Correction: A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models.
Author(s):
DOI: 10.1093/jamia/ocac102
Author(s):
DOI: 10.1093/jamia/ocac102
This case study assesses the uptake, user characteristics, and outcomes of automated self-scheduling in a community-based physician group affiliated with an academic health system. We analyzed 1 995 909 appointments booked between January 1, 2019, and June 30, 2021 at more than 30 practice sites. Over the study period, uptake of self-scheduling increased from 4% to 15% of kept appointments. Younger, commercially insured patients were more likely to be users. Missed appointments [...]
Author(s): Woodcock, Elizabeth, Sen, Aditi, Weiner, Jonathan
DOI: 10.1093/jamia/ocac087
Deep learning models for clinical event forecasting (CEF) based on a patient's medical history have improved significantly over the past decade. However, their transition into practice has been limited, particularly for diseases with very low prevalence. In this paper, we introduce CEF-CL, a novel method based on contrastive learning to forecast in the face of a limited number of positive training instances.
Author(s): Zhang, Ziqi, Yan, Chao, Zhang, Xinmeng, Nyemba, Steve L, Malin, Bradley A
DOI: 10.1093/jamia/ocac086
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocac128
HL7 SMART on FHIR apps have the potential to improve healthcare delivery and EHR usability, but providers must be aware of the apps and use them for these potential benefits to be realized. The HL7 CDS Hooks standard was developed in part for this purpose. The objective of this study was to determine if contextually relevant CDS Hooks prompts can increase utilization of a SMART on FHIR medical reference app [...]
Author(s): Morgan, Keaton L, Kukhareva, Polina V, Warner, Phillip B, Wilkof, Jonah, Snyder, Meir, Horton, Devin, Madsen, Troy, Habboushe, Joseph, Kawamoto, Kensaku
DOI: 10.1093/jamia/ocac085
Hospitals have multiple methods available to engage in health information exchange (HIE); however, it is not well understood whether these methods are complements or substitutes. We sought to characterize patterns of adoption of HIE methods and examine the association between these methods and increased availability and use of patient information.
Author(s): Everson, Jordan, Patel, Vaishali
DOI: 10.1093/jamia/ocac079
Our objective was to evaluate tokens commonly used by clinical research consortia to aggregate clinical data across institutions.
Author(s): Bernstam, Elmer V, Applegate, Reuben Joseph, Yu, Alvin, Chaudhari, Deepa, Liu, Tian, Coda, Alex, Leshin, Jonah
DOI: 10.1055/a-1910-4154
School-aged children with chronic conditions require care coordination for health needs at school. Access to the student's accurate, real-time medical information is essential for school nurses to maximize their care of students. We aim to analyze school nurse access to medical records in a hospital-based electronic health record (EHR) and the effect on patient outcomes. We hypothesized that EHR access would decrease emergency department (ED) visits and inpatient hospitalizations.
Author(s): Baker, Christina, Loresto, Figaro, Pickett, Kaci, Samay, Sadaf Sara, Gance-Cleveland, Bonnie
DOI: 10.1055/a-1905-3729
Author(s): Chen, You, Adler-Milstein, Julia, Sinsky, Christine A
DOI: 10.1055/a-1892-1437
Venipunctures and the testing they facilitate are clinically necessary, particularly for hospitalized patients. However, excess venipunctures lead to patient harm, decreased patient satisfaction, and waste.
Author(s): Anstett, Tyler, Smith, Chris, Hess, Kaitlyn, Patten, Luke, Pincus, Sharon, Lin, Chen-Tan, Ho, P Michael
DOI: 10.1055/a-1913-4158