Search AMIA.org

As coronavirus disease 2019 (COVID-19) started its rapid emergence and gradually transformed into an unprecedented pandemic, the need for having a knowledge repository for the disease became crucial. To address this issue, a new COVID-19 machine-readable dataset known as the COVID-19 Open Research Dataset (CORD-19) has been released. Based on this, our objective was to build a computable co-occurrence network embeddings to assist association detection among COVID-19-related biomedical entities.

Improving outcomes of transplant recipients within and across transplant centers is important with the increasing number of organ transplantations being performed. The current practice is to analyze the outcomes based on patient level data submitted to the United Network for Organ Sharing (UNOS). Augmenting the UNOS data with other sources such as the electronic health record will enrich the outcomes analysis, for which a common data model (CDM) can be [...]

Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictive model coupled with effective, patient-centered interventions.

Social determinants of health play an important role in the likelihood of readmission and therefore should be considered in care transition planning. Unfortunately, some social determinants that can be of value to care transition planners are missing in the electronic health record. Rather than trying to understand the value of data that are missing, decision makers often exclude these data. This exclusion can lead to failure to design appropriate care [...]

An electronic pathway for the management of adhesive small bowel obstruction (SBO) was built and implemented on top of the electronic health record. The aims of this study are to describe the development of the electronic pathway and to report early outcomes.

With the increased usage of dashboard reporting systems to monitor and track patient panels by clinical users, developers must ensure that the information displays they produce are accurate and intuitive. When evaluating usability of a clinical dashboard among potential end users, developers oftentimes rely on methods such as questionnaires as opposed to other, more time-intensive strategies that incorporate direct observation.

An area deprivation index (ADI) is a geographical measure that accounts for socioeconomic factors (e.g., crime, health, and education). The state of Ohio developed an ADI associated with infant mortality: Ohio Opportunity Index (OOI). However, a powerful tool to present this information effectively to stakeholders was needed.