Search AMIA.org

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.

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.

Open discussions of social justice and health inequities may be an uncommon focus within information technology science, business, and health care delivery partnerships. However, the COVID-19 pandemic-which disproportionately affected Black, indigenous, and people of color-has reinforced the need to examine and define roles that technology partners should play to lead anti-racism efforts through our work. In our perspective piece, we describe the imperative to prioritize TechQuity-equity and social justice as [...]

Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems.

Although social and environmental factors are central to provider-patient interactions, the data that reflect these factors can be incomplete, vague, and subjective. We sought to create a conceptual framework to describe and classify data about presence, the domain of interpersonal connection in medicine.

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 [...]

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.