Search AMIA.org

To assess the functionality and feasibility of the GROWIN app for promoting early detection of growth disorders in childhood, supporting early interventions, and improving children's lifestyle by analyzing data collected over 3 years (2018-2020).

Patients in the intensive care unit (ICU) are often in critical condition and have a high mortality rate. Accurately predicting the survival probability of ICU patients is beneficial to timely care and prioritizing medical resources to improve the overall patient population survival. Models developed by deep learning (DL) algorithms show good performance on many models. However, few DL algorithms have been validated in the dimension of survival time or compared [...]

Both academic medical centers and biomedical research sponsors need to understand impact of scientific funding to determine value. For the National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) hubs, tracking research activities can be complex, often involving multiple institutions and continually changing federal reporting requirements. Existing research administrative systems are institution-specific and tend to focus only on parts of a greater whole. The goal of this case [...]

HL7 SMART on FHIR apps have the potential to improve healthcare delivery and EHR usability, but providers must be aware of the apps and use them for these potential benefits to be realized. The HL7 CDS Hooks standard was developed in part for this purpose. The objective of this study was to determine if contextually relevant CDS Hooks prompts can increase utilization of a SMART on FHIR medical reference app [...]

We investigated how the electronic health records (EHRs) strategies concerning EHR sourcing and vendor switching impact user satisfaction over time.

The purpose of the study was to develop and validate a model to predict the risk of experiencing a fall for nursing home residents utilizing data that are electronically available at the more than 15 000 facilities in the United States.

To develop and validate a standards-based phenotyping tool to author electronic health record (EHR)-based phenotype definitions and demonstrate execution of the definitions against heterogeneous clinical research data platforms.

Participation in healthcare research shapes health policy and practice; however, low trust is a barrier to participation. We evaluated whether returning health information (information transparency) and disclosing intent of data use (intent transparency) impacts trust in research.

The Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program is a consortium of community-engaged research projects with the goal of increasing access to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests in underserved populations. To accelerate clinical research, common data elements (CDEs) were selected and refined to standardize data collection and enhance cross-consortium analysis.