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OBJECTIVE： To provide experience and reference for the study of medical insurance budget impact analysis （BIA） in China. METHODS： Retrieved from PubMed， ProQuest， CNKI， Wanfang database and CBM， related literatures about medical insurance BIA research in China and the United States were collected since the establishment of the database. The basic information， analysis results and data sources were summarized and sorted out， and descriptive analysis of the included literature was carried out on basis of seven key elements such as model design， research perspective， treatment cost， reference scenario， target population， research time limit and discount/inflation， sensitivity analysis. RESULTS： A total of 72 literatures were included in this study， involving 24 （33.33％） studies in China， 48 （66.67％） studies in the United States； the indications of 45 studies were chronic diseases （62.50％）， and those of 21 studies were acute diseases （37.50％）. Among the research methods， 49 studies （68.06％） used BIA alone and 23 studies （31.94％） adopted BIA combined with pharmaceutical economics. In terms of model design， 50 studies （69.44％） adopted cost calculation models. In terms of research perspective， 60 studies （81.94％） were based on the perspective of medical insurance department research. In the calculation of treatment cost， 69 studies （95.84％） included drug cost. In terms of reference scenarios， 61 studies （84.72％） compared the economics of different drug-based treatment groups. For target population， only 31 （43.06％） studies used real world data. In terms of research duration and discount/inflation， 14 studies （19.44％） used treatment or length of hospitalization to indicate research duration， and 19 studies （26.39％） used discount rate or inflation rate to adjust costs. As for sensitivity analysis， 62 studies （86.11％） conducted sensitivity analysis， of which 49 （68.06％） used single factor sensitivity analysis. CONCLUSIONS： There are still some limitations in medical insurance BIA research literature in China and the United States， such as unreasonable use of data， incomplete coverage of the cost， and unreasonable setting of sensitivity analysis variables. It is recommended that BIA research should standardize data sources to improve the quality of budget evidence quality， reasonably evaluate market size to improve the authenticity of prediction， scientifically set variables and their scope of change to improve the stability of results， establish BIA research paradigms or evaluating standards so as to guide BIA research scientifically.
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Objective@#To evaluate the postoperative clinical effects of balloon sinuplasty on chronic rhinosinusitis.@*Methods@#PubMed, OVID, Embase, Cochrane Library, Proquest, Web of Science, Sinomed, Wan Fang and CNKI database (from established time to March of 2017) were searched for trials about the chronic rhinosinusitis treated by balloon sinuplasty. The relavent literatures were screened, and the prospective control studies were chosen. Lund-Mackay and SNOT-20 scores were used as the outcome idicators, and the methodological quality of the literatures were evaluated strictly. The extracted data were analyzed by Revman 5.3 software.@*Results@#A total of 7 prospective before-after self-controlled studies were included, and the overall quality of which was relatively high. Meta-analysis showed that the Lund-Mackay scores at 6 months post-operation, the SNOT-20 scores at 6 months and more than 1 year post-operation were significant lower than baseline when balloon sinuplasty used in the surgery; the SNOT-20 scores at more than 1 year post-operation was lower than baseline when a standalone ballon sinuplasty was performed. All the results was statistically significant (P<0.05), and all the SMD were more than 0.8.@*Conclusions@#The postoperative effect of balloon sinuplasty on chronic rhinosinusitis is obvious, and the subjective symptoms in patients is relieved effectively.
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Objective@#To evaluate the daily airborne pollen concentrations and visiting rate of patients with allergic rhinitis (AR) and their correlation during 2012-2014 in Beijing.@*Methods@#Daily airborne pollen concentrations (55 998 numbers in total and 549 numbers in average) and its constitution from April to September each year (2012 to 2014) were compared. The number of patients with AR (44 203 in total) who visited the outpatient department of Otorhinolaryngology Head and Neck Surgery, Peking University Third Hospital between January 2012 and December 2014 was analyzed by month. Using SPSS 22.0 software, Kruskal-Wallis test was done for the comparison of visiting rate of patients with AR and airborne pollen concentrations. Correlation analysis between them was made as well.@*Results@#χ2 value of airborne pollen concentrations between different months in 2012 to 2014 was 110.7, 108.4 and 121.4, respectively; all P<0.01. The airborne pollen concentrations had two peaks per year, respectively: April to May, August to September. χ2 value of visiting rate of patients with AR between different months in 2012 to 2014 was 175.0, 185.1 and 134.5, respectively; all P<0.01. Visiting rate of patients with AR showed two scattering peaks each year, respectively: April to May, August to September. The highest pollen concentration of spring (April to May) was in early and middle April. Tree pollen was the major portion in spring, which were poplar pollen, pine tree pollen, ash tree pollen, cypress tree pollen and birch trees pollen. The highest pollen concentration of autumn (August to September) was in late August and early September. Weed pollen was the major portion in summer and autumn, which were artemisia pollen, chenopodiaceae pollen and humulus japonicas pollen. The visiting rate of patients with AR showed significant correlation with airborne pollen concentrations (r value was 0.537, 0.484 and 0.566, respectively; all P<0.01).@*Conclusion@#The visiting rate of patients with AR showed positive correlation with airborne pollen concentrations in recent three years.