1.Deployment practice and exploration of cloud desktop technology for domestic substitution
Yaoke MAO ; Guiliang WU ; Yi ZHANG ; Haoshuang HAN
Modern Hospital 2025;25(8):1153-1156
The accelerated advancement of medical informatization has increasingly highlighted the limitations of tradi-tional PC terminals in terms of data security,operational efficiency,and resource integration.Cloud desktop technology has e-merged as a viable solution for hospital informatization,offering both cost-effectiveness and operational efficiency while fulfilling domestic substitution requirements.This study implemented a comprehensive cloud desktop management system by utilizing exist-ing hospital IT infrastructure supplemented with newly deployed cloud desktop servers and terminal devices.The system signifi-cantly improved hardware/software resource utilization and management efficiency,delivering stable and high-performance cloud desktop services to meet growing clinical and administrative demands.This study showcased a hospital cloud desktop deployment as a case study,exploring healthcare informatization solutions based on cloud desktop technology.The technical architecture,de-ployment strategy,implementation pathway,and effectiveness evaluation were analyzed to investigate the application of cloud desktop technology in healthcare settings.The results indicate that cloud desktop technology can significantly improve operational efficiency,reduce maintenance costs,and provide foundational support for smart hospital construction.
2.Application and verification of moving average seasonal index method in predicting emergency depart-ment visits
Yi ZHANG ; Guilian WU ; Yaoke MAO ; Yuejiao TUO
Modern Hospital 2025;25(9):1386-1390
Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13%to 8.81%,with an average relative error of 4.22%.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26%),while the second quarter is the low point(95.91%).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.
3.Deployment practice and application effectiveness analysis of hospital virtualization platform
Yaoke MAO ; Guiliang WU ; Yi ZHANG ; Yuejiao TUO
Modern Hospital 2025;25(10):1581-1584
With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.
4.Application and verification of moving average seasonal index method in predicting emergency depart-ment visits
Yi ZHANG ; Guilian WU ; Yaoke MAO ; Yuejiao TUO
Modern Hospital 2025;25(9):1386-1390
Objective This study aims to apply the moving average method of time series analysis to forecast outpatient and emergency department visits at our hospital for 2024.Additionally,we will validate the trend prediction model against actual visit data from January to April 2024,assessing the accuracy of the time series fitting.The insights generated will serve as a sci-entific foundation for the hospital to allocate resources effectively,formulate work plans,and meet annual objectives.Methods We collected data on outpatient and emergency visits from 2020 to 2023(n=16 periods)and employed the four moving average method for time series decomposition.We calculated the adjusted seasonal index values and developed a linear trend prediction model(Y=7 3847+568.08t)that incorporates seasonal factors.We then computed the predicted monthly outpatient emergency visits for 2024 and compared these forecasts with actual values from the first four months of 2024 to test the model's reliability.Results The predicted visits for the first four months of 2024 were 84 396,80 633,88 244,and 84 158 respectively.The rela-tive errors compared to actual figures ranged from 1.13%to 8.81%,with an average relative error of 4.22%.The seasonal indi-ces revealed that the third quarter represents the peak period(104.26%),while the second quarter is the low point(95.91%).Conclusion The moving average seasonal index method effectively captures the seasonal variations in outpatient and emergency department visits,offering high prediction accuracy.This methodology can assist hospitals in dynamically adjusting their schedu-ling and optimizing resource allocation.
5.Deployment practice and application effectiveness analysis of hospital virtualization platform
Yaoke MAO ; Guiliang WU ; Yi ZHANG ; Yuejiao TUO
Modern Hospital 2025;25(10):1581-1584
With the popularization of computer software technology and the development of hospital informatization,virtu-alization technology-as a key technology supporting IT infrastructure-has seen continuously expanding market demand and ap-plication scenarios.In recent years,domestic virtualization manufacturers have increased investment in independent innovation,achieving breakthroughs in virtualization software and related technologies,along with iterative product updates.This has enabled them to catch up with and surpass foreign virtualization technologies,providing more personalized virtualization products for Chi-nese enterprises.Hospitals operate multiple systems such as HIS databases,Electronic Medical Record Systems(EMRS),Pic-ture Archiving and Communication Systems(PACS),and Laboratory Information Systems(LIS).Migrating these systems from a purely physical machine environment to a virtualization platform,and using CNware virtualization products to manage existing physical resources in the data center,enables the sharing and integration of computing resources such as server resources,storage resources,and memory resources.This improves hardware utilization and software operation efficiency,achieves significant appli-cation results,and continuously enhances the quality of medical informatization services.
6.Deployment practice and exploration of cloud desktop technology for domestic substitution
Yaoke MAO ; Guiliang WU ; Yi ZHANG ; Haoshuang HAN
Modern Hospital 2025;25(8):1153-1156
The accelerated advancement of medical informatization has increasingly highlighted the limitations of tradi-tional PC terminals in terms of data security,operational efficiency,and resource integration.Cloud desktop technology has e-merged as a viable solution for hospital informatization,offering both cost-effectiveness and operational efficiency while fulfilling domestic substitution requirements.This study implemented a comprehensive cloud desktop management system by utilizing exist-ing hospital IT infrastructure supplemented with newly deployed cloud desktop servers and terminal devices.The system signifi-cantly improved hardware/software resource utilization and management efficiency,delivering stable and high-performance cloud desktop services to meet growing clinical and administrative demands.This study showcased a hospital cloud desktop deployment as a case study,exploring healthcare informatization solutions based on cloud desktop technology.The technical architecture,de-ployment strategy,implementation pathway,and effectiveness evaluation were analyzed to investigate the application of cloud desktop technology in healthcare settings.The results indicate that cloud desktop technology can significantly improve operational efficiency,reduce maintenance costs,and provide foundational support for smart hospital construction.

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