Objective:To estimate the burden of influenza-associated outpatient consultations in China from 2011 to 2021 surveillance years to provide a reference for developing influenza prevention, control strategies, and vaccination policies.Methods:Data on influenza-like illness (ILI) and virological confirmation of sentinel specimens from 2011 to 2021 surveillance years were extracted from China's national sentinel surveillance system. Generalized additive models were fitted to estimate influenza-associated excess ILI outpatient burden, accounting for seasonal baselines and meteorological factors.Results:Influenza was associated with an average of 1.66 (95% CI: 1.51-1.80) excess ILI consultations per 1 000 person-years (py) in China each year from 2011 to 2021 surveillance years. The influenza-associated outpatient burden was similar across different virus types/subtypes. Influenza A(H1N1)pdm09 led to a higher rate of influenza- associated ILI consultations [0.65 (95% CI: 0.53-0.76) per 1 000 py] compared to other types/subtypes. The age groups with the highest burdens were children aged 0-4 years and 5-14 years, with excess outpatient consultation rates of 15.23 (95% CI: 13.73-16.73) per 1 000 py and 13.53 (95% CI: 12.49-14.52) per 1 000 py, respectively. Conclusions:Influenza caused many outpatient consultations in China, particularly among children aged 0-14. Continuous influenza monitoring and disease burden assessment should be conducted, and close attention should be paid to the changing trends of various influenza virus types/subtypes. When formulating vaccination strategies, priority should be given to recommending vaccination for high-risk populations, such as children.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective:To estimate the burden of influenza-associated outpatient consultations in China from 2011 to 2021 surveillance years to provide a reference for developing influenza prevention, control strategies, and vaccination policies.Methods:Data on influenza-like illness (ILI) and virological confirmation of sentinel specimens from 2011 to 2021 surveillance years were extracted from China's national sentinel surveillance system. Generalized additive models were fitted to estimate influenza-associated excess ILI outpatient burden, accounting for seasonal baselines and meteorological factors.Results:Influenza was associated with an average of 1.66 (95% CI: 1.51-1.80) excess ILI consultations per 1 000 person-years (py) in China each year from 2011 to 2021 surveillance years. The influenza-associated outpatient burden was similar across different virus types/subtypes. Influenza A(H1N1)pdm09 led to a higher rate of influenza- associated ILI consultations [0.65 (95% CI: 0.53-0.76) per 1 000 py] compared to other types/subtypes. The age groups with the highest burdens were children aged 0-4 years and 5-14 years, with excess outpatient consultation rates of 15.23 (95% CI: 13.73-16.73) per 1 000 py and 13.53 (95% CI: 12.49-14.52) per 1 000 py, respectively. Conclusions:Influenza caused many outpatient consultations in China, particularly among children aged 0-14. Continuous influenza monitoring and disease burden assessment should be conducted, and close attention should be paid to the changing trends of various influenza virus types/subtypes. When formulating vaccination strategies, priority should be given to recommending vaccination for high-risk populations, such as children.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.