The DOD and VA have created a joint vision registry with the goal of improving service member and veterans’ outcomes by the prevention, diagnosis, mitigation, treatment and rehabilitation of disorders of the visual system. The registry is designed to track and optimize outcomes by utilizing data abstraction (from multiple sources), analysis, research, and statistic prediction. Knowledge Analytics Incorporated (KAI) was tasked to develop an idealized, semantically-enabled information model to support the abstraction of clinical medical information of eye injury patients. Abstracted data is stored into a computable database called the Defense and Veterans Eye Injury and Vision Registry (DVEIVR) Pilot and VA Eye Injury Data Store. The idealized information model/ontology is being developed using KAIs analytical tool suite which allows subject matter experts (SME) to independently specify ontological types, meanings, and relationships. The tool suite allowed: 1. SMEs to define the information model/ontology using types and value sets. 2. Compile this model into a programming implementation (Currently Java) 3. Create instances of the model types (i.e. Patient with an Ocular Trauma). 4. Perform analytics on the set of patients (Registry) using operational rules or statistical analysis (R Statistical Package).

propecia online canada
weight loss supplements that actually work
vytorin cost
viagra without prescription
singulair medicine
synthroid 100 mcg
gabapentin 100mg
cialis without a prescription
blood pressure medicine lisinopril
how to lose fat fast
where to buy viagra pills
tamiflu medicine
стрижки на средние волосы с челкой
crestor dosage
discount prescription drugs
app collaboration
buy cialis online safely
software collaboration

Included in the development of the idealized information model, KAI focused its efforts on the specification of Interocular Foreign Bodies (IOFB) within the model, as well as IOFB material properties. Also included in this task was the specification and use of the RxNORM drug ontology and use of drug categories for the purpose of improving outcomes.