Response to Lapkoff and Sittig.
Author(s): Poikonen, John, Fotsch, Edward, Lehmann, Christoph U
DOI: 10.4338/ACI2017050081
Author(s): Poikonen, John, Fotsch, Edward, Lehmann, Christoph U
DOI: 10.4338/ACI2017050081
The International Classification of Functioning, Disability and Health (ICF) is the World Health Organization's standard for describing health and health-related states. Examples of how the ICF has been used in Electronic Health Records (EHRs) have not been systematically summarized and described yet.
Author(s): Maritz, Roxanne, Aronsky, Dominik, Prodinger, Birgit
DOI: 10.4338/ACI2017050078
Increasing use of EHRs has generated interest in the potential of computerized clinical decision support to improve treatment of sepsis. Electronic sepsis alerts have had mixed results due to poor test characteristics, the inability to detect sepsis in a timely fashion and the use of outside software limiting widespread adoption. We describe the development, evaluation and validation of an accurate and timely severe sepsis alert with the potential to impact [...]
Author(s): Rolnick, Joshua, Downing, N Lance, Shepard, John, Chu, Weihan, Tam, Julia, Wessels, Alexander, Li, Ron, Dietrich, Brian, Rudy, Michael, Castaneda, Leon, Shieh, Lisa
DOI: 10.4338/ACI-2015-11-RA-0159
A critical consideration when applying the results of a clinical trial to a particular patient is the degree of similarity of the patient to the trial population. However, similarity assessment rarely is practical in the clinical setting. Here, we explore means to support similarity assessment by clinicians.
Author(s): Cahan, Amos, Cimino, James J
DOI: 10.4338/ACI-2015-12-RA-0178
Big data or population-based information has the potential to reduce uncertainty in medicine by informing clinicians about individual patient care. The objectives of this study were: 1) to explore the feasibility of extracting and displaying population-based information from an actual clinical population's database records, 2) to explore specific design features for improving population display, 3) to explore perceptions of population information displays, and 4) to explore the impact of population [...]
Author(s): Roosan, Don, Del Fiol, Guilherme, Butler, Jorie, Livnat, Yarden, Mayer, Jeanmarie, Samore, Matthew, Jones, Makoto, Weir, Charlene
DOI: 10.4338/ACI-2015-12-RA-0182
For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we [...]
Author(s): Tham, Eric, Swietlik, Marguerite, Deakyne, Sara, Hoffman, Jeffrey M, Grundmeier, Robert W, Paterno, Marilyn D, Rocha, Beatriz H, Schaeffer, Molly H, Pabbathi, Deepika, Alessandrini, Evaline, Ballard, Dustin, Goldberg, Howard S, Kuppermann, Nathan, Dayan, Peter S, ,
DOI: 10.4338/ACI-2015-10-CR-0144
To describe lung transplant recipients (LTRs') acceptance and use of mobile technology for health self-monitoring during the first year post-transplantation, and explore correlates of the use of technology in the 0 to 2, >2 to ≤6, >6 to ≤12, and 0 to 12 months.
Author(s): Jiang, Yun, Sereika, Susan M, Dabbs, Annette DeVito, Handler, Steven M, Schlenk, Elizabeth A
DOI: 10.4338/ACI-2015-12-RA-0170
Physicians caring for children with serious acute neurologic disease must process overwhelming amounts of physiological and medical information. Strategies to optimize real time display of this information are understudied.
Author(s): Grinspan, Zachary M, Eldar, Yonina C, Gopher, Daniel, Gottlieb, Amihai, Lammfromm, Rotem, Mangat, Halinder S, Peleg, Nimrod, Pon, Steven, Rozenberg, Igal, Schiff, Nicholas D, Stark, David E, Yan, Peter, Pratt, Hillel, Kosofsky, Barry E
DOI: 10.4338/ACI-2015-12-RA-0177
Health information exchange (HIE) facilitates the exchange of patient information across different healthcare organizations. To match patient records across sites, HIEs usually rely on a master patient index (MPI), a database responsible for determining which medical records at different healthcare facilities belong to the same patient. A single patient's records may be improperly split across multiple profiles in the MPI.
Author(s): Zech, John, Husk, Gregg, Moore, Thomas, Shapiro, Jason S
DOI: 10.4338/ACI-2015-11-RA-0158
Recently there have been several high-profile ransomware attacks involving hospitals around the world. Ransomware is intended to damage or disable a user's computer unless the user makes a payment. Once the attack has been launched, users have three options: 1) try to restore their data from backup; 2) pay the ransom; or 3) lose their data. In this manuscript, we discuss a socio-technical approach to address ransomware and outline four [...]
Author(s): Sittig, Dean F, Singh, Hardeep
DOI: 10.4338/ACI-2016-04-SOA-0064