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Surgical registries play a crucial role in clinical knowledge discovery, hospital quality assurance, and quality improvement. However, maintaining a surgical registry requires significant monetary and human resources given the wide gamut of information abstracted from medical records ranging from patient co-morbidities to procedural details to post-operative outcomes. Although natural language processing (NLP) methods such as pretrained language models (PLMs) have promised automation of this process, there are yet substantial barriers [...]

Physician burnout in the US has reached crisis levels, with one source identified as extensive after-hours documentation work in the electronic health record (EHR). Evidence has illustrated that physician preferences for after-hours work vary, such that after-hours work may not be universally burdensome. Our objectives were to analyze variation in preferences for after-hours documentation and assess if preferences mediate the relationship between after-hours documentation time and burnout.

To describe the prevalence and trends in the use of social media over time and explore whether social media use is related to better self-care efficacy and thus related to better mental health among United States older adults with multimorbidity.

Accurately identifying clinical phenotypes from Electronic Health Records (EHRs) provides additional insights into patients' health, especially when such information is unavailable in structured data. This study evaluates the application of OpenAI's Generative Pre-trained Transformer (GPT)-4 model to identify clinical phenotypes from EHR text in non-small cell lung cancer (NSCLC) patients. The goal was to identify disease stages, treatments and progression utilizing GPT-4, and compare its performance against GPT-3.5-turbo, Flan-T5-xl, Flan-T5-xxl [...]

To evaluate the use of patient portal messaging to recruit individuals historically underrepresented in biomedical research (UBR) to the All of Us Research Program (AoURP) at a single recruitment site.

The aim of this study was to investigate GPT-3.5 in generating and coding medical documents with International Classification of Diseases (ICD)-10 codes for data augmentation on low-resource labels.

Clinical research networks facilitate collaborative research, but data sharing remains a common barrier.

To address the challenges of sharing clinical research data through the implementation of cloud-based virtual desktops, enhancing collaboration among researchers while maintaining data security.

Accelerating demand for patient messaging has impacted the practice of many providers. Messages are not recommended for urgent medical issues, but some do require rapid attention. This presents an opportunity for artificial intelligence (AI) methods to prioritize review of messages. Our study aimed to highlight some patient portal messages for prioritized review using a custom AI system integrated into the electronic health record (EHR).

We evaluated the effectiveness and implementability of a standardized EHR-integrated handoff report to support intraoperative handoffs.