Objective To explore the present situation of the efficiency about public tertiary general hospitals in Shandong province, measure and compare the efficiency and the state of returns to scale of hospitals under different bed scales. Methods Based on the input and output data of 137 public tertiary general hospitals in Shandong province in 2017, two input indicators (the number of employees and the number of actual beds) and two output indicators (the total number of outpatients and emergent patients, and the number of discharges) were selected. The technical efficiency, pure technical efficiency and scale efficiency of sample hospitals were calculated by using data envelopment analysis, and a comparative analysis was carried out under different bed scales. Results Of the 137 public tertiary general hospitals, the mean of technical efficiency value was 0.666, the medians of pure technical efficiency value and scale efficiency value in 2017 were 0.817 and 0.919, respectively. In the 137 sample hospitals, there were 132 hospitals (96.4%) in ineffective status; there were 90 hospitals (65.7%) exhibiting increasing returns to scale, 11 hospitals (8.0%) exhibiting constant returns to scale, and 36 hospitals (26.3%) exhibiting decreasing returns to scale. There were significant differences in hospital efficiency and returns to scale under different bed sizes (P<0.001), and the scale efficiency was the highest when the bed size was 1001-2000. Conclusions The overall operating efficiency of the public tertiary general hospitals in the province was not high yet. Most hospitals were in ineffective status and most of them were in the state of increasing returns to scale. The optimal scale of actual beds is between 1001 and 2000 beds from the perspective of scale efficiency.
Sharing clinical trial data can increase the transparency of clinical trials and improve the its authenticity. The current requirements of clinical research data transparency is not fully adequate, and it is still difficult to create an environment in which the sharing of the clinical trial data becomes the norm. The article analyzed various concerns on data sharing and proposed solutions in data ownership, technology, implementation, and legal issues systematically, calling for clinical trial data sharing in order to promote transparency of clinical trials, and looking forward to minimize the risks and maximize the benefits of data sharing.
Objective To establish a predictive model for long-term tumor-specific survival after surgery for patients with intermediate to advanced medullary thyroid cancer (MTC) based on American Joint Committee on Cancer (AJCC) TNM staging, by using the Surveillance, Epidemiology, and End Results (SEER) Database. Methods The data of 692 patients with intermediate to advanced MTC who underwent total thyroidectomy and cervical lymph node dissection registered in the SEER database during 2004–2017 were extracted and screened, and were randomly divided into 484 cases in the modeling group and 208 cases in the validation group according to 7∶3. Cox proportional hazard regression was used to screen predictors of tumor-specific survival after surgery for intermediate to advanced stage MTC and to develop a Nomogram model. The accuracy and usefulness of the model were tested by using the consistency index (C-index), calibration curve, time-dependent ROC curve and decision curve analysis (DSA). Results In the modeling group, the multivariate Cox proportional hazard regression model indicated that the factors affecting tumor-specific survival after surgery in patients with intermediate to advanced MTC were AJCC TNM staging, age, lymph node ratio (LNR), and tumor diameter, and the Nomogram model was developed based on these results. The modeling group had a C-index of 0.827 and its area under the 5-year and 10-year time-dependent ROC curves were 0.865 [95%CI (0.817, 0.913)], 0.845 [95%CI (0.787, 0.904)], respectively, and the validation group had a C-index of 0.866 and its area under the 5-year and 10-year time-dependent ROC curves were 0.866 [95%CI (0.798, 0.935)] and 0.923 [95%CI (0.863, 0.983)], respectively. Good agreement between the model-predicted 5- and 10-year tumor-specific survival rates and the actual 5- and 10-year tumor-specific survival rates were showed in both the modeling and validation groups. Based on the DCA curve, the new model based on AJCC TNM staging was developed with a significant advantage over the former model containing only AJCC TNM staging in terms of net benefits obtained by patients at 5 years and 10 years after surgery. Conclusion The prognostic model based on AJCC TNM staging for predicting tumor-specific survival after surgery for intermediate to advanced MTC established in this study has good predictive effect and practicality, which can help guide personalized, precise and comprehensive treatment decisions and can be used in clinical practice.
Data integrity, accuracy, and traceability are key elements of high-quality clinical research, as well as weak links in the promotion of clinical research transparency. How to promote data quality has become a major concern to all clinical research stakeholders. In this article, we dissected and analyzed data generation and capturing process in clinical research, and identified a key aspect in improving data quality: to promote electronic source data, especially to break the barrier between electronic health records and clinical research systems. Additionally, we summarized the experiences regarding this issue in China and overseas to propose a solution suitable for China to improve data quality in clinical research: to strengthen clinical research source data management by building clinical research source data platform and adopt common source data management process in hospitals.
Objective To analyze the impact of age on surgical reaction and postoperative complications of patients with colorectal cancer served by West China Hospital of Sichuan University as a regional center in the Database from Colorectal Cancer (DACCA). Methods The data of DACCA was updated on January 5, 2022. All data items included age, surgical trauma reaction, elevated body temperature time, exhaust time, pain, mental status, and postoperative hospital complications. According to the age segmentation method in China, the patients can be divided into 3 groups: ≤35 years old (including infant, toddler, child, teenager and youth, set as the younger group), 36–59 years old (set as the middle-aged group), and ≥60 years old (set as the elderly group). Results After scanning, 5 224 data rows were analyzed. There was no significant difference in surgical trauma reaction (H=0.352, P=0.838), elevated body temperature time (H=3.999, P=0.135), exhaust time (H=1.940, P=0.379), mental status (H=2.075, P=0.354), incidence of postoperative complications (χ2=2.078, P=0.354), incidence of anastomotic bleeding (χ2=1.737, P=0.420), incidence of anastomotic leakage (χ2=0.573, P=0.751), and incidence of pulmonary infection (P=0.410) among different age groups, but the younger group had more severe pain (H=12.985, P=0.002) and higher incidence of inflammatory obstruction (χ2=7.789, P=0.020). Conclusions Age has little effect on trauma reaction related parameters and overall incidence of complications in colorectal cancer patients. However, younger patients with colorectal cancer showed increased pain levels and increased incidence of inflammatory obstruction after surgery. These clinical manifestations can provide clinicians with evidence for intervention, but more prospective intervention trials are needed.
ObjectiveTo analyze the current version of the West China Database from Colorectal Cancer (DACCA) and explore how the occupational background of colorectal cancer patients affects the complexity of surgical difficulty and postoperative complications. MethodsWhen using the updated version of DACCA data on May 28, 2023 for analysis, the data items concerned covered occupation, operative duration, anatomical difficulty, pelvic stenosis, abdominal obesity, adhesion in surgical area, abnormal mesenteric status, tissue or organ hypertrophy, intestinal quality in surgical area, postoperative complications in hospital, short-term postoperative complications and long-term postoperative complications. According to the “Occupational Classification Code of the People’s Republic of China”, the occupations of patients were divided into professional and technical personnel, staff, service personal, production personnel, manufacturing personnel and retirees according to different occupations. The operative difficulty and postoperative complications of 6 groups were analyzed. ResultsAccording to the screening conditions, 5 734 valid data rows were obtained from DACCA. The results of occupation analysis showed that there were significant difference in operative duration (H=11.609, P=0.041), anatomical difficulty (H=29.166, P<0.001), pelvic stenosis (H=16.412, P=0.006), abdominal obesity (H=44.622, P<0.001), adhesion in surgical area (H=23.695, P<0.001), abnormal mesenteric status (χ2=39.252, P=0.035), tissue or organ hypertrophy (χ2=58.284, P<0.001) and intestinal quality in surgical area (H=21.041, P=0.001) between different groups. There were no significant differences in the occurrence of complications in hospital, near and short-term and long-term after operation among different occupations (P>0.05). Further subgroup analysis showed that only the difference of fever (χ2=10.969, P=0.041) and intestinal obstruction (χ2=12.025, P=0.021) were statistically significant among different occupations. ConclusionThe occupation of patients may affect the difficulty of colon cancer surgery, and the occurrence of postoperative complications is nothing to do with the occupation of patients, but the occurrence of postoperative fever and postoperative intestinal obstruction is related to occupations, and the possible causes need to be further explored.
Objective To establish the Chinese Evidence-Based Medicine/Cochrane Centre Database of Clinical Trials and Diagnostic Tests to provide reliable scientific data for clinical practice, teaching, research and systematic reviewers and submit the results of randomised controlled trials (RCTs) and controlled clinical trials (CCTs) to The Cochrane Collaboration. Methods Data were collected by handsearching and electronic searching based on the criterion of the Collaboration and clinical epidemiology. Results Up to December 2003, there were 16 652 RCTs /CCTs and 3 786 DT included in the database. A total of 4 966 RCTs and CCTs were submitted to the Collaboration. Nineteen specialized databases were set up. Conclusions The first phase of the Chinese Evidence-Based Medicine/Cochrane Centre Database of Clinical Trials and Diagnostic Tests has been completed. The database has provided advice for contributiors both at home and abroad.
ObjectiveTo explore the influencing factors of cancer-specific survival of patients with large hepatocellular carcinoma, and draw a nomogram to predict the cancer-specific survival rate of large hepatocellular carcinoma patients.MethodsThe clinicopathological data of patients with large hepatocellular carcinoma during the period from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) database were searched and randomly divided into training group and validation group at 1∶1. Using the training data, the Cox proportional hazard regression model was used to explore the influencing factors of cancer-specific survival and construct the nomogram; finally, the receiver operating characteristic curve (ROC curve) and the calibration curve were drawn to verify the nomogram internally and externally.ResultsThe results of the multivariate Cox proportional hazard regression model showed that the degree of liver cirrhosis, tumor differentiation, tumor diameter, T stage, M stage, surgery, and chemotherapy were independent influencing factors that affect the specific survival of patients with large hepatocellular carcinoma (P<0.05), and then these factors were enrolled into the nomogram of the prediction model. The areas under the 1, 3, and 5-year curves of the training group were 0.800, 0.827, and 0.814, respectively; the areas under the 1, 3, and 5-year curves of the validation group were 0.800, 0.824, and 0.801, respectively. The C index of the training group was 0.779, and the verification group was 0.777. The calibration curve of the training group and the verification group was close to the ideal curve of the actual situation.ConclusionThe nomogram of the prediction model drawn in this study can be used to predict the specific survival of patients with large hepatocellular carcinoma in the clinic.
As an important auxiliary means of pharmacoeconomics evaluation, budget impact analysis can effectively measure the affordability of medical insurance fund, and plays a significant role in the process of medical insurance access negotiation, adjustment of medical insurance reimbursement directory and establishment of payment price. The quality of budget impact analysis data has a great impact on the analysis results and the scientific decision-making. When the existing data cannot meet the requirements of the paper, relevant software is needed to carry out Delphi method to ensure the data accuracy. Infopoll is a powerful, easy-to-use application that designs consultation questionnaires by providing multiple question choices and multiple forms of answer settings, as well as detailed statistical charts for results analysis. This paper introduces how to obtain the data of budget impact analysis based on Delphi method using Infopoll software, and analyzes the main results in detail.