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To evaluate the performance of "Vaccination Rates Monitoring Report System" implemented by Shenzhen CDC, we conducted an analysis of the data quality and identify key areas for system improvement. Following evaluation guidelines provided by WHO and United States CDC, we established six evaluation attributes: representativeness, simplicity, acceptability, data reliability, stability and timeliness. In eastern, central and western regions of Shenzhen, we selected one district from each region, of which the local CDC and ten CHSCs under jurisdiction were chosen for evaluation. On-site inspections, questionnaires survey and interviews were utilized for data collection, while the Likert scale method was used for attributes rating evaluation. A total of 70 participants were surveyed, consisting of 60 CHSCs and 10 CDCs staff. The gender ratio was 1:2.5 (males to females), with the majority falling within the 25-34 age range (46%). Most participants held full-time positions (80%) and had more than 5 years of work experience (62%). The system achieved 100% coverage of all CHSCs and CDCs (100%). The cumulative percentage scores for the overall favorable options of simplicity, acceptability, data reliability, stability, and timeliness were 79%, 85%, 73%, 50%, and 71% respectively. The system operates normally with strong representativeness. Acceptability was rated as "good." Simplicity, data reliability, and system timeliness were rated as "average," while system stability was rated as "poor." Based on these survey results, developers should urgently investigate reasons for poor stability, particularly addressing concerns from CHSCs users. Additionally, the issues and shortcomings identified in other attributes should also be gradually improved.

Objectives: Healthcare-associated infections (HAIs) represent a major threat to patient safety and are associated with significant economic burden. Calculating the costs attributable to HAIs is challenging given the various sources of bias. Although HAIs as a reasonably preventable medical harm should have been closely linked to medical insurance incentives, there was little linkage between HAIs and medicare in western China owing to the lack of economic evaluation data. The present study aimed to generate estimates of the attributable costs associated with HAIs and the magnitude of costs growth., Methods: In this cohort study designed horizontally and vertically from 2016 to 2022, we compared outcomes of randomly sampling patients with HAIs and individually matched patients without HAIs in two cohorts at a 6-year interval at 34 hospitals in western China. The primary outcome was the direct medical cost for the entire hospital stay, converted to US dollars ($ for the benchmark year), discounted at 3% annually, and estimated separately in the full analysis set (FAS) and the per protocol set (PPS). We used multiple linear regression to adjust the discounted costs and to assess subgroups effects within each cohort. We nested a dynamic vertical comparison of costs attributable to HAIs between the front and rear cohorts., Results: A total of 230 patients with HAIs in 2016 and 204 patients with HAIs in 2022 were enrolled. After a 1:1 match, all 431 pairs were recruited as FAS, of which 332 pairs as PPS met all matching restrictions. Compared to the 2016 cohort in FAS, the patients with HAIs in 2022 had a significantly older age (64.40 ± 16.45 years), higher repeat hospitalization rate (65 [32.02%] of 203), and lower immune function (69 [33.99%] of 203). The discounted costs and adjusted-discounted costs for patients with HAIs in the 2022 cohort were found to be significantly higher than those of patients without HAIs (discounted costs: $5484.60 [IQR 8426.03] vs $2554.04(4530.82), P < 0.001; adjusted-discounted costs: $5235.90 [3772.12] vs $3040.21(1823.36), P < 0.001, respectively), and also higher than those of patients with HAIs in the 2016 cohort (discounted costs: $5484.60 [8426.03] vs $3553.00 [6127.79], P < 0.001; adjusted-discounted costs: $5235.90 [3772.12] vs $3703.82 [3159.14], P < 0.001, respectively). In vertical comparison of PPS, the incremental costs of the 2022 cohort are 1.48 times higher than those of the 2016 cohort ($964.63(4076.15) vs $652.43 [2533.44], P = 0.084)., Conclusions: This meticulously designed study in western China has successfully and accurately examined the economic burden attributable to HAIs. Their rapidly increasing tendency poses a serious challenge to patients, hospitals, and the medical insurance. A closer linkage between HAIs and ongoing motivating system changes is urgently needed in western China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Created by the US National Organ Transplant Act in 1984, the Scientific Registry of Transplant Recipients (SRTR) is obligated to publicly report data on transplant program and organ procurement organization performance in the United States. These reports include risk-adjusted assessments of graft and patient survival, and programs performing worse or better than expected are identified. The SRTR currently maintains 43 risk adjustment models for assessing posttransplant patient and graft survival and, in collaboration with the SRTR Technical Advisory Committee, has developed and implemented a new systematic process for model evaluation and revision. Patient cohorts for the risk adjustment models are identified, and single-organ and multiorgan transplants are defined, then each risk adjustment model is developed following a prespecified set of steps. Model performance is assessed, the model is refit to a more recent cohort before each evaluation cycle, and then it is applied to the evaluation cohort. The field of solid organ transplantation is unique in the breadth of the standardized data that are collected. These data allow for quality assessment across all transplant providers in the United States. A standardized process of risk model development using data from national registries may enhance the field.

Unlabelled: The current system granting liver transplant candidates with hepatocellular carcinoma (HCC) additional Model for End-Stage Liver Disease (MELD) points is controversial due to geographic disparity and uncertainty regarding optimal prioritization of candidates. The current national policy assigns a MELD exception score of 22 immediately upon listing of eligible patients with HCC. The aim of this study was to evaluate the potential effects of delays in granting these exception points on transplant rates for HCC and non-HCC patients. We used Scientific Registry of Transplant Recipients data and liver simulated allocation modeling software and modeled (1) a 3-month delay before granting a MELD exception score of 25, (2) a 6-month delay before granting a score of 28, and (3) a 9-month delay before granting a score of 29. Of all candidates waitlisted between January 1 and December 31, 2010 (n = 28,053), 2773 (9.9%) had an HCC MELD exception. For HCC candidates, transplant rates would be 108.7, 65.0, 44.2, and 33.6 per 100 person-years for the current policy and for 3-, 6-, and 9-month delays, respectively. Corresponding rates would be 30.1, 32.5, 33.9, and 34.8 for non-HCC candidates., Conclusion: A delay of 6-9 months would eliminate the geographic variability in the discrepancy between HCC and non-HCC transplant rates under current policy and may allow for more equal access to transplant for all candidates., (© 2015 by the American Association for the Study of Liver Diseases.)

Few equations have been developed to predict end-stage renal disease (ESRD) after deceased donor liver transplant. This retrospective observational cohort study analyzed all adult deceased donor liver transplant recipients in the Scientific Registry of Transplant Recipients (SRTR) database, 1995-2010. The prediction equation for ESRD was developed using candidate predictor variables available in SRTR after implementation of the allocation policy based on the model for end-stage liver disease. ESRD was defined as initiation of maintenance dialysis therapy, kidney transplant or registration on the kidney transplant waiting list. We used Cox proportional hazard models to develop separate equations for assessing risk of ESRD by 6 months posttransplant and between 6 months and 5 years posttransplant. Variables in the 6-month equation included recipient age, history of diabetes, history of dialysis before liver transplant, history of malignancy, body mass index, serum creatinine and liver donor risk index. Variables in the 6-month to 5-year equation included recipient race, history of diabetes, hepatitis C status, serum albumin, serum bilirubin and serum creatinine. The prediction equations have good calibration and discrimination (C statistics 0.74-0.78). We have produced risk prediction equations that can be used to aid in understanding the risk of ESRD after liver transplant., (© Copyright 2013 The American Society of Transplantation and the American Society of Transplant Surgeons.)