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Objective:Patient risk-based statistical quality control (SQC) program was designed for 9 specific protein projects using Westgard sigma rules with run length.Methods:The cumulative coefficient of variation of immunoglobulin (Ig)G, IgA, IgM, C3, C4, rheumatoid factor (RF), antistreptolysin O (ASO), transferrin (TRF) and prealbumin (PA) from the laboratory department of Beijing Tongren Hospital between December 2018 to May 2019 were used as the estimated value of imprecision. The mean of the absolute value of the percentage difference of 10 batches in the laboratory, which was derived from the results of participating the external quality assessment (EQA), was used as the estimated value of bias. The National Center for Clinical Laboratories EQA evaluation criteria was used as an allowable total error (TEa), and the sigma value of each project (σ) was calculated. Westgard Sigma rule with run length was used to design appropriate SQC program for each project, including quality control rules, number of control measurements (N) and frequency of quality control.Results:The sigma value was larger than 6 for SQC procedure of IgG, IgA, IgM, C4 and TRF. SQC could be established with the use of 1 3s rule, number of control measurements (N)=2, number of runs (R)=1, and a run length of 1 000 patient samples. Combined with the average daily workload, internal quality control could be conducted once every 10 days for IgG, IgA, IgM and C4, every 50 days for TRF. The σ was 5.86 for C3, SQC program could be established with run length of 450 using 1 3S/2 2S/R 4s rule (N=2, R=1), combined with average daily workload, internal quality control could be conducted every 4.5 days. σ was between 3 and 4 for RF, ASO and PA. With the use of 1 3S/2 2S/R 4s/4 1s/6 X rule (N=6, R=1), SQC program with a run length of 45 and higher frequency internal quality control activities. Conclusion:It is feasible to use Westgard sigma rules with run length for the laboratories design of personalized risk-based SQC procedures, the method is very simple and intuitive. This tool is valued to be recommended to be actively applied by all clinical laboratories.
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Background & objectives: The models for implementation of antibiotic stewardship programme (ASP) in the acute care settings of developing countries are lacking. In most of the hospitals, patient turnover is high and a proper system for recording antibiotic-related information and tracking hospital-acquired infections is not in place. This pilot study was conducted in a tertiary care teaching hospital in north India to assess the feasibility of implementation of an ASP in a Medicine unit and to evaluate the effect of implementation as per the criteria applicable in this set up. Methods: A pre-post-quasi-experimental non-randomized study was conducted in two phases. In the first phase, current practices in the Medicine wards were observed. In the second phase, the ASP was implemented in a single Medicine unit, along with prospective audit and feedback, tracking of the process, as well as outcome measures. Patient risk stratification, blood culture on day one, day 3 bundle, dose optimization, de-escalation and intravenous to oral conversion of antibiotics were the key elements focused upon. Results: There was a significant improvement in the appropriateness of antibiotic prescription (66 vs. 86%, P<0.001) and reduction in the mean number of antibiotics used per person (4.41 vs. 3.86, P<0.05) along with decrease in the duration of hospital stay (17 vs. 14 days, P<0.05). There was a significant improvement in sending of blood cultures on day one during the stewardship phase (P<0.001). Interpretation & conclusions: The ASP approach used in our pilot study may be feasible and beneficial. However, it needs further confirmation in other settings and on a large scale.
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BACKGROUND: Surveillance of surgical site infection is a main component of nosocomial infection surveillance. To perform a valid comparison of rates among hospitals, among surgeons, across time, surgical site infection rates must account for the variation in patient's underlying severity of illness and other important risk factors. So, a risk index was developed to predict a surgical patient's risk of acquiring a surgical site infection. The risk index score, ranging from 0 to 3, was the number of risk factors present among the following: (1) a patient with an American Society of Anesthesiologists preoperative assessment score of 3,4,5, (2) an operation classified as contaminated or dirty-infected, and (3) an operation lasting over T hours, where T depends upon the operative procedure being performed. METHOD: We performed surgical site infection surveillance according to patient risk index after cardiovascular surgery from Mar 1, 1997 to May 31, 1997. In addition, we also monitored nosocomial infection of all patients after cardiovascular surgery Data was collected prospectively, Surgical site infection rate was classified according to patient risk index and compared with NNIS (National Nosocomial Infections Surveillance) semiannual report of 1995. RESULT: Overall nosocomial infection rate was 18.9% and among all patients detected by surveillance protocols, pneumonia was the most common (6.3%) nosocomial infection after cardiovascular surgery, and the remaining infections were distributed as follows: surgical site infection 45%, urinary tract infection 3.2%, bloodstream infection 3.2%. Surgical site infection rate for patient with scores of 0, 1, 2 and 3 were 0%, 3.1%, 4.6%, 66,7%, respectively and increased according to patient risk index (P0.05). CONCLUSION: The patient risk index is a better predictor d surgical site infection risk than the traditional wound classification system and surgical site infection surveillance with patient risk index is useful for nosocomial infection surveillance after surgery.