Supporting rigor through reproducibility.
Author(s): Sarkar, Indra Neil
DOI: 10.1093/jamiaopen/ooaa050
Author(s): Sarkar, Indra Neil
DOI: 10.1093/jamiaopen/ooaa050
Self-tracking through mobile health technology can augment the electronic health record (EHR) as an additional data source by providing direct patient input. This can be particularly useful in the context of enigmatic diseases and further promote patient engagement.
Author(s): Ensari, Ipek, Pichon, Adrienne, Lipsky-Gorman, Sharon, Bakken, Suzanne, Elhadad, Noémie
DOI: 10.1055/s-0040-1718755
As the coronavirus disease 2019 pandemic exerts unprecedented stress on hospitals, health care systems have quickly deployed innovative technology solutions to decrease personal protective equipment (PPE) use and augment patient care capabilities. Telehealth technology use is established in the ambulatory setting, but not yet widely deployed at scale for inpatient care.
Author(s): Ong, Shawn Y, Stump, Lisa, Zawalich, Matthew, Edwards, Lisa, Stanton, Glynn, Matthews, Michael, Hsiao, Allen L
DOI: 10.1055/s-0040-1719180
Cancer is a leading cause of death, but much of the diagnostic information is stored as unstructured data in pathology reports. We aim to improve uncertainty estimates of machine learning-based pathology parsers and evaluate performance in low data settings.
Author(s): Odisho, Anobel Y, Park, Briton, Altieri, Nicholas, DeNero, John, Cooperberg, Matthew R, Carroll, Peter R, Yu, Bin
DOI: 10.1093/jamiaopen/ooaa029
The electronic health record is a rising resource for quantifying medical practice, discovering the adverse effects of drugs, and studying comparative effectiveness. One of the challenges of applying these methods to health care data is the high dimensionality of the health record. Methods to discover the effects of drugs in health data must account for tens of thousands of potentially relevant confounders. Our goal in this work is to reduce [...]
Author(s): Melamed, Rachel D
DOI: 10.1093/jamiaopen/ooaa040
Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients' (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine [...]
Author(s): Choudhury, Avishek, Renjilian, Emily, Asan, Onur
DOI: 10.1093/jamiaopen/ooaa034
Managing participants and their data are fundamental for the success of a clinical trial. Our review identifies and describes processes that deal with management of trial participants and highlights information technology (IT) assistance for clinical research in the context of participant management.
Author(s): Pung, Johannes, Rienhoff, Otto
DOI: 10.1093/jamiaopen/ooaa041
Referring patients to specialty care is an inefficient and error-prone process. Gaps in the referral process lead to delays in patients' access to care, negative patient experience, worse health outcomes, and increased operational costs. While implementation of standards-based electronic referral options can alleviate some of these inefficiencies, many referrals to tertiary and quaternary care centers continue to be sent via fax.
Author(s): Odisho, Anobel Y, Lui, Hansen, Yerramsetty, Ramakrishna, Bautista, Felicisimo, Gleason, Nathaniel, Martin, Edwin, Young, Jerry J, Blum, Michael, Neinstein, Aaron B
DOI: 10.1093/jamiaopen/ooaa036
To identify recurrent themes, insights, and process recommendations from stakeholders in US organizations during the health information technology (HIT) modernization of an existing electronic health record (EHR) to a commercial-off-the-shelf product in both resource-plentiful settings and in a resource-constrained environment, the US Indian Health Service.
Author(s): Amlung, Joseph, Huth, Hannah, Cullen, Theresa, Sequist, Thomas
DOI: 10.1093/jamiaopen/ooaa027
To enhance reproducible research by creating a broadly accessible, free, open-source software tool for connecting Microsoft Word to statistical programs (R/R Markdown, Python, SAS, Stata) so that results may be automatically updated in a manuscript.
Author(s): Welty, Leah J, Rasmussen, Luke V, Baldridge, Abigail S, Whitley, Eric W
DOI: 10.1093/jamiaopen/ooaa043