SAND Technology announced its new high-performance Healthcare Analytic Server the product is designed to make the information contained in electronic medical records more easily and inexpensively available to the full health care community, including researchers and administrators, with minimal need for involvement by IT resources.
The SAND Healthcare Analytic Server includes:
- An automated process to manage the extraction and transformation of data from medical systems.
- A specialized data model to translate complex health data into information that is meaningful to the different sectors of the healthcare organization.
- A patient privacy protection component based on the 3DES encryption standard.
- A SNOMED batch encoder used to integrate semi-structured (free text) medical information, for example medical notes.
- User-friendly report generation and ad hoc query interfaces.
- A data segmentation tool for providing precise extracted data samples to researchers.
The system is modular, providing entry capabilities for institutions at any stage of operational automation. It can be configured to suit different departmental functions:
The SAND Discharge Record Analytic Server enables analytics on a healthcare organization's discharge database. This solution can be quickly implemented for organizations of any size, and delivers a 360-degree view of discharge information to a variety of departments, including administration, professional services, health record managers, and researchers.
The SAND Laboratory Analytic Server combines laboratory data with discharge record data. The result can be coupled with disease and/or medical procedure data to enable a better understanding of healthcare practices or to support health demographic studies.
The SAND Clinical Analytic Server integrates the Electronic Patient Record into the analytic platform. For healthcare organizations that have implemented an Electronic Patient Record system, this enables analysis of all aspects of a clinical pathway and can be used to monitor and analyze clinical practices as well as to track organizational efficiency.
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