Objective To explore the optimization and effect analysis method of rational drug use pre-prescription review rule base for traditional Chinese medicine(TCM).Methods The rules for the modules including indications,dosage range,incompatibility,administration route and repeated drug use of TCM decoction pieces and Chinese patent medicine were set to improve pre-prescription review rule base.The prescription rationality rate and intervention effectiveness rate to evaluate effect by χ2 test before and after the system optimization.Results After the optimization of pre-prescription review rule base for TCM,the rate of prescription rationality of the hospital increased from approximately 78.19%to 94.50%,and the rate of intervention effectiveness increased from approximately 82.80%to 97.15%.There were statistically significant differences in prescription rationality and intervention effectiveness rate between pre-and post-optimization groups(P＜0.05).Conclusion According to the current pre-prescription status of the hospital,optimizing pre-prescription review rules of TCM can improve the applicability of the review system for TCM prescriptions,and enhance the pre-prescription accuracy and the level of rational medication.However,rules optimization on other modules still needs to be further improved.

Objective To explore the optimization and effect analysis method of rational drug use pre-prescription review rule base for traditional Chinese medicine(TCM).Methods The rules for the modules including indications,dosage range,incompatibility,administration route and repeated drug use of TCM decoction pieces and Chinese patent medicine were set to improve pre-prescription review rule base.The prescription rationality rate and intervention effectiveness rate to evaluate effect by χ2 test before and after the system optimization.Results After the optimization of pre-prescription review rule base for TCM,the rate of prescription rationality of the hospital increased from approximately 78.19%to 94.50%,and the rate of intervention effectiveness increased from approximately 82.80%to 97.15%.There were statistically significant differences in prescription rationality and intervention effectiveness rate between pre-and post-optimization groups(P＜0.05).Conclusion According to the current pre-prescription status of the hospital,optimizing pre-prescription review rules of TCM can improve the applicability of the review system for TCM prescriptions,and enhance the pre-prescription accuracy and the level of rational medication.However,rules optimization on other modules still needs to be further improved.

Objective To Investigate correlation between screening assay of human papillomavirus (HPV) and microbial pathogens in gynecology. Methods Cervical samples were collected to search for HPV, bacteria and yeast infections in gynecologic outpatients. HPV typing was carried out by PCR and sequencing on cervical brush specimens. Chlamydia trachomatis was identified by strand displacement amplification (SDA) and the other microorganisms were detected by conventional methods. All data were analyzed to investigate the correlation among them. Results In this cross-sectional study, among 857 enrolled outpatients, there were 266 cases with positive HPV DNA, and the rate of infection was 31.0%(266/857). HPV genotype showed that thirty-five different HPV types were identified, of which HPV16 was the most prevalent ( 14.5%, 38/262), followed by HPV58 (9.2%, 24/262), HPV53 (8.0%, 21/262)and HPV42 (6.1%, 16/262); while other genotypes were present in less than 5% of HPV positive women.According to the reclassification, the aggregated percentage (high-risk and probably high-risk) of detected HPV was 58.8% ( 154/262), 27.9% (73/262) for low-risk and 13.4% (35/262) for unknown-risk HPV types. Among HPV positive women, cervical brush specimens results showed that more than 60% cases with normal cytology, 3.8% (10/266) with high-grade squamous intraepithelial lesions (HSIL), 29. 7% (79/266) with low-grade squamous intraepithelial lesions (LSIL) and 3.0% (8/266) with atypical squamous cells of undetermined significance (ASCUS), respectively. Statistical analyses revealed there was a significant association between the infected HPV and Chlamydia trachomatis or Ureaplasma urealyticum ( >10000 CCU/ml; all P <0.01), while no correlation was found between HPV infection and bacterial vaginosis, streptococcus agalactiae, candida, Trichomonas vaginalis or Ureaplasma urealyticum ( ≤ 10000CCU/ml; all P > 0.05 ). Among the cases with bacterial vaginosis, the positive rate of HPV infected was42.6%. Chlamydia trachomatis was one of the high-risk factors for the infection of HPV ( OR = 2.82, 95%CI: 1.74 -4.57). Mycoplasma hominis was isolated only in 2 cases, no patient was infected with Neisseria gonorrhocae. Conclusions Although bacterial vaginosis was not significantly associated with HPV, it was more common among the HPV positive women. There is the significant association between HPV and Chlamydia trachomatis or Ureaplasma urealyticum which may be increase the infection of HPV. These data suggest that it may be important to screen for the simultaneous presence of different microorganisms which may have synergistic pathological effects.