Abstract - Insufficient, disjointed and un-interoperable health care systems are the major causes of iatrogenic injuries by the means of adverse events (AE). Consequently, detecting and analyzing such events reveal problems affecting not only health care providers (HCP) and patients, but also the whole community. In this research we aim to architect a conceptual data flow model that helps in optimizing patient’s safety by the means of a newly designed Unified Medical Coding Structure (UMCS) and Structured Evidence Based Medicine (SEBM). Using this model we can assist in supporting clinical decisions at the point of care, preventing AEs as much as possible and collecting data when any missing AE occurred to be analyzed and used in setting rules
