Search AMIA.org

Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due to the lack of tools for the management of such findings and the time required to maintain up-to-date lists. Natural language processing (NLP) is capable of extracting information from free-text clinical documents and could provide the basis for software [...]

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 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.

Complex electronic medical records (EMRs) presenting large amounts of data create risks of cognitive overload. We are designing a Learning EMR (LEMR) system that utilizes models of intensive care unit (ICU) physicians' data access patterns to identify and then highlight the most relevant data for each patient.

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 [...]

Rule-based data quality assessment in health care facilities was explored through compilation, implementation, and evaluation of 63,397 data quality rules in a single-center case study to assess the ability of rules-based data quality assessment to identify data errors of importance to physicians and system owners.

This study was aimed to explore the intersection between organizational environment, workflow, and technology in pediatric emergency departments (EDs) and how these factors impact antibiotic prescribing decisions.

Although patients who work and have related health issues are usually first seen in primary care, providers in these settings do not routinely ask questions about work. Guidelines to help manage such patients are rarely used in primary care. Electronic health record (EHR) systems with worker health clinical decision support (CDS) tools have potential for assisting these practices.