Correction to: Measuring interpersonal firearm violence: natural language processing methods to address limitations in criminal charge data.
Author(s):
DOI: 10.1093/jamia/ocae268
Author(s):
DOI: 10.1093/jamia/ocae268
The Vanderbilt Clinical Informatics Center (VCLIC) is based in the Department of Biomedical Informatics (DBMI) and operates across Vanderbilt University Medical Center (VUMC) and Vanderbilt University (VU) with a goal of enabling and supporting clinical informatics research and practice. VCLIC supports several types of applied clinical informatics teaching, including teaching of students in courses, professional education for staff and faculty throughout VUMC, and workshops and conferences that are open to [...]
Author(s): Russo, Elise, McCoy, Allison, Mize, Dara, Osterman, Travis, Nelson, Scott, Wanderer, Jonathan P, Wright, Adam
DOI: 10.1055/a-2443-8318
Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to coprescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low.
Author(s): Wu, Richard, Foster, Emily, Zhang, Qiyao, Eynatian, Tim, Mishuris, Rebecca, Cordella, Nicholas
DOI: 10.1055/a-2447-8463
To understand how health-related social needs (HRSN) data are collected at US hospitals and implications for use.
Author(s): Richwine, Chelsea, Patel, Vaishali, Everson, Jordan, Iott, Bradley
DOI: 10.1093/jamia/ocae279
This study aims to improve the ethical use of machine learning (ML)-based clinical prediction models (CPMs) in shared decision-making for patients with kidney failure on dialysis. We explore factors that inform acceptability, interpretability, and implementation of ML-based CPMs among multiple constituent groups.
Author(s): Sperling, Jessica, Welsh, Whitney, Haseley, Erin, Quenstedt, Stella, Muhigaba, Perusi B, Brown, Adrian, Ephraim, Patti, Shafi, Tariq, Waitzkin, Michael, Casarett, David, Goldstein, Benjamin A
DOI: 10.1093/jamia/ocae255
Primary care pediatricians play an important role in genetic testing, including referrals, test ordering, responding to results, assessing risk, treatment, and managing care. As genetic testing rapidly evolves to include new tests identifying patients at risk for certain conditions, alert-based clinical decision support is insufficient in assisting pediatric primary care providers in working with patients, parents, genetics, and other specialties. Supporting pediatricians in the return of these results requires addressing [...]
Author(s): Karavite, Dean, Terek, Shannon, Connolly, John J, Harr, Margaret, Muthu, Naveen, Hakonarson, Hakon, Grundmeier, Robert W
DOI: 10.1055/a-2445-9185
To examine changes in technology-related errors (TREs), their manifestations and underlying mechanisms at 3 time points after the implementation of computerized provider order entry (CPOE) in an electronic health record; and evaluate the clinical decision support (CDS) available to mitigate the TREs at 5-years post-CPOE.
Author(s): Raban, Magdalena Z, Fitzpatrick, Erin, Merchant, Alison, Rahman, Bayzidur, Badgery-Parker, Tim, Li, Ling, Baysari, Melissa T, Barclay, Peter, Dickinson, Michael, Mumford, Virginia, Westbrook, Johanna I
DOI: 10.1093/jamia/ocae218
The Supplemental Nutrition Assistance Program (SNAP) is one of the most successful national programs to reduce poverty and improve health outcomes, but millions of Americans who qualify still do not have access to SNAP, and limited data are available to determine how referrals to the program can be completed successfully.
Author(s): Oliveira, Eliel, Hautala, Matti, Henry, JaWanna, Lakshminarayanan, Vidya, Abrol, Vishal, Granado, Linda, Shah, Shashank, Khurshid, Anjum
DOI: 10.1055/a-2441-5941
To understand barriers to obtaining and using interoperable information at US hospitals.
Author(s): Everson, Jordan, Richwine, Chelsea
DOI: 10.1093/jamia/ocae263
We aim to use large language models (LLMs) to detect mentions of nuanced psychotherapeutic outcomes and impacts than previously considered in transcripts of interviews with adolescent depression. Our clinical authors previously created a novel coding framework containing fine-grained therapy outcomes beyond the binary classification (eg, depression vs control) based on qualitative analysis embedded within a clinical study of depression. Moreover, we seek to demonstrate that embeddings from LLMs are informative [...]
Author(s): Xin, Alison W, Nielson, Dylan M, Krause, Karolin Rose, Fiorini, Guilherme, Midgley, Nick, Pereira, Francisco, Lossio-Ventura, Juan Antonio
DOI: 10.1093/jamia/ocae298