College (WC) are a tripartite organization with large academic medical centers that initiated a phased transition of their EHRs to one system, EpicCare.

Pseudorandomized testing can be applied to perform rigorous yet practical evaluations of clinical decision support tools. We apply this methodology to an interruptive alert aimed at reducing free-text prescriptions. Using free-text instead of structured computerized provider order entry elements can cause medication errors and inequity in care by bypassing medication-based clinical decision support tools and hindering automated translation of prescription instructions.

Acute care ophthalmic clinics often suffer from inefficient triage, leading to suboptimal patient access and resource utilization. This study reports the preliminary results of a novel, symptom-based, patient-directed, online triage tool developed to address the most common acute ophthalmic diagnoses and associated presenting symptoms.

We sought to create a digital application to support clinicians in empiric and pathogen-directed antibiotic ordering based on local susceptibility patterns and evidence-based treatment durations, thereby promoting antimicrobial stewardship.

In Taiwan, the number of confirmed cases of coronavirus disease 2019 (COVID-19) has risen significantly in May 2021. The second wave of the epidemic occurred in May 2022. mHealth (mobile health, social media communities) and eHealth (electronic health, Hospital Information System) can play an important role in this pandemic by minimizing the spread of the virus, leveraging health care providers' time, and alleviating the challenges of medical education.

Technological improvements and, subsequently, the federal 21st Century Cures Act have resulted in increased access to and interoperability of electronic protected health information (ePHI). These not only have many benefits, but also have created unique challenges for privacy and confidentiality for adolescent patients. The inability to granularly protect sensitive data and a lack of standards have resulted in limited confidentiality protection and inequitable access to health information.

Musculoskeletal pain is common in the Veterans Health Administration (VHA), and there is growing national use of chiropractic services within the VHA. Rapid expansion requires scalable and autonomous solutions, such as natural language processing (NLP), to monitor care quality. Previous work has defined indicators of pain care quality that represent essential elements of guideline-concordant, comprehensive pain assessment, treatment planning, and reassessment.