Electronic health records: usability and utilization by health care providers and patients.
Author(s): Ohno-Machado, Lucila
DOI: 10.1093/jamia/ocx013
Author(s): Ohno-Machado, Lucila
DOI: 10.1093/jamia/ocx013
Follow-up with a primary care provider after hospital discharge has been associated with a reduced likelihood of readmission. However, primary care providers are frequently unaware of their patients' hospitalizations. Event notification may be an effective tool for reducing readmissions by notifying primary care providers when their patients have been admitted to and discharged from a hospital.
Author(s): Unruh, Mark Aaron, Jung, Hye-Young, Kaushal, Rainu, Vest, Joshua R
DOI: 10.1093/jamia/ocw139
Clinical guidelines recommending the use of myeloid growth factors are largely based on the prescribed chemotherapy regimen. The guidelines suggest that oncologists consider patient-specific characteristics when prescribing granulocyte-colony stimulating factor (G-CSF) prophylaxis; however, a mechanism to quantify individual patient risk is lacking. Readily available electronic health record (EHR) data can provide patient-specific information needed for individualized neutropenia risk estimation. An evidence-based, individualized neutropenia risk estimation algorithm has been developed. This [...]
Author(s): Pawloski, Pamala A, Thomas, Avis J, Kane, Sheryl, Vazquez-Benitez, Gabriela, Shapiro, Gary R, Lyman, Gary H
DOI: 10.1093/jamia/ocw131
Phenotyping algorithms are capable of accurately identifying patients with specific phenotypes from within electronic medical records systems. However, developing phenotyping algorithms in a scalable way remains a challenge due to the extensive human resources required. This paper introduces a high-throughput unsupervised feature selection method, which improves the robustness and scalability of electronic medical record phenotyping without compromising its accuracy.
Author(s): Yu, Sheng, Chakrabortty, Abhishek, Liao, Katherine P, Cai, Tianrun, Ananthakrishnan, Ashwin N, Gainer, Vivian S, Churchill, Susanne E, Szolovits, Peter, Murphy, Shawn N, Kohane, Isaac S, Cai, Tianxi
DOI: 10.1093/jamia/ocw135
We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts.
Author(s): Spratt, Susan E, Pereira, Katherine, Granger, Bradi B, Batch, Bryan C, Phelan, Matthew, Pencina, Michael, Miranda, Marie Lynn, Boulware, Ebony, Lucas, Joseph E, Nelson, Charlotte L, Neely, Benjamin, Goldstein, Benjamin A, Barth, Pamela, Richesson, Rachel L, Riley, Isaretta L, Corsino, Leonor, McPeek Hinz, Eugenia R, Rusincovitch, Shelley, Green, Jennifer, Barton, Anna Beth, , , Kelley, Carly, Hyland, Kristen, Tang, Monica, Elliott, Amanda, Ruel, Ewa, Clark, Alexander, Mabrey, Melanie, Morrissey, Kay Lyn, Rao, Jyothi, Hong, Beatrice, Pierre-Louis, Marjorie, Kelly, Katherine, Jelesoff, Nicole
DOI: 10.1093/jamia/ocw123
Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB).
Author(s): Guthrie, Jennifer L, Alexander, David C, Marchand-Austin, Alex, Lam, Karen, Whelan, Michael, Lee, Brenda, Furness, Colin, Rea, Elizabeth, Stuart, Rebecca, Lechner, Julia, Varia, Monali, McLean, Jennifer, Jamieson, Frances B
DOI: 10.1093/jamia/ocw130
Despite the widespread adoption of electronic health records (EHRs), usability of many EHRs continues to be suboptimal, with some vendors failing to meet usability standards, resulting in clinician frustration and patient safety hazards. In an effort to increase EHR vendor competition on usability, recommendations have been made and legislation drafted to develop comparison tools that would allow purchasers to better understand the usability of EHR products prior to purchase. Usability [...]
Author(s): Ratwani, Raj M, Hettinger, A Zachary, Fairbanks, Rollin J
DOI: 10.1093/jamia/ocw117
The goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system.
Author(s): Chen, You, Lorenzi, Nancy M, Sandberg, Warren S, Wolgast, Kelly, Malin, Bradley A
DOI: 10.1093/jamia/ocw124
To describe the usage of a novel application (The FLOW) that allows mobile devices to be used for rounding and handoffs.
Author(s): Motulsky, Aude, Wong, Jenna, Cordeau, Jean-Pierre, Pomalaza, Jorge, Barkun, Jeffrey, Tamblyn, Robyn
DOI: 10.1093/jamia/ocw107