On improving the implementation of automatic updating of systematic reviews.
Author(s): Koroleva, Anna, Olarte Parra, Camila, Paroubek, Patrick
DOI: 10.1093/jamiaopen/ooz044
Author(s): Koroleva, Anna, Olarte Parra, Camila, Paroubek, Patrick
DOI: 10.1093/jamiaopen/ooz044
Health care systems are increasingly utilizing electronic medical record-associated patient portals to facilitate communication with patients and between providers and their patients. These patient portals are growing in recognition as potentially valuable research tools. While there is much information about the response rates and demographics of internet-based surveys as well as the demographics of patients who are portal members, not much is known about the response rate of internet-based surveys [...]
Author(s): Peltz-Rauchman, Cathryn D, Divine, George, McLaren, Daniel, Rubinfeld, Ilan S, Conway, William A, Allard, David, Johnson, Christine Cole
DOI: 10.1093/jamiaopen/ooz061
Author(s): Sarkar, Indra Neil
DOI: 10.1093/jamiaopen/ooz070
To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns contained within granular data of electronic health records.
Author(s): Fohner, Alison E, Greene, John D, Lawson, Brian L, Chen, Jonathan H, Kipnis, Patricia, Escobar, Gabriel J, Liu, Vincent X
DOI: 10.1093/jamia/ocz106
Predictive analytics in health care has generated increasing enthusiasm recently, as reflected in a rapidly growing body of predictive models reported in literature and in real-time embedded models using electronic health record data. However, estimating the benefit of applying any single model to a specific clinical problem remains challenging today. Developing a shared framework for estimating model value is therefore critical to facilitate the effective, safe, and sustainable use of [...]
Author(s): Liu, Vincent X, Bates, David W, Wiens, Jenna, Shah, Nigam H
DOI: 10.1093/jamia/ocz088
Author(s): Stubbs, Amber, Uzuner, Özlem
DOI: 10.1093/jamia/ocz174
Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP).
Author(s): Liao, Katherine P, Sun, Jiehuan, Cai, Tianrun A, Link, Nicholas, Hong, Chuan, Huang, Jie, Huffman, Jennifer E, Gronsbell, Jessica, Zhang, Yichi, Ho, Yuk-Lam, Castro, Victor, Gainer, Vivian, Murphy, Shawn N, O'Donnell, Christopher J, Gaziano, J Michael, Cho, Kelly, Szolovits, Peter, Kohane, Isaac S, Yu, Sheng, Cai, Tianxi
DOI: 10.1093/jamia/ocz066
Track 1 of the 2018 National NLP Clinical Challenges shared tasks focused on identifying which patients in a corpus of longitudinal medical records meet and do not meet identified selection criteria.
Author(s): Stubbs, Amber, Filannino, Michele, Soysal, Ergin, Henry, Samuel, Uzuner, Özlem
DOI: 10.1093/jamia/ocz163
The study sought to characterize institution-wide participation in secure messaging (SM) at a large academic health network, describe our experience with electronic medical record (EMR)-based cohort selection, and discuss the potential roles of SM for research recruitment.
Author(s): Miller, Hailey N, Gleason, Kelly T, Juraschek, Stephen P, Plante, Timothy B, Lewis-Land, Cassie, Woods, Bonnie, Appel, Lawrence J, Ford, Daniel E, Dennison Himmelfarb, Cheryl R
DOI: 10.1093/jamia/ocz168
Electronic health records are increasingly utilized for observational and clinical research. Identification of cohorts using electronic health records is an important step in this process. Previous studies largely focused on the methods of cohort selection, but there is little evidence on the impact of underlying vocabularies and mappings between vocabularies used for cohort selection. We aim to compare the cohort selection performance using Australian Medicines Terminology to Anatomical Therapeutic Chemical [...]
Author(s): Guo, Guan N, Jonnagaddala, Jitendra, Farshid, Sanjay, Huser, Vojtech, Reich, Christian, Liaw, Siaw-Teng
DOI: 10.1093/jamia/ocz143