JAMIA Article
Climate change, security, privacy, and data sharing: Important areas for advocacy and informatics solutions.
September 18, 2021
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocab188
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocab188
Author(s): Atwoli, Lukoye, Baqui, Abdullah H, Benfield, Thomas, Bosurgi, Raffaella, Godlee, Fiona, Hancocks, Stephen, Horton, Richard, Laybourn-Langton, Laurie, Monteiro, Carlos Augusto, Norman, Ian, Patrick, Kirsten, Praities, Nigel, Olde Rikkert, Marcel G M, Rubin, Eric J, Sahni, Peush, Smith, Richard, Talley, Nick, Turale, Sue, Vázquez, Damián
DOI: 10.1093/jamia/ocab178
Author(s): Hensher, Martin, Cooper, Paul, Dona, Sithara Wanni Arachchige, Angeles, Mary Rose, Nguyen, Dieu, Heynsbergh, Natalie, Chatterton, Mary Lou, Peeters, Anna
DOI: 10.1093/jamia/ocab106
Author(s): Torous, John, Lagan, Sarah
DOI: 10.1093/jamia/ocab107
De-identification is a fundamental task in electronic health records to remove protected health information entities. Deep learning models have proven to be promising tools to automate de-identification processes. However, when the target domain (where the model is applied) is different from the source domain (where the model is trained), the model often suffers a significant performance drop, commonly referred to as domain adaptation issue. In de-identification, domain adaptation issues can [...]
Author(s): Liao, Shun, Kiros, Jamie, Chen, Jiyang, Zhang, Zhaolei, Chen, Ting
DOI: 10.1093/jamia/ocab128
Using a risk stratification model to guide clinical practice often requires the choice of a cutoff-called the decision threshold-on the model's output to trigger a subsequent action such as an electronic alert. Choosing this cutoff is not always straightforward. We propose a flexible approach that leverages the collective information in treatment decisions made in real life to learn reference decision thresholds from physician practice. Using the example of prescribing a [...]
Author(s): Patel, Birju S, Steinberg, Ethan, Pfohl, Stephen R, Shah, Nigam H
DOI: 10.1093/jamia/ocab159
The study sought to investigate whether consistent use of the Veterans Health Administration's My HealtheVet (MHV) online patient portal is associated with improvement in diabetes-related physiological measures among new portal users.
Author(s): Zocchi, Mark S, Robinson, Stephanie A, Ash, Arlene S, Vimalananda, Varsha G, Wolfe, Hill L, Hogan, Timothy P, Connolly, Samantha L, Stewart, Maureen T, Am, Linda, Netherton, Dane, Shimada, Stephanie L
DOI: 10.1093/jamia/ocab115
Biomedical text summarization helps biomedical information seekers avoid information overload by reducing the length of a document while preserving the contents' essence. Our systematic review investigates the most recent biomedical text summarization researches on biomedical literature and electronic health records by analyzing their techniques, areas of application, and evaluation methods. We identify gaps and propose potential directions for future research.
Author(s): Wang, Mengqian, Wang, Manhua, Yu, Fei, Yang, Yue, Walker, Jennifer, Mostafa, Javed
DOI: 10.1093/jamia/ocab143
To explore Veterans Health Administration clinicians' perspectives on the idea of redesigning electronic consultation (e-consult) delivery in line with a hub-and-spoke (centralized) model.
Author(s): Anderson, Ekaterina, Rinne, Seppo T, Orlander, Jay D, Cutrona, Sarah L, Strymish, Judith L, Vimalananda, Varsha G
DOI: 10.1093/jamia/ocab139
We investigated the progression of healthcare cybersecurity over 2014-2019 as measured by external risk ratings. We further examined the relationship between hospital data breaches and cybersecurity ratings.
Author(s): Choi, Sung J, Johnson, M Eric
DOI: 10.1093/jamia/ocab142