Feasibility and Data Quality of the National Spinal Cord Injury Registry of Iran (NSCIR-IR): A Pilot Study.

BACKGROUND: Spinal cord injury (SCI) is one of the most disabling consequences of trauma with unparalleled economic, social, and personal burden. Any attempt aimed at improving quality of care should be based on comprehensive and reliable data. This pilot investigation studied the feasibility of implementing the National Spinal Cord and Column Injury Registry of Iran (NSCIR-IR) and scrutinized the quality of the registered data. METHODS: From October 2015 to May 2016, over an 8-month period, 65 eligible trauma patients who were admitted to hospitals in three academic centers in mainland Iran were included in this pilot study. Certified registered nurses and neurosurgeons were in charge of data collection, quality verification, and registration. RESULTS: Sixty-five patients with vertebral column fracture dislocations were registered in the study, of whom 14 (21.5%) patients had evidence of SCI. Mechanisms of injury included mechanical falls in 30 patients (46.2%) and motor vehicle accidents in 29 (44.6%). The case identification rate i.e. clinical and radiographic confirmation of spine and SCI, ranged from 10.0% to 88.9% in different registry centers. The completion rate of all data items was 100%, except for five data elements in patients who could not provide clinical information because of their medical status. Consistency i.e. identification of the same elements by all the registrars, was 100% and accuracy of identification of the same pathology ranged from 66.6% to 100%. CONCLUSIONS: Our pilot study showed both the feasibility and acceptable data quality of the NSCIR-IR. However, effective and successful implementation of NSCIR-IR data use requires some modifications such as presence of a dedicated registrar in each center, verification of data by a neurosurgeon, and continuous assessment of patients' neurological status and complications.

Developing SNOMED-CT for decision making and data gathering: a software prototype for low back pain.

The issue of medical errors is currently a global concern which places a heavy financial and emotional burden on communities. A clinical decision support system (CDSS) is an electronic system designed to support clinical decision making. Considering the increasing importance and use of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), we developed SNOMED-CT to implement it more efficiently in making smart history taking, decisions to perform lab tests and imaging, diagnosis and recommendations. To evaluate these capabilities in real clinical problems, a new CDSS was compiled, aimed at supporting decisions on patients with a chief complaint of low back pain (LBP). A number of LBP differential diagnoses as well as some recommended indications and contraindications published by guidelines, were inputted to the database. Future software based on this model would help physicians to do necessary assessments and recommendations and might improve patients' safety.