Search AMIA.org

The Enhanced EHR-facilitated Cancer Symptom Control (E2C2) Trial is a pragmatic trial testing a collaborative care approach for managing common cancer symptoms. There were challenges in identifying cancer site and metastatic status.This study compares three different approaches to determine cancer site and six strategies for identifying the presence of metastasis using EHR and cancer registry data.The E2C2 cohort included 50,559 patients seen in the medical oncology clinics of a large [...]

Human immunodeficiency virus (HIV) remains a significant global health challenge, especially in Europe, including Italy, where it affects thousands. Antiretroviral therapy (ART) has turned HIV into a manageable chronic condition, improving the quality of life and life expectancy for people living with HIV (PLWH). Enhancing health-related quality of life (HRQoL) is essential, as it positively influences therapy adherence.The objective of the study was to evaluate the impact of the AURORA [...]

Adoption of electronic health record (EHR)-based clinical decision support tools in community-based health centers might increase the provision of indicated cancer screening orders. We examined: (1) if the use of the care gaps smartset (CGS), an EHR tool that expedites ordering care, is associated with colorectal/cervical cancer (CRC/CVC) screening order rates; and (2) how selected implementation strategies, barriers, and facilitators impact CGS use.Within a sequential mixed methods design, we used [...]

To quantify differences between (1) stratifying patients by predicted disease onset risk alone and (2) stratifying by predicted disease onset risk and severity of downstream outcomes. We perform a case study of predicting sepsis.

This study evaluates the integration of electronic health records (EHRs) and natural language processing (NLP) with large language models (LLMs) to enhance healthcare data management and patient care, focusing on using advanced language models to create secure, Health Insurance Portability and Accountability Act-compliant synthetic patient notes for global biomedical research.

Artificial Intelligence (AI)-based approaches for extracting Social Drivers of Health (SDoH) from clinical notes offer healthcare systems an efficient way to identify patients' social needs, yet we know little about the acceptability of this approach to patients and clinicians. We investigated patient and clinician acceptability through interviews.

Many children with cancer are treated as part of interventional clinical trials. Ensuring that the correct chemotherapy treatment plan is used is paramount.The objectives of this report were to: (1) highlight the initial design of a clinical decision support (CDS) tool that was intended to help ensure the correct matching of research studies to research chemotherapy medications, (2) discuss the issues identified with the CDS tool, and (3) review the [...]

The objective of this work is to demonstrate the value of simulation testing for rapidly evaluating artificial intelligence (AI) products.

Electronic health records (EHRs) data are increasingly used for research and analysis, but there is little empirical evidence to inform how automated and manual assessments can be combined to efficiently assess data quality in large EHR repositories.

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.