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Pediatric cancer patients with fever and neutropenia are at risk for bacterial sepsis, traditionally requiring extended hospital stays on antibiotics until neutrophil counts recover. According to a newly validated scoring system, a subset of these patients is at lower risk and eligible for early discharge and reduced intravenous (IV) antibiotic exposure.Reduce length-of-stay (LOS) for febrile neutropenic patients using clinical decision support (CDS) to identify low-risk patients.A CDS system was developed [...]

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.

screening is a labor-intensive component of systematic review involving repetitive application of inclusion and exclusion criteria on a large volume of studies. We aimed to validate large language models (LLMs) used to automate abstract screening.

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

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