European journal of clinical investigation
33043432
BACKGROUND: Prolonged length of stay (LOS) and post-acute care after percutaneous coronary intervention (PCI) is common and costly. Risk models for predicting prolonged LOS and post-acute care have limited accuracy. Our goal was to develop and valida...
Our objective was to detect common barriers to post-acute care (B2PAC) among hospitalized older adults using natural language processing (NLP) of clinical notes from patients discharged home when a clinical decision support system recommended post-ac...
Journal of the American Medical Directors Association
37838000
OBJECTIVES: To determine the scope of the application of natural language processing to free-text clinical notes in post-acute care and provide a foundation for future natural language processing-based research in these settings.
Journal of the American Medical Directors Association
38909630
This article proposes a framework for examining the ethical and legal concerns for using artificial intelligence (AI) in post-acute and long-term care (PA-LTC). It argues that established frameworks on health, AI, and the law should be adapted to spe...
Journal of the American Medical Informatics Association : JAMIA
39530740
OBJECTIVES: This study aims to (1) review machine learning (ML)-based models for early infection diagnostic and prognosis prediction in post-acute care (PAC) settings, (2) identify key risk predictors influencing infection-related outcomes, and (3) e...
PURPOSE: As the global population ages, long-term/post-acute care (LTPAC) systems face challenges in ensuring quality care for older adults with complex medical needs. Using health information technology (IT) is a promising strategy to address these ...