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While computerized provider order entry (CPOE) has become standard for medication, laboratory, referral, and imaging ordering, use in surgical case requests has not been well-described. At a large county hospital, many surgical clinics used a variety of workflows for case requests, leading to data duplication and data storage outside of the electronic health record (EHR).We hypothesized that a provider-entered order-based case request (OBCR) tool would improve data entry efficiency and [...]

To measure hospital engagement in interoperable exchange of health-related social needs (HRSN) data.

Consumer involvement in the co-design of diabetes self-management smartphone apps is vital. This scoping review explored how consumers are involved in the co-design processes and methods and approaches guiding this research.Our review was guided by Arksey and O'Malley's five-stage framework, PRISMA-ScR guidelines, and Witteman and colleagues' 11-item user-centered design (UCD-11) framework. We searched literature across five databases and examined types of consumer involvement in co-design and frequency of methods and [...]

Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the impact of AI scribes on clinicians, patients and organizations.

To develop an electronic medical record (EMR) data processing tool that confers clinical context to machine learning (ML) algorithms for error handling, bias mitigation, and interpretability.

Observational data have been actively used to estimate treatment effect, driven by the growing availability of electronic health records (EHRs). However, EHRs typically consist of longitudinal records, often introducing time-dependent confounding that hinder the unbiased estimation of treatment effect. Inverse probability of treatment weighting (IPTW) is a widely used propensity score method since it provides unbiased treatment effect estimation and its derivation is straightforward. In this study, we aim to [...]

There is limited knowledge on how providers and patients in the emergency department (ED) use electronic health records (EHRs) to facilitate the diagnostic process. While EHRs can support diagnostic decision-making, EHR features that are not user-centered may increase the likelihood of diagnostic error. We aimed to identify how EHRs facilitate or impede the diagnostic process in the ED and to identify opportunities to reduce diagnostic errors and improve care quality.

[This corrects the article DOI: 10.1093/jamiaopen/ooaf007.].

To assess the capacity of a bespoke artificial intelligence (AI) process to help medical writers efficiently generate quality plain language summary abstracts (PLSAs).

Machine learning (ML) algorithms are promising tools for managing anemia in hemodialysis (HD) patients. However, their efficacy in predicting erythropoiesis-stimulating agents (ESAs) doses remains uncertain. This study aimed to evaluate the effectiveness of a contemporary artificial intelligence (AI) model in prescribing ESA doses compared to physicians for HD patients.