From MedWreck to MedRec: A Call to Action to Improve Medication Reconciliation.
Author(s): Kashyap, Nitu, Jeffery, Sean, Agresta, Thomas
DOI: 10.1055/a-2181-1847
Author(s): Kashyap, Nitu, Jeffery, Sean, Agresta, Thomas
DOI: 10.1055/a-2181-1847
Manual data entry is time-consuming, inefficient, and error prone. In contrast, leveraging two-dimensional (2D) barcodes and barcode scanning tools is a rapid and effective practice for automatically entering vaccine data accurately and completely. CDC pilots documented clinical and public health impacts of 2D barcode scanning practices on data quality and completeness, time savings, workflow efficiencies, and staff experience.
Author(s): Reza, Faisal, Jones, Caroline, Reed, Jenica H
DOI: 10.1055/a-2255-9749
Electronic health records (EHRs) present navigation challenges due to time-consuming searches across segmented data. Voice assistants can improve clinical workflows by allowing natural language queries and contextually aware navigation of the EHR.
Author(s): Kumah-Crystal, Yaa A, Lehmann, Christoph U, Albert, Dan, Coffman, Tim, Alaw, Hala, Roth, Sydney, Manoni, Alexandra, Shave, Peter, Johnson, Kevin B
DOI: 10.1055/a-2177-4420
Clinicians play an important role in addressing pediatric and adolescent obesity, but their effectiveness is restricted by time constraints, competing clinical demands, and the lack of effective electronic health record (EHR) tools. EHR tools are rarely developed with provider input.
Author(s): Braddock, Amy S, Bosworth, K Taylor, Ghosh, Parijat, Proffitt, Rachel, Flowers, Lauren, Montgomery, Emma, Wilson, Gwendolyn, Tosh, Aneesh K, Koopman, Richelle J
DOI: 10.1055/a-2283-9036
Narrative nursing notes are a valuable resource in informatics research with unique predictive signals about patient care. The open sharing of these data, however, is appropriately constrained by rigorous regulations set by the Health Insurance Portability and Accountability Act (HIPAA) for the protection of privacy. Several models have been developed and evaluated on the open-source i2b2 dataset. A focus on the generalizability of these models with respect to nursing notes [...]
Author(s): Chen, Fangyi, Bokhari, Syed Mohtashim Abbas, Cato, Kenrick, Gürsoy, Gamze, Rossetti, Sarah
DOI: 10.1055/a-2282-4340
National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard [...]
Author(s): Iott, Bradley E, Rivas, Samantha, Gottlieb, Laura M, Adler-Milstein, Julia, Pantell, Matthew S
DOI: 10.1093/jamia/ocad261
This study aimed to identify barriers and facilitators to the implementation of family cancer history (FCH) collection tools in clinical practices and community settings by assessing clinicians' perceptions of implementing a chatbot interface to collect FCH information and provide personalized results to patients and providers.
Author(s): Allen, Caitlin G, Neil, Grace, Halbert, Chanita Hughes, Sterba, Katherine R, Nietert, Paul J, Welch, Brandon, Lenert, Leslie
DOI: 10.1093/jamia/ocad243
Clinical text processing offers a promising avenue for improving multiple aspects of healthcare, though operational deployment remains a substantial challenge. This case report details the implementation of a national clinical text processing infrastructure within the Department of Veterans Affairs (VA).
Author(s): McManus, Kimberly F, Stringer, Johnathon Michael, Corson, Neal, Fodeh, Samah, Steinhardt, Steven, Levin, Forrest L, Shotqara, Asqar S, D'Auria, Joseph, Fielstein, Elliot M, Gobbel, Glenn T, Scott, John, Trafton, Jodie A, Taddei, Tamar H, Erdos, Joseph, Tamang, Suzanne R
DOI: 10.1093/jamia/ocad249
Author(s): Tugaoen, Julian, Becker, Alana, Guo, Chenmeinian, Parasidis, Efthimios, Venkatakrishnan, Shaileshh Bojja, Otero, José Javier
DOI: 10.1093/jamia/ocad227
Research on how people interact with electronic health records (EHRs) increasingly involves the analysis of metadata on EHR use. These metadata can be recorded unobtrusively and capture EHR use at a scale unattainable through direct observation or self-reports. However, there is substantial variation in how metadata on EHR use are recorded, analyzed and described, limiting understanding, replication, and synthesis across studies.
Author(s): Rule, Adam, Kannampallil, Thomas, Hribar, Michelle R, Dziorny, Adam C, Thombley, Robert, Apathy, Nate C, Adler-Milstein, Julia
DOI: 10.1093/jamia/ocad254