Brian W. Patterson
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View article: Evaluating clinical AI summaries with large language models as judges
Evaluating clinical AI summaries with large language models as judges Open
Electronic Health Records (EHRs) contain vast clinical data that are difficult for providers to synthesize. Generative AI with Large Language Models (LLMs) can summarize records to reduce cognitive burden, but ensuring accuracy requires re…
View article: Eliminating the AI digital divide by building local capacity
Eliminating the AI digital divide by building local capacity Open
Over the past few years, health delivery organizations (HDOs) have been adopting and integrating AI tools, including clinical tools for tasks like predicting risk of inpatient mortality and operational tools for clinical documentation, sch…
View article: Correction: Toward Real-Time Discharge Volume Predictions in Multisite Health Care Systems: Longitudinal Observational Study
Correction: Toward Real-Time Discharge Volume Predictions in Multisite Health Care Systems: Longitudinal Observational Study Open
[This corrects the article DOI: 10.2196/63765.].
View article: A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice
A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice Open
We provide a publicly available framework and protocols to help safely implement ambient AI in health care. Innovations include an embedded pragmatic trial design, human factors engineering, compliance-driven feedback loops, and real-time …
View article: Evaluation of falls detected by natural language processing algorithm and not coded external cause of morbidity
Evaluation of falls detected by natural language processing algorithm and not coded external cause of morbidity Open
Objective Falls are a leading cause of morbidity and mortality among older adults. Common methods for identifying fall-related ED visits within both claims and electronic health record datasets rely on diagnosis code-based definitions, whi…
View article: Toward Real-Time Discharge Volume Predictions in Multisite Health Care Systems: Longitudinal Observational Study
Toward Real-Time Discharge Volume Predictions in Multisite Health Care Systems: Longitudinal Observational Study Open
Background Emergency department (ED) admissions are one of the most critical decisions made in health care, with 40% of ED visits resulting in inpatient hospitalization for Medicare patients. A main challenge with the ED admissions process…
View article: Automating Evaluation of AI Text Generation in Healthcare with a Large Language Model (LLM)-as-a-Judge
Automating Evaluation of AI Text Generation in Healthcare with a Large Language Model (LLM)-as-a-Judge Open
Electronic Health Records (EHRs) store vast amounts of clinical information that are difficult for healthcare providers to summarize and synthesize relevant details to their practice. To reduce cognitive load on providers, generative AI wi…
View article: Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score
Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score Open
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and…
View article: Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study
Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study Open
Background Polypharmacy, the concurrent use of multiple medications, is prevalent among older adults and associated with increased risks for adverse drug events including falls. Deprescribing, the systematic process of discontinuing potent…
View article: Current and future state of evaluation of large language models for medical summarization tasks
Current and future state of evaluation of large language models for medical summarization tasks Open
Large Language Models have expanded the potential for clinical Natural Language Generation (NLG), presenting new opportunities to manage the vast amounts of medical text. However, their use in such high-stakes environments necessitate robu…
View article: Development and Validation of the Provider Documentation Summarization Quality Instrument for Large Language Models
Development and Validation of the Provider Documentation Summarization Quality Instrument for Large Language Models Open
As Large Language Models (LLMs) are integrated into electronic health record (EHR) workflows, validated instruments are essential to evaluate their performance before implementation. Existing instruments for provider documentation quality …
View article: A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice
A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice Open
Background Ambient artificial intelligence (AI) offers the potential to reduce documentation burden and improve efficiency through clinical note generation. Widespread adoption, however, remains limited due to challenges in electronic heal…
View article: Revisits, Readmission, and Mortality From Emergency Department Admissions for Older Adults With Vague Presentations: Longitudinal Observational Study
Revisits, Readmission, and Mortality From Emergency Department Admissions for Older Adults With Vague Presentations: Longitudinal Observational Study Open
Background Older adults (65 years and older) often present to the emergency department (ED) with an unclear need for hospitalization, leading to potentially harmful and costly care. This underscores the importance of measuring the trade-of…
View article: Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study (Preprint)
Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study (Preprint) Open
BACKGROUND Polypharmacy, the concurrent use of multiple medications, is prevalent among older adults and associated with increased risks for adverse drug events including falls. Deprescribing, the systematic process of discontinuing poten…
View article: Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study
Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study Open
Background Electronic health records (EHRs) and routine documentation practices play a vital role in patients’ daily care, providing a holistic record of health, diagnoses, and treatment. However, complex and verbose EHR narratives can ove…
View article: Outcomes and Cost-Effectiveness of an EHR-Embedded AI Screener for Identifying Hospitalized Adults at Risk for Opioid Use Disorder
Outcomes and Cost-Effectiveness of an EHR-Embedded AI Screener for Identifying Hospitalized Adults at Risk for Opioid Use Disorder Open
Hospitalized adults with opioid use disorder (OUD) are at high risk for adverse events and rehospitalizations. This pre-post quasi-experimental study evaluated whether an AI-driven OUD screener embedded in the electronic health record (EHR…
View article: Prompt engineering with a large language model to assist providers in responding to patient inquiries: a real-time implementation in the electronic health record.
Prompt engineering with a large language model to assist providers in responding to patient inquiries: a real-time implementation in the electronic health record. Open
Future studies should explore strategies for optimizing the integration of LLMs into the provider workflow to maximize both usability and effectiveness.
View article: Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review
Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review Open
Large Language Models have advanced clinical Natural Language Generation, creating opportunities to manage the volume of medical text. However, the high-stakes nature of medicine requires reliable evaluation, which remains a challenge. In …
View article: A rapid noninvasive wearable device for assessing cardiac troponin I level
A rapid noninvasive wearable device for assessing cardiac troponin I level Open
Objective: Chest pain, a common emergency department presentation, requires rapid evaluation. The current gold standard of care is serial troponin measurements from blood draws along with an electrocardiogram and clinical presentation. How…
View article: Considerations for Developing Patient-centered Clinical Decision Support: Preventing Older Adult Falls after Emergency Department Visits
Considerations for Developing Patient-centered Clinical Decision Support: Preventing Older Adult Falls after Emergency Department Visits Open
To support the ongoing adaptation and implementation of an Emergency Department (ED)-based clinical decision support (CDS) tool to prevent future falls, we interviewed older adults ( n = 15) during their ED stay. We elicited their feedback…
View article: Influence of time‐to‐diagnosis on time‐to‐percutaneous coronary intervention for emergency department ST‐elevation myocardial infarction patients: Time‐to‐electrocardiogram matters
Influence of time‐to‐diagnosis on time‐to‐percutaneous coronary intervention for emergency department ST‐elevation myocardial infarction patients: Time‐to‐electrocardiogram matters Open
Reducing D2E is associated with a shorter E2B. Targeting D2E reduction in patients currently diagnosed during triage (11-30 min) may be the greatest opportunity to improve D2B and could enable 24.9% more ED STEMI patients to achieve timely…
View article: Shorter Door-to-ECG Time Is Associated with Improved Mortality in STEMI Patients
Shorter Door-to-ECG Time Is Associated with Improved Mortality in STEMI Patients Open
Background: Delayed intervention for ST-segment elevation myocardial infarction (STEMI) is associated with higher mortality. The association of door-to-ECG (D2E) with clinical outcomes has not been directly explored in a contemporary US-ba…
View article: Call me Dr Ishmael: trends in electronic health record notes available at emergency department visits and admissions
Call me Dr Ishmael: trends in electronic health record notes available at emergency department visits and admissions Open
Objectives Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over …
View article: Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study (Preprint)
Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study (Preprint) Open
BACKGROUND Electronic health records (EHRs) and routine documentation practices play a vital role in patients’ daily care, providing a holistic record of health, diagnoses, and treatment. However, complex and verbose EHR narratives can ov…
View article: Development of a Human Evaluation Framework and Correlation with Automated Metrics for Natural Language Generation of Medical Diagnoses
Development of a Human Evaluation Framework and Correlation with Automated Metrics for Natural Language Generation of Medical Diagnoses Open
In the evolving landscape of clinical Natural Language Generation (NLG), assessing abstractive text quality remains challenging, as existing methods often overlook generative task complexities. This work aimed to examine the current state …
View article: Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score
Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score Open
OBJECTIVE Early detection of clinical deterioration using machine learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and w…
View article: Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department–Based Clinical Decision Support Tool to Prevent Future Falls
Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department–Based Clinical Decision Support Tool to Prevent Future Falls Open
Background Clinical decision support (CDS) tools that incorporate machine learning–derived content have the potential to transform clinical care by augmenting clinicians’ expertise. To realize this potential, such tools must be designed to…
View article: Call Me Dr. Ishmael: Trends in Electronic Health Record Notes Available at ED Visits and Admissions
Call Me Dr. Ishmael: Trends in Electronic Health Record Notes Available at ED Visits and Admissions Open
Objective Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over t…
View article: WITHDRAWN: Prompt Engineering GPT-4 to Answer Patient Inquiries: A Real-Time Implementation in the Electronic Health Record across Provider Clinics
WITHDRAWN: Prompt Engineering GPT-4 to Answer Patient Inquiries: A Real-Time Implementation in the Electronic Health Record across Provider Clinics Open
Withdrawal Statement The authors have withdrawn their manuscript owing to needing additional internal review. Therefore, the authors do not wish this work to be cited as a reference for the project. If you have any questions, please contac…