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Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS:  We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR [...]

Asthma is a common cause of morbidity and mortality in children. Predictive models may help providers tailor asthma therapies to an individual's exacerbation risk. The effectiveness of asthma risk scores on provider behavior and pediatric asthma outcomes remains unknown.

Medication discrepancies between clinical systems may pose a patient safety hazard. In this paper, we identify challenges and quantify medication discrepancies across transitions of care.

Critically ill patients are at greater risk of healthcare-associated infections (HAIs). The use of maintenance bundles helps to reduce this risk but also generates a rapid accumulation of complex data that is difficult to aggregate and subsequently act upon.

Concerns around opioid safety for patients living with chronic pain have led to a growing number of collaborative and multimodal pain care initiatives. A major challenge in these efforts has been identifying and engaging patients on high-risk opioid regimens in a timely manner.

Few community pharmacies have access to health information exchange (HIE) data. We conducted a first-of-its-kind usability evaluation of an HIE interface prototype (referred to throughout as the "HIE-Pioneer mock-up") developed with pharmacists and pharmacy technicians to aid future implementation in community pharmacies.

Analysis of health care real-world data (RWD) provides an opportunity to observe the actual patient diagnostic, treatment, and outcome events. However, researchers should understand the possible limitations of RWD. In particular, the dates in these data may be shifted from their actual values, which might affect the validity of study conclusions.

This study evaluated if medical doctors could identify more hemorrhage events during chart review in a clinical setting when assisted by an artificial intelligence (AI) model and medical doctors' perception of using the AI model.

Within the CAPABLE project the authors developed a multi-agent system that relies on a distributed architecture. The system provides cancer patients with coaching advice and supports their clinicians with suitable decisions based on clinical guidelines.