AMIA People and Organizational Issues Working Group, AMIA Evaluation Working Group (WG), with participation from the IMIA Technology Assessment & Quality Development in Health Informatics WG and the EFMI Evaluation WG present this webinar.
Natural language processing (NLP) is increasingly used to tackle the huge volume of information available in both the free text of medical records, and in the life science literature.
To create interoperability across regions in LMICs a practical architecture solution for all partners to follow must exist. OpenHIE empowers LMICs to pragmatically implement sustainable health information sharing architectures that measurably improve health outcomes. In this webinar, participants will be introduced to OpenHIE and encouraged to discuss its use.
After participating in this activity, the learner should be better able to:
The complexity of patient care data magnifies the importance of implementing consistent, critical, structured data elements within electronic patient records. Interoperability and data sharing are reliant on data standardization; however, health care data management presents unique challenges in an environment of continual change.
The Informatics Paper Club of the Air presented by the AMIA CIS-WG is a regularly scheduled Paper Club series that will address the gap in knowledge and performance by an ongoing review of literature and by exposing our clinical informaticists to evidence-based approaches and strategies with discussions centered on incorporating those strategies into their practices.
The theme for the next few episodes will be open notes. The following two papers will be discussed during this webinar:
The reuse of EHR data is a promising complement to traditional, prospective approaches to various activities involved in healthcare improvement, including, but not limited to, clinical research and the evaluation and improvement of care. Existing clinical data sources provide opportunities for efficient analyses and can be expected to be representative of the populations of interest.
Rapid growth in the clinical implementation of large electronic medical records (EMRs) has led to an unprecedented expansion in the availability of dense longitudinal datasets for clinical and translational research. Secondary use of EMR data for clinical and translational research is hampered by the fact that much of detailed patient information is embedded in narrative text. Natural Language Processing (NLP) technologies, which are able to convert unstructured clinical text into coded data, have been introduced into the biomedical domain and have demonstrated promising results.
Informatics research that crosses institutional boundaries brings challenges, particularly when research questions focus on contextual factors, evaluation, and other people or organizational issues. This webinar will bring researchers together to participate in a facilitated discussion of experiences in collaborating across institutions. Topics will include collaborating on grant proposals, IRB issues, communication tools and strategies, collaborative writing, international collaborations, how the Working Groups can help, and others identified by participants.
What are the priorities for hospital or clinic patients to have dental as well as medical patient records available in the facility's EHR? Let us imagine that hospitals and clinics want to know, for the sake of quality and safety of care, for both inpatients and outpatients, what each patient's dental treatment record shows. Patients who should have a dental record on file in the EHR would be underserved with regard to oral health care access if a dental record were not available. The first impact would be to highlight which patients have not been receiving routine preventive dental care.
The AMIA Genomics and Translational Bioinformatics working group is proud to present their latest webinar. This webinar will present the Harvard School of Medicine’s PIC-SURE Center of Excellence for Big Data Computing- Patient-Centered Information Commons: Standardized Unification of Research Elements. PIC-SURE was established in September 2014 as part of the NIH Big Data to Knowledge (BD2K) Initiative’s Centers of Excellence for Big Data Computing program.