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Objective:To explore the application effect of the intelligent ward combined with DMAIC in improving the procedure and shortening the time of operation, so as to provide a reasonable basis for optimizing and improving the operation process.Methods:This was a prospective study. A total of 240 patients with gynecological surgery hospitalized in Shengjing Hospital of China Medical University from August to November 2021 were selected as the research object. From August to September 2021, the routine management mode of staff in the operating room and ward was adopted as the control group, with a total of 120 cases. From October to November 2021, the intelligent ward combined with DMAIC mode of staff in the operating room and ward was adopted as the observation group, with a total of 120 cases. The time of receiving operation notice, preoperative preparation time, preparation time of transfer personnel, waiting time after the arrival of transfer personnel and the total time of receiving operation were compared between the two groups.Results:The time of receiving operation notice was (1.42 ± 0.61) min in the observation group, which was less than that in the control group (3.53 ± 1.12) min, the difference was statistically significant ( t=18.14, P<0.05). The preoperative preparation time was (8.43 ± 1.80) min in the observation group,which was less than that in the control group (11.36 ± 2.01) min, the difference was statistically significant ( t=11.89, P<0.05). There was no significant difference in the preparation time of transfer personnel between the two groups ( P>0.05). The waiting time after the arrival of transfer personnel was 2.33(1.75, 2.93) min in the observation group, which was less than that in the control group 5.19(3.46, 8.42) min, the difference was statistically significant ( t=-10.06, P<0.05). The total time of receiving operation was (23.90 ± 4.94) min in the observation group, which was less than that in the control group (28.84 ± 4.75) min, the difference was statistically significant ( t=7.90, P<0.05). Conclusions:The intelligent ward combined with DMAIC improves the operation receiving process of the ward, shortens the total time for receiving the operation, and effectively improves the work quality and efficiency of the medical staff.
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AIM: The pre-prescription system of outpatient was established and implemented based on six sigma DMAIC model to ensure the safety of drug use and promote rational of drug use. METHODS: The rules database was made scientifically and precisely, according to DMAIC model of Six Sigma-define, measure, analyze, improve and control. The pre-prescription system of our hospital was established and improved, through adopting the prescription review mode of interception and Intervention. And the process management was continued to optimize. RESULTS: The rule-making of pre-trial system for outpatient prescription in our hospital was reasonable, and the rate of clinical approval and acceptance was high. After the system audit, the average rate of doctor's revision was 76.32%, and the average rate of Pharmacist's intervention was 63.23%, the effective rate and qualified rate of pharmacist intervention were 97.23% and 96.87%, respectively. CONCLUSION: Based on Six Sigma DMAIC model, the pre-trial system for outpatient prescription was established and implemented, which improved the level of rational drug use, effectively ensured the safety of drug use, and improved the satisfaction of patients.
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Introduction : Quality control of the laboratory has gained increased importance in the present years. 70 % of the errors in the clinical laboratory occur in the pre-analytical phase. With various guidelines to gauge the quality of the laboratory, Six Sigma Metrics remains by far the most difficult benchmark that a laboratory can achieve. We aimed to quantify the performance of the quality indicators of the routine clinical Biochemistry laboratory in the pre-analytical phase in the form of sigma metrics and devise measures and identify steps to decrease the percentage of errors by defining the DMAIC approach. Materials and Methods : One year retrospective data was collected from January, 2020 to December, 2020 from the data entry register and pre-analytical variables were quantified. Defects Per Million and sigma metric were calculated for each pre-analytical indicator. DMAIC approach was applied and post intervention sigma scores for the month of Jananuary, 2021, February, 2021 and March, 2021 were calculated. Results : Postinterventional analysis was done on a month-to-month basis to monitor the trend and also to ensure corrective action can be taken without delay. Out of 5 quality indicators which were quantified, the pre versus post sigma scores (March’21) are as follows: missing location of the patient (Sigma 4 versus 3.6), missing registration number (Sigma 3.7 versus 4.3) and both registration number and location missing (Sigma 3.6 versus 4.0), Homolysed sample (4.2 versus 4.6), insufficient sample volume (sigma 3.9 versus 4.7). Encouraging results in the form of improved Sigma scores were seen in four of the quality indicators except for the fact that the patient location were still missing in the forms and hence warrants continuous monitoring.
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Objective To improve laboratory research of generic drugs in Chinese pharmaceutical enterprises, avoid the defects in the research process, and explore the feasibility of six sigma management (DMAIC) as improvement model in the process of generic drugs laboratory research. Methods The effectiveness of DMAIC implementation was evaluated through the literature search and case study of a generic API’s process with the DMAIC model. Results The DMAIC model was successfully applied in this case. The model made laboratory research more reasonable, helped R&D personnel to pinpoint key quality attributes and process parameters, etc., ensured the authenticity and completeness of experimental data, and provided valuable data for subsequent industrial production as well as meeting registration requirements. Conclusion DMAIC model can solve the problems, such as poor overall arrangement, poor connection with production, and irregular management. It embodied the idea of Quality by Design (QbD) and can be used as good reference for domestic laboratory research of generic drugs.
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Objective@#To explore the effect of DMAIC(Define, Measure, Analyze, Improve, Control) in reducing catheter-related urinary tract infection.@*Methods@#A retrospective case control method was used to select 578 patients admitted and treated in comprehensive ICU of Tianjin First Central Hospital from January to December 2018 with catheters as research objects.The 283 patients from January to June 2018 were the control group, and 295 patients from July to December 2018 were the observation group.Routine methods were used in the control group, and DMAIC method with 6 sigma management was used in the observation group. The correct rate of implementation of each measure, the utilization rate of urinary catheter and the infection rate between the two groups were compared.@*Results@#Implementation rate of early extubation assessment, urine collection accuracy, urine tube fixed correctly, urine tube cleaning time, urine collection bags location accuracy were 60.42%(171/283), 69.61%(197/283), 79.86%(226/283), 89.40%(253/283), 92.58%(262/283)in the control group, 80.34%(237/295), 90.85%(268/295), 94.92%(280/295), 96.27%(284/295), 97.97%(289/295) in the observation group, the differences were statistically significant (χ2= 9.411-41.415, P < 0.01). The rate of urinary catheter usage was 75.31%(3 856/5 120) in the observation group and 82.60%(4 098/4 961) in the control group, the differences was statistically significant (χ2=80.475, P < 0.01). The rate of catheter associated urinary tract infection was 0.26‰ (1/3 856) in the observation group and 1.95 ‰ (8/4 098) in the control group, the differences was statistically significant (χ2=5.832, P< 0.05).@*Conclusions@#DMAIC can improve the accuracy of nursing measures, optimize the catheter care process, and reduce catheter-related urinary tract infections.