ABSTRACT
Objective To develop a war wound database that is capable of data acquisition , audit, storage, query and statistical analysis,and can be used to record wounds, diagnosis,treatment and outcomes.Methods Based on requirement analysis and database design , the basic structure and function of this database system were determined before we developed this database system by Java on Oracle 11g.Results The database had eight data modules , including basic information , wounded information , wound conditions , first aid and treatment information , medication information , surgical information , medical evacuation , and operational background .The database management system ( DBMS ) was established , and the functions were ensured .Conclusion The records of war wound in the databases are highly continuous , timely, and standardized .They can adapt to the language of medical support research and war wound treatment research .
ABSTRACT
Objective To improve the analysis efficiency and interactive experience of the Military Electronic Health Records System(MEHRS)and to realize quick response of ad-hoc queries and statistics in the MEHRS with big data columnar storage and processing technologies.Methods We carried out requirement analysis and functional design of the ad-hoc queries and statistics subsystem of the MEHRS,proposed a three-tier architecture which included the archive storage layer,statistical pretreatment layer and statistical application layer.After the selection and evaluation of big data processing technologies,CarbonData columnar storage was used to store preprocessed data and executed statistics with Spark SQL on the basis of medical business data modeling and preprocessing.Results Five testing tasks were executed on two million archives in the following two subsystems:one with modeless and non-preprocessed MongoDB storage,the other with modeled and preprocessed CarbonData storage.The latter could finish these tasks within seconds and was dozens of times more efficient than the former statistically.Conclusion This study designs and implements a big data technology proposal that satisfies the quick response of ad-hoc queries and statistics in the MEHRS, providing powerful and flexible technical support for big data statistical analysis.
ABSTRACT
Objective To store and use the military electronic health record ( EHR) data effectively , and to improve the flexibility, scalability, and statistical query performance of data storage .Methods The military EHR data access patterns were analyzed,a military EHR storage model using MongoDB document database was designed ,and the storage model was optimized by storing the whole document and the reduced summary document separately .Results The storage model was used in the military EHR system , which can meet the demands of document query and statistical query at the same time . The optimized model improves the statistical query performance without losing scalability .Conclusion This model can meet the daily needs of the EHR system and is of practical application value.