Search AMIA.org

Hospital census prediction has well-described implications for efficient hospital resource utilization, and recent issues with hospital crowding due to CoVID-19 have emphasized the importance of this task. Our team has been leading an institutional effort to develop machine-learning models that can predict hospital census 12 hours into the future. We describe our efforts at developing accurate empirical models for this task. Ultimately, with limited resources and time, we were able [...]

In electronic health record data, the exact time stamp of major health events, defined by significant physiologic or treatment changes, is often missing. We developed and externally validated a method that can accurately estimate these time stamps based on accurate time stamps of related data elements.

This article reviews recent literature on the use of SNOMED CT as an extension of Lee et al's 2014 review on the same topic. The Lee et al's article covered literature published from 2001-2012, and the scope of this review was 2013-2020.

As master of science in health informatics (MSc HI) programs emerge in developing countries, quality assurance of these programs is essential. This article describes a comprehensive comparative analysis of competencies covered by accredited MSc HI programs in the East African common labor and educational zone.

Multitask learning (MTL) using electronic health records allows concurrent prediction of multiple endpoints. MTL has shown promise in improving model performance and training efficiency; however, it often suffers from negative transfer - impaired learning if tasks are not appropriately selected. We introduce a sequential subnetwork routing (SeqSNR) architecture that uses soft parameter sharing to find related tasks and encourage cross-learning between them.

Cardiovascular disease (CVD) and its risk factors disproportionately affect people returning from incarceration. These individuals face multiple barriers to obtaining care, which can impact CVD and risk factor management and may be mitigated through use of a smartphone application (app). Therefore, we explored the CVD-related needs of people released from incarceration and which app features would support these needs.

While the judicious use of antibiotics takes past microbiological culture results into consideration, this data's typical format in the electronic health record (EHR) may be unwieldy when incorporated into clinical decision-making. We hypothesize that a visual representation of sensitivities may aid in their comprehension.

During the first 9 months of the coronavirus disease 2019 (COVID-19) pandemic, many emergency departments (EDs) experimented with telehealth applications to reduce virus exposure, decrease visit volume, and conserve personal protective equipment. We interviewed ED leaders who implemented telehealth programs to inform responses to the ongoing COVID-19 pandemic and future emergencies.

Clinical trials are an essential part of the effort to find safe and effective prevention and treatment for COVID-19. Given the rapid growth of COVID-19 clinical trials, there is an urgent need for a better clinical trial information retrieval tool that supports searching by specifying criteria, including both eligibility criteria and structured trial information.

COVID-19 quickly immobilized healthcare systems in the United States during the early stages of the outbreak. While much of the ensuing response focused on supporting the medical infrastructure, Columbia University College of Dental Medicine pursued a solution to triage and safely treat patients with dental emergencies amid the pandemic. Considering rapidly changing guidelines from governing bodies, dental infection control protocols, and our clinical faculty's expertise, we modeled, built, and implemented [...]