Development Of Cost-benefit Analysis Software Of Large Medical Equipments Based On PYTHON

Large medical equipment demonstrates the overall capibility of a contemporary hospital.As the requirements of hospital management, medical treatmentquality and scientific researchability ascend, the large medical equipment have been introduced into the hospital and dailyoperation of system. They havegreatly promoted the hospital management, medical treatmentand scientific research, and also have increased income. Along with decades of computertechnology development, hospital management informationization becomes moremature.Hospital information system (HIS) andPicture Archiving and Communications System(PACS) have been used more widely. Hence, it becomes more vital to accurately analyzeusage status and application trends of existing hospital large medical equipment throughscientific method, based on the data of hospital information system.This paper aims to assess the usage status of existing large medicalequipmentquantitatively, through analyzingthe daily business data in hospital informationsystems, includingincome of large medical equipment usage by patients, equipment usageamount, equipment operation and maintenance data,combining with human capital, energyconsumption, and auxiliary data. Through the analysis of these data, it can make configuration,introduction and usageof large medical equipment on the track to a healthy and promisingfuture. Rough management modewill be avoided,which only focus on expectedincome-generating withoutconsidering the actual cost. Through this research, the largemedical equipment can make the biggest economic benefits and social benefits.First, starting from the current application status at our country and abroad, a cost-benefitanalysis model of large medical equipment is built in this paper. Functional requirements andnon-functional requirements of cost-benefit analysis software of large medical equipment are analyzed.Use case model is defined, and specificationof each use caseis givenin detail.Secondly, this paperproposes the design solution and implementation techniques forcost-benefit analysis software of large medical equipment. Design models are built from thelogical view, deployment view and data view.The system uses B/S structure, MTV(Model-Template-View) pattern and multi-layer architecture. It consists of four layers, fromtop to bottom, which are the response processing layer, application processing layer, datamapping and template call layer and data services and file services layer.Finally, using Django1.3, Python2.5Apache2.2and other tools, cost-benefit analysissoftware of large medical equipment is implemented. Comprehensive unit test, functional testand performance test are performed. The average response time is less than2s; when thevolume of data is more than100,000records, the response time in history is less than8s.System testing bug rate is1.8/kloc, which achieves the original goal. And all found bugs arefixed. Now, the system has been put into trial use at the Fudan University Shanghai CancerHospital.