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Nonexercise algorithms are cost-effective methods to estimate cardiorespiratory fitness (CRF), but the existing models have limitations in generalizability and predictive power. This study aims to improve the nonexercise algorithms using machine learning (ML) methods and data from US national population surveys.

(1) Characterize persistent hazards and inefficiencies in inpatient medication administration; (2) Explore cognitive attributes of medication administration tasks; and (3) Discuss strategies to reduce medication administration technology-related hazards.

Vaccines are crucial components of pandemic responses. Over 12 billion coronavirus disease 2019 (COVID-19) vaccines were administered at the time of writing. However, public perceptions of vaccines have been complex. We integrated social media and surveillance data to unravel the evolving perceptions of COVID-19 vaccines.

Prior authorization (PA) may be a necessary evil within the healthcare system, contributing to physician burnout and delaying necessary care, but also allowing payers to prevent wasting resources on redundant, expensive, and/or ineffective care. PA has become an "informatics issue" with the rise of automated methods for PA review, championed in the Health Level 7 International's (HL7's) DaVinci Project. DaVinci proposes using rule-based methods to automate PA, a time-tested strategy [...]

We conducted a systematic review to characterize and critically appraise developed prediction models based on structured electronic health record (EHR) data for adverse drug event (ADE) diagnosis and prognosis in adult hospitalized patients.

Estimating the deterioration paths of chronic hepatitis B (CHB) patients is critical for physicians' decisions and patient management. A novel, hierarchical multilabel graph attention-based method aims to predict patient deterioration paths more effectively. Applied to a CHB patient data set, it offers strong predictive utilities and clinical value.

Studies examining the effects of computerized order entry (CPOE) on medication ordering errors demonstrate that CPOE does not consistently prevent these errors as intended. We used the Agency for Healthcare Research and Quality (AHRQ) Network of Patient Safety Databases (NPSD) to investigate the frequency and degree of harm of reported events that occurred at the ordering stage, characterized by error type.

Understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED).

The development of phenotypes using electronic health records is a resource-intensive process. Therefore, the cataloging of phenotype algorithm metadata for reuse is critical to accelerate clinical research. The Department of Veterans Affairs (VA) has developed a standard for phenotype metadata collection which is currently used in the VA phenomics knowledgebase library, CIPHER (Centralized Interactive Phenomics Resource), to capture over 5000 phenotypes. The CIPHER standard improves upon existing phenotype library metadata [...]