Correction to: Managing re-identification risks while providing access to the All of Us research program.
Author(s):
DOI: 10.1093/jamia/ocad044
Author(s):
DOI: 10.1093/jamia/ocad044
The COVID-19 pandemic exposed multiple weaknesses in the nation's public health system. Therefore, the American College of Medical Informatics selected "Rebuilding the Nation's Public Health Informatics Infrastructure" as the theme for its annual symposium. Experts in biomedical informatics and public health discussed strategies to strengthen the US public health information infrastructure through policy, education, research, and development. This article summarizes policy recommendations for the biomedical informatics community postpandemic. First, the [...]
Author(s): Dixon, Brian E, Staes, Catherine, Acharya, Jessica, Allen, Katie S, Hartsell, Joel, Cullen, Theresa, Lenert, Leslie, Rucker, Donald W, Lehmann, Harold
DOI: 10.1093/jamia/ocad033
Nonexercise algorithms are cost-effective methods to estimate cardiorespiratory fitness (CRF), but the existing models have limitations in generalizability and predictive power. This study aims to improve the nonexercise algorithms using machine learning (ML) methods and data from US national population surveys.
Author(s): Liu, Yuntian, Herrin, Jeph, Huang, Chenxi, Khera, Rohan, Dhingra, Lovedeep Singh, Dong, Weilai, Mortazavi, Bobak J, Krumholz, Harlan M, Lu, Yuan
DOI: 10.1093/jamia/ocad035
Understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED).
Author(s): Moy, Amanda J, Hobensack, Mollie, Marshall, Kyle, Vawdrey, David K, Kim, Eugene Y, Cato, Kenrick D, Rossetti, Sarah C
DOI: 10.1093/jamia/ocad038
This study aimed to assess Uganda's readiness for implementing a national Point-of-Care (PoC) electronic clinical data capture platform that can function in near real-time.
Author(s): Nabukenya, Josephine, Egwar, Andrew Alunyu, Drumright, Lydia, Semwanga, Agnes Rwashana, Kasasa, Simon
DOI: 10.1093/jamia/ocad034
(1) Characterize persistent hazards and inefficiencies in inpatient medication administration; (2) Explore cognitive attributes of medication administration tasks; and (3) Discuss strategies to reduce medication administration technology-related hazards.
Author(s): Taft, Teresa, Rudd, Elizabeth Anne, Thraen, Iona, Kazi, Sadaf, Pruitt, Zoe M, Bonk, Christopher W, Busog, Deanna-Nicole, Franklin, Ella, Hettinger, Aaron Z, Ratwani, Raj M, Weir, Charlene R
DOI: 10.1093/jamia/ocad031
Enabling discovery across the spectrum of rare and common diseases requires the integration of biological knowledge with clinical data; however, differences in terminologies present a major barrier. For example, the Human Phenotype Ontology (HPO) is the primary vocabulary for describing features of rare diseases, while most clinical encounters use International Classification of Diseases (ICD) billing codes. ICD codes are further organized into clinically meaningful phenotypes via phecodes. Despite their prevalence [...]
Author(s): McArthur, Evonne, Bastarache, Lisa, Capra, John A
DOI: 10.1093/jamiaopen/ooad007
This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab.
Author(s): Zhu, Siyi, Vennemeyer, Scott, Xu, Catherine, Wu, Danny T Y
DOI: 10.1093/jamiaopen/ooad010
There is much interest in utilizing clinical data for developing prediction models for Alzheimer's disease (AD) risk, progression, and outcomes. Existing studies have mostly utilized curated research registries, image analysis, and structured electronic health record (EHR) data. However, much critical information resides in relatively inaccessible unstructured clinical notes within the EHR.
Author(s): Oh, Inez Y, Schindler, Suzanne E, Ghoshal, Nupur, Lai, Albert M, Payne, Philip R O, Gupta, Aditi
DOI: 10.1093/jamiaopen/ooad014
Coronavirus disease (COVID)-related misinformation is prevalent online, including on social media. The purpose of this study was to explore factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok. A sample of TikTok videos associated with the hashtag #coronavirus was downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, and high) using a codebook developed by experts in infectious diseases. Multivariable modeling [...]
Author(s): Baghdadi, Jonathan D, Coffey, K C, Belcher, Rachael, Frisbie, James, Hassan, Naeemul, Sim, Danielle, Malik, Rena D
DOI: 10.1093/jamiaopen/ooad013