Response to Randell et al. "Using realist reviews to understand how health IT works, for whom, and in what circumstances".
Author(s): Otte-Trojel, Terese, de Bont, Antoinette, Rundall, Thomas G, van de Klundert, Joris
DOI: 10.1093/jamia/ocu008
Author(s): Otte-Trojel, Terese, de Bont, Antoinette, Rundall, Thomas G, van de Klundert, Joris
DOI: 10.1093/jamia/ocu008
We aimed to investigate medical students' attitudes about Clinical Informatics (CI) training and careers.
Author(s): Banerjee, Rahul, George, Paul, Priebe, Cedric, Alper, Eric
DOI: 10.1093/jamia/ocu046
Author(s): Valdez, Rupa S, Holden, Richard J, Novak, Laurie L, Veinot, Tiffany C
DOI: 10.1093/jamia/ocu031
Author(s): Marceglia, Sara, Fontelo, Paul, Ackerman, Michael J
DOI: 10.1093/jamia/ocu030
In alignment with a major shift toward patient-centered care as the model for improving care in our health system, informatics is transforming patient-provider relationships and overall care delivery. AMIA's 2013 Health Policy Invitational was focused on examining existing challenges surrounding full engagement of the patient and crafting a research agenda and policy framework encouraging the use of informatics solutions to achieve this goal. The group tackled this challenge from educational [...]
Author(s): Brennan, Patti Flatley, Valdez, Rupa, Alexander, Greg, Arora, Shifali, Bernstam, Elmer V, Edmunds, Margo, Kirienko, Nikolai, Martin, Ross D, Sim, Ida, Skiba, Diane, Rosenbloom, Trent
DOI: 10.1136/amiajnl-2014-003176
To integrate data elements from multiple sources for informing comprehensive and standardized collection of family health history (FHH).
Author(s): Chen, Elizabeth S, Carter, Elizabeth W, Winden, Tamara J, Sarkar, Indra Neil, Wang, Yan, Melton, Genevieve B
DOI: 10.1136/amiajnl-2014-003092
We study the use of speech recognition and information extraction to generate drafts of Australian nursing-handover documents.
Author(s): Suominen, Hanna, Johnson, Maree, Zhou, Liyuan, Sanchez, Paula, Sirel, Raul, Basilakis, Jim, Hanlen, Leif, Estival, Dominique, Dawson, Linda, Kelly, Barbara
DOI: 10.1136/amiajnl-2014-002868
Despite effective therapies for many conditions, patients find it difficult to adhere to prescribed treatments. Technology-mediated interventions (TMIs) are increasingly being used with the hope of improving adherence.
Author(s): Mistry, Niraj, Keepanasseril, Arun, Wilczynski, Nancy L, Nieuwlaat, Robby, Ravall, Manthan, Haynes, R Brian, ,
DOI: 10.1093/jamia/ocu047
Clinical decision support systems (CDSSs) assist clinicians with patient diagnosis and treatment. However, inadequate attention has been paid to the process of selecting and buying systems. The diversity of CDSSs, coupled with research obstacles, marketplace limitations, and legal impediments, has thwarted comparative outcome studies and reduced the availability of reliable information and advice for purchasers. We review these limitations and recommend several comparative studies, which were conducted in phases; studies [...]
Author(s): Dhiman, Gaurav Jay, Amber, Kyle T, Goodman, Kenneth W
DOI: 10.1093/jamia/ocu033
Radiology reports are usually narrative, unstructured text, a format which hinders the ability to input report contents into decision support systems. In addition, reports often describe multiple lesions, and it is challenging to automatically extract information on each lesion and its relationships to characteristics, anatomic locations, and other information that describes it. The goal of our work is to develop natural language processing (NLP) methods to recognize each lesion in [...]
Author(s): Bozkurt, Selen, Lipson, Jafi A, Senol, Utku, Rubin, Daniel L
DOI: 10.1136/amiajnl-2014-003009