Large language models for identifying depression concerns in cancer patients.
Author(s): Wang, Yu, Ye, Xin, Luo, Huiping, Feng, Wei
DOI: 10.1093/jamia/ocaf072
Author(s): Wang, Yu, Ye, Xin, Luo, Huiping, Feng, Wei
DOI: 10.1093/jamia/ocaf072
Intrahospital patient transport is pivotal in enabling hospital operations and facilitating safe and efficient patient movement. However, transport delays are common in hospitals, signaling a need for improvement. This study develops, implements, and evaluates a proximity-based transporter-to-request assignment system aimed at improving transport service system efficiency.
Author(s): Sun, Christopher L F, Copenhaver, Martin S, Zenteno Langle, Ana Cecilia, Viscomi, Bruno, Raeke, Ed, Daily, Bethany J, Dunn, Peter F, Levi, Retsef
DOI: 10.1093/jamia/ocaf081
Electronic health records (EHRs) contain valuable patient information, yet certain aspects of care remain infrequently documented and difficult to extract. Identifying these rarely documented elements requires advanced informatics approaches to uncover clinical documentation patterns that would otherwise remain inaccessible for research and quality improvement.This study developed and validated an informatics approach using natural language processing (NLP) to detect and characterize rarely documented elements in EHRs, using spiritual care documentation as [...]
Author(s): Albashayreh, Alaa, Zeinali, Nahid, Gusen, Nanle Joseph, Ji, Yuwen, Gilbertson-White, Stephanie
DOI: 10.1055/a-2599-6300
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 effect of AI scribes on clinicians, patients, and organizations.This study aimed to (1) propose an evaluation framework to guide future AI scribe implementations, (2) describe the effect of AI scribes along the domains proposed in the developed evaluation framework, and (3) identify gaps in [...]
Author(s): Hassan, Hadeel, Zipursky, Amy R, Rabbani, Naveed, You, Jacqueline G, Tse, Gabriel, Orenstein, Evan, Ray, Mondira, Parsons, Chase, Shin, Stella, Lawton, Gregory, Jessa, Karim, Sung, Lillian, Yan, Adam P
DOI: 10.1055/a-2597-2017
Electronic health record (EHR) usage measures may quantify physician activity at scale and predict practice settings with a high risk for physician burnout, but their relation to experiences is poorly understood.This study aimed to explore the EHR-related experiences and well-being of primary care physicians in comparison to EHR usage measures identified as important for predicting burnout from a machine learning model.Exploratory qualitative study with semi-structured interviews of primary care physicians [...]
Author(s): Tawfik, Daniel, Sebok-Syer, Stefanie S, Bragdon, Cassandra, Brown-Johnson, Cati, Winget, Marcy, Bayati, Mohsen, Shanafelt, Tait, Profit, Jochen
DOI: 10.1055/a-2595-0415
The patient-facing ASTHMAXcel mobile platform has been linked to improved asthma knowledge decreased asthma-related health care utilization (emergency department [ED] visits, hospitalizations), and reduced prednisone use among adult and pediatric patient populations.Given the upfront costs associated with developing mobile health platforms, this paper seeks to estimate the savings attributable to pediatric and adult users of the ASTHMAXcel platform through decreased hospitalizations, ED visits, and prednisone use.Forty adult patients and 39 [...]
Author(s): Nadelmann, Julia, Patel, Milin, Lane, Sarah, Hammock, James, Stark, Allison, Jariwala, Sunit P
DOI: 10.1055/a-2595-3329
While electronic health record (EHR)-based tools for refugee health screening exist, support for other immigrant children has lagged. Reasons include lack of time, difficulty determining screening eligibility, and lack of awareness of screening recommendations. EHR-based tools to promote immigrant child health screening (ICHS) can address these challenges, but guidance is needed for tools that are usable by clinicians and acceptable to immigrant families.Develop useful EHR-based tools to support ICHS while [...]
Author(s): Michel, Jeremy J, Karavite, Dean, White, Daniel, Mudenge, Nadège, Dawson-Hahn, Elizabeth, Yun, Katherine
DOI: 10.1055/a-2594-3633
Approximately 10% of patients have a documented penicillin "allergy"; however, up to 95% have subsequent negative testing. These patients may receive suboptimal antibiotics, leading to longer hospitalizations and higher costs, rates of resistant and nosocomial infections, and all-cause mortality. To mitigate these risks in children, we implemented an inpatient penicillin allergy delabeling protocol and integrated it into the electronic health record (EHR) through a mixed methods approach of clinical decision [...]
Author(s): Plattner, Alexander S, Lockowitz, Christine R, Same, Rebecca G, Abdelnour, Monica, Chin, Samuel, Cormier, Matthew J, Daugherty, Megan S, Grier, Alexandra E, Hampton, Nicholas B, Hofford, Mackenzie R, Mehta, Sarah S, Newland, Jason G, O'Bryan, Kevin S, Sattler, Matthew M, Shah, Mehr Z, Starnes, G Lucas, Yuenger, Valerie, Ellis, Alysa G, Facer, Evan E
DOI: 10.1055/a-2595-4849
Cancer staging is integral to ensuring cancer patients receive appropriate risk-adapted therapy. Discrete cancer staging using a structured staging form helps ensure accurate staging, provides a single source of truth for staging information, and allows for reporting to regulatory authorities. Our institution created pediatric oncology specific discrete staging forms that have been shared with the broader Epic community. By November 2023, baseline utilization of the staging form for patients with [...]
Author(s): Potashner, Renee, Yan, Adam P
DOI: 10.1055/a-2594-3722
Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness. Guidelines recommend screening for infants with gestational age at birth <31 weeks or birth weight ≤1,500 g. However, ensuring timely screening during readmissions after birth is challenging.To analyze the performance of an interruptive alert at a large academic pediatric hospital for identifying premature infants needing ROP screening upon hospital readmission and to describe how data informed the transition to a non-interruptive dashboard.The alert appeared for patients 1 to 365 days of age hospitalized in acute care or pediatric intensive care and instructed providers to order an ophthalmology consult from within the alert and to call ophthalmology for at-risk patients. For quality improvement, the clinical decision support (CDS) advisory group evaluated the effectiveness and efficiency of the alert. We extracted alert metrics from the hospital's enterprise data warehouse, including the user response and feedback, patient characteristics (age, birth gestational age, and birth weight), and any ophthalmology consultations. We analyzed the percentage of encounters seen by ophthalmology using a statistical process control chart during alert implementation and 6 months before and after.The alert appeared 3,309 times during 2,194 patient encounters usually. Users chose "Accept and place order" for 43% (943/2,194) of encounters, but only 11% (102/943) had an ophthalmology consult; 34% (53/155) of ophthalmology consultations occurred in encounters with a final response other than "Accept and place order." The intervention was redesigned using a non-interruptive surveillance dashboard with greater specificity, and the alert was de-implemented.Analysis of a failed interruptive alert for identifying patients at risk for ROP led to a transition to targeted surveillance using a dashboard. This case emphasizes the importance of aligning the CDS modality to the clinical workflow, information availability, and user decision-making needs and should be supported by governance.
Author(s): Guzman-Karlsson, Mikael C, Hess, Lauren M, Jeppesen, Amy L, Fortunov, Regine M
DOI: 10.1055/a-2594-3571