Information management of full-cycle inpatient bed reservation for cancer patients under the normalised prevention and control of the COVID-19 pandemic.

BACKGROUND: During the prolonged COVID-19 pandemic, hospitals became focal points for normalised prevention and control. In this study, we investigated the feasibility of an inpatient bed reservation system for cancer patients that was developed in the department?s public WeChat account. We also explored its role in improving operational efficiency and nursing quality management, as well as in optimising nursing workforce deployment. METHODS: We utilised WeChat to facilitate communication between cancer patients and health care professionals. Furthermore, we collected data on admissions, discharges, average number of hospitalisation days, bed utilisation rate, and the number of bed days occupied by hospitalised patients through the hospital information system and nurses? working hours and competency levels through the nurse scheduling system. The average nursing hours per patient per day were calculated. Through the inpatient bed reservation system, the number of accepted admissions, denied admissions, and cancelled admissions from the reservation system were collected. The impact of the bed reservation system on the department?s operational efficiency was analysed by comparing the number of hospitalisation discharges before and after reservations, as well as the average hospitalisation and bed utilisation rates. By comparing nurses? working hours per month and average nursing hours per patient per day, the system?s impact on nurses? working hours and nursing quality indicators was analysed. RESULTS: The average hospitalisation length, bed utilisation rate, and nurses? working hours were significantly lower, and the average number of nursing hours per patient per day was significantly higher after the implementation of the reservation system. The full-cycle bed information management model for cancer patients did not affect the number of discharged patients. CONCLUSION: Patients? ability to reserve bed types from home in advance using the department?s official WeChat-based inpatient bed reservation system allowed nurses to prepare for their work ahead of time. This in turn improved the operational efficiency of the department and nursing quality, and it optimised the deployment of the nursing workforce.

Improved performance of the SH test as an in vitro skin sensitization test with a new predictive model and decision tree.

Demands for the elimination and replacement of animal experiments for cosmetic safety assessment have increased in recent years. Evaluation of skin sensitization, however, is a critical issue in cosmetic safety assessment. The SH test is an in vitro skin sensitization test method that evaluates protein binding of chemical substances, which is an important event in skin sensitization. We previously verified the technical transferability and between-laboratory reproducibility of the SH test, a domestic test method for which no scientific research has been conducted, and improved the protocol, but also noted some unresolved issues. Therefore, in the present study, we successfully improved the operational efficiency and clarity of the final judgment of the SH test by (i) developing a new decision-making system that can make a final judgment without statistical processing, (ii) changing the statistical method, and (iii) evaluating and determining the maximum number of repetitions necessary for optimal efficiency. The improved SH test was verified by comparing it with existing test methods already adopted by the Organization for Economic Cooperation and Development. The results of this study demonstrated excellent performance of the improved SH test, with high reproducibility, reliable predictability, and good operational efficiency. The predictive performance of the improved method does not differ significantly from that of the conventional method, although it is clearer and more efficient. Therefore, the results of the present improved method are consistent with those obtained using the conventional method, with higher efficiency.

Effects of the Multidisciplinary Preoperative Clinic on the Incidence of Elective Surgery Cancellation.

To evaluate effects of the multidisciplinary preoperative clinic (POC) consisting of anesthesiologists, dentists, pharmacists, and nurses on elective surgery cancellation, we retrospectively investigated patients who underwent elective non-cardiac, non-obstetric surgeries between October, 2018 and March, 2019 (before the POC establishment: Group 1) and between October, 2019 and March, 2020 (after the POC establishment: Group 2). Among reasons for surgery cancellation allocated into eight categories, three reasons for cancellation (related to consent authorization, medication, and significant comorbidities) were considered preventable. We compared incidences of overall and preventable cancellations of surgeries between 4,198 patients in Group 1 and 4,664 patients in Group 2, who had significantly different clinical backgrounds, including the ASA-PS class. There was no significant difference in the incidence of overall cancellation between Group 1 and Group 2 (4.1% vs. 4.1%, p = 0.96). However, the incidence of preventable cancellation was significantly lower in Group 2 than in Group 1 (0.4% vs. 0.7%, p = 0.045). In addition, the incidence of overall cancellation was significantly lower in 3,741 Group 2 patients visiting the POC than in 5,121 patients not visiting the POC in both Groups (3.2% vs. 4.7%, p < 0.001). Further, in 3,423 pairs of patients with comparable clinical backgrounds created from both Groups using propensity score matching, incidences of overall cancellation (2.2% vs. 3.1%) and preventable cancellation (0.1% vs. 0.6%) were significantly lower in Group 2 than in Group 1 (p = 0.036 and 0.008, respectively). In conclusion, the multidisciplinary POC was effective in reducing elective surgery cancellation.

Characterization of the flow of patients in a hospital from complex networks.

We study the efficiency of operations management in a hospital from the dynamics of the flow of patients. Our principal aim is to characterize strategic departments and seasonal patterns in a hospital from a complex networks approach. Process mining techniques are developed to track out-patients' pathways along different departments for the purpose of building weekly networks. In these networks, departments act as nodes with multiple out/in-going arrows connecting other departments. Strategic departments are classified into target and critical departments. On the one hand, target departments, which in this study belong to the oncology area, correspond to those affected by new management policies whose impact is to be assessed. On the other hand, critical departments correspond to the most active departments, the hubs of the networks. Using suitable networks parameters, strategic departments are shown to be highly efficient regardless of the season, which naturally translates into a high level of service offered to patients. In addition, our results show conformance with the new objectives concerning target departments. The methodology presented is shown to be successful in evaluating the efficiency of hospital services in order to enhance process performances, and moreover, it is suitable to be implemented in healthcare management systems at a greater scale and the service industry whenever the flow of clients or customers are involved.

Operational resilience, disruption, and efficiency: Conceptual and empirical analyses.

This research develops the notion of operational resilience and investigates its relationship with operational efficiency under differing conditions of operational disruption. Operational resilience is conceptualized as a multi-dimensional construct, consisting of two theoretically distinct components (i.e., disruption absorption and recoverability), which are argued to have unique effects on operational efficiency under varying operational disruption conditions. The study's hypotheses are empirically tested on primary data from a sample of 259 firms in a sub-Saharan African economy. Using structural equation modeling as an analytical tool, the study finds that both disruption absorption and recoverability have positive effects on operational efficiency. Additionally, the study finds that while the effect of disruption absorption on operational efficiency is stronger under conditions of high operational disruption, the effect of recoverability on operational efficiency is stronger under conditions of low operational disruption. A major implication of these findings is that the nature of operational resilience and the disruption circumstances under which it is deployed shape its efficiency value, thus advancing knowledge on the nuances associated with how and when operational resilience influences operational efficiency.

What explains the operational efficiency of listed commercial banks in China? Evidence from a three-stage DEA-tobit modeling analysis.

Based on the actual situation of listed commercial banks in China, this study utilizes a three-stage DEA model to eliminate external macro-environmental factors and random error factors. As a result, the study objectively measures the true efficiency values of 42 listed commercial banks in China from 2015 to 2021. On this basis, a Tobit model is constructed to analyze the micro-level factors influencing the operational efficiency of listed commercial banks in China. Empirical research shows that the operational efficiency values in the first stage are significantly lower than those in the third stage. Analyzing the proportion of banks with an efficiency value of 1, it is found that state-owned banks and joint-stock banks account for a large proportion. The proportion of city commercial banks decreases significantly, while agricultural banks and commercial banks have the lowest proportion. In addition, the Tobit regression results show that bank size, innovation level, profitability, and development capacity have a significant positive impact on the operational efficiency of listed commercial banks in China at the current stage. Based on the above empirical results and analysis, specific measures are proposed to improve the operational efficiency of listed commercial banks in China. Based on the above empirical results and analysis, the study finally suggests the following specific measures to enhance the operational efficiency of listed commercial banks in China: 1. Strengthening technological investment to achieve diversified operations and cultivate new niche markets; 2. Emphasizing intermediate business income to enhance market competitiveness; 3. Undertaking digital transformation and upgrading to improve sustainable profitability.

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces.

Museums are critical in safeguarding cultural heritage and cultivating community educational opportunities. This research aims to evaluate operational efficiency (OE), the impact of technological change on total factor productivity change (TFPC), and the regional heterogeneity of museum performance in three regions and 31 provinces across China. To this end, the study employed DEA-SBM and the Malmquist Productivity Index to gauge OE, TFPC, and determinants of TFPC (efficiency change or emerging technologies change) across 31 provinces for 2012-2021. Results reveal that the average OE of the Chinese Museum is 0.8394. It shows a 16.06 % growth potential in the operational efficiency of Chinese Museums. Further, the OE of Chinese Museums declined over the study period from 0.8965 in 2012 to 0.8088 in 2021. Beijing, Fujian, and Hunan are ranked top with a Museum's OE Score of 1. The average MI score of Chinese Museums is 0.9744, and technology change is the main determinant of Decline in productivity change as EC = 0.9992 is greater than TC = 0.9846. The MI of Liaoning, Shanghai, Ningxia, Jiangxi, Chongqing, Sichuan, Guangdong, and Tianjin is over 1, indicating growth in total factor productivity over the study period. The eastern region of China shows higher operational efficiency and total factor productivity scores of museums than the central and western regions. The results of the Kruskal-Wallis test proved that a statistically significant difference exists among different regions of China for the OE, MI, EC, and TC of museums.

Impact of a systematic framework for anticipatory compounding on medication waste reduction in a mid-size community hospital.

PURPOSE: In current hospital pharmacy practice, the need to compound medications ahead of patient orders often results in an increase in medication waste. The purpose of this study was to implement a strategic approach for anticipatory sterile compounding and evaluate its effect on the reduction of expired medication waste. METHODS: This was a pre-/post-intervention quasi-experimental study with 3 weeks of data collection for both arms and a 1-week washout period to implement process changes. A par log was placed on the medication storage refrigerator used for anticipatory compounding, with minimum and maximum levels determined by the demand-forecasting model. The primary outcome was the percentage of observations associated with waste. The secondary outcomes were the overall percentage of sterile compounding spending attributable to waste, median wasted dollars per sterile compounded product, and median dollars spent per sterile product compounded as anticipatory stock. Descriptive statistics were calculated using Minitab version 20, with the α level set to 0.05. RESULTS: A total of 4,619 observations were included in the analysis: 2,433 in the preintervention group and 2,186 in the postintervention group. Despite the median price being higher in the postintervention group than in the preintervention group, both the primary and secondary outcomes indicated that waste was reduced following the intervention. CONCLUSION: Overall, implementation of the framework reduced sterile products waste at our institution. More research is needed to evaluate the effects of this framework at institutions of different sizes and with different patient populations. Further research on probabilistic models for sterile compounded products is also needed.

A Case of Headache Treated by Online Telemedicine in Collaboration With a Midwifery Home.

Midwifery centers are places where midwives not only provide antenatal checkups and delivery care but also offer a wide range of health guidance to pregnant women, postpartum mothers, newborns, and older women. In recent years, midwives have also provided onsite and online health guidance. However, diagnosis and prescribing medication are impossible in midwifery centers because no doctor is present. If the midwife determines that the patient should consult doctors, the patient may have to go to a hospital and see doctors in person, which can be burdensome. Online telemedicine facilitates midwife-doctor collaboration and may solve this problem. We report a case of headache management by telemedicine that minimized the patient's travel burden by collaborating with a midwifery center that provides onsite, visiting, and online health guidance for patients who have difficulty visiting a hospital due to postpartum period, childcare, and breastfeeding. A 29-year-old woman and her husband were raising an infant in Sado City (a remote island across the sea), Niigata Prefecture. She developed acute back pain and was bedridden for several days due to immobility. She consulted a midwife because of stress and anxiety caused by childcare and acute back pain, as well as newly occurring headaches. The midwife visited her and provided on-site health guidance. The midwife decided that a doctor's diagnosis and treatment with painkillers were desirable for the headache and back pain, so she contacted a doctor based on the patient's request. The doctor provided online telemedicine across the sea, diagnosed her headache as a tension-type headache, and prescribed acetaminophen 500 mg as an abortive prescription. The prescription was faxed to a pharmacy on the island, and the original was sent by post. The midwife picked up the medication and delivered it to the patient. After taking the medication, the patient's back pain and headache went into remission. Collaboration between midwifery centers that provide onsite, visiting, and online health guidance and medical institutions that offer online telemedicine can potentially improve accessibility to medical care. It differs from conventional online telemedicine in the midwife's coordination practice by monitoring the patient's condition and requesting the physician based on the patient's request.

Predictors of same day cancellation of elective surgery.

Same day cancellations of surgery have adverse effects on both patients and health care systems. To date, the majority of research has evaluated reasons for same day cancellation, and relatively little is known about risk factors for cancellation. The aim of this study is to develop and evaluate the accuracy of a model for preoperatively predicting which patients are at risk for experiencing same day cancellation. While accurately predicting which patients are likely to experience same day cancellation remains challenging, predictive models may aid in the early identification of patients at risk for cancellation. Future studies are required to assess whether the use of predictive analytics leads to reduced cancellation rates in practice.

Conducting Action Research to Improve Operational Efficiency in Manufacturing: The Case of a First-Tier Automotive Supplier.

Optimising available resources and minimising production costs and throughput time is vital for first-tier suppliers in the worldwide automotive sector. To develop this type of optimisation and efficiency, MAHLE applied Action Research (AR) in one of its factories located in Spain. A multidisciplinary collaborative work team was created with the aim of deploying the AR initiative in combination with Lean Manufacturing and Six Sigma tools. Four improvement and learning cycles were deployed and key performance metrics were defined to collect and measure data in order to analyse the improvements achieved. The application of the AR initiative in the production line of a power filter device enabled improvements in both production times and quality indicators in the manufacturing process. The most outstanding results were the improvements made in the decrease in initial throughput time (34.78%) and in average daily rejections (73.53%). In addition, the AR initiative generated practical and theoretical contributions for business and academia, allowing the AR initiative to be applied in other areas of the company, and contributing to the current state of the art in the industrial application of this methodology.

Impact of the coronavirus disease 2019 (COVID-19) pandemic on the operational efficiency of emergency medical services and its association with out-of-hospital cardiac arrest survival rates: A population-based cohort study in Kobe, Japan.

Aim: To identify whether the coronavirus disease 2019 (COVID-19) pandemic affects the operational efficiency of emergency medical services (EMS) and the survival rate of out-of-hospital cardiac arrest (OHCA) in prehospital settings. Methods: We conducted a population-based cohort study in Kobe, Japan, between March 1, 2020, and September 31, 2022. In study 1, the operational efficiency of EMS, such as the total out-of-service time for ambulances, the daily occupancy rate of EMS, and response time, was compared between the pandemic and nonpandemic periods. In study 2, the impacts of the changes in EMS operational efficiency were investigated among patients with OHCA, with 1-month survival as the primary outcome and return of spontaneous circulation, 24-h survival, 1-week survival, and favorable neurological outcomes as the secondary outcomes. Logistic regression analysis was conducted to identify the factors associated with survival among patients with OHCA. Results: The total out-of-service time, occupancy rate, and response time significantly increased during the pandemic period (p < 0.001). The response time during the pandemic period increased significantly per pandemic wave. Regarding OHCA outcomes, 1-month survival rates during the pandemic period significantly decreased compared with those during the nonpandemic period (pandemic 3.7% vs. nonpandemic 5.7%; p < 0.01). Similarly, 24-h survival (9.9% vs. 12.8%), and favorable neurological outcomes significantly decreased during the pandemic period. In the logistic regression analysis, response time was associated with lower OHCA survival in all outcomes (p < 0.05). Conclusion: The COVID-19 pandemic has been associated with reduced operational efficiency of EMS and decreased OHCA survival rates. Further research is required to improve the efficiency of EMS and OHCA survival rates.

Effective risk management in the shadow of COVID-19 pandemic: The evidence of Indonesian listed corporations.

The study uses COVID-19 to identify the treatment group as the difference in change of non-financial corporations (NFCs) risk management ratios over time to investigate the causal effect of the NFCs' effective risk management (ERM) practices on operational efficiency (OE). ERM was measured by solvency and liquidity ratios, while the risk management theory was developed to refine the scope of the study. The data were collected from the central bank of Indonesia to map the empirical analysis, and the difference in difference (DID) technique was used to illustrate how NFCs react to mitigate the negative impact of COVID-19 and generate OE. Specifically, a quasi-natural experiment was used to size the effect of ERM practices on corporate OE during the COVID-19 pandemic. The descriptive analysis revealed that the COVID-19 pandemic effect has been unequal across different industrial sectors. Moreover, the empirical findings showed that corporate risk management during COVID-19 is the source of structural change, which affects its existence and operational efficiency. While debt amount and age may affect corporate credit score, ERM practices led the indebted corporation to the flexibility of debt refinancing or/and restructuring, which offers them the ability to prevent bankruptcy and adapt to the changes while operating efficiently. The finding revealed evidence of the important role of long-term debt in offering protection to NFCs during the credit supply shock brought in by the COVID-19 pandemic. Furthermore, the findings show that long-term debt is negatively associated with corporate OE. This was expected given that corporations use long-term debt financing for long-term investment, while short-term debt funds the working capital. Thus, to assess the effect of debts on corporate OE, managers should consider their maturity structure, among other factors.

Research on the Operational Efficiency of Basic Medical Insurance for Urban Employees in China-Based on Three-Stage DEA Model.

Purpose: To conduct a three-stage data envelopment analysis (DEA) of the operational efficiency of urban employee basic medical insurance (UEBMI) across 31 provinces in China from 2012 to 2021. Methods: Utilized a three-stage DEA model, this study measured and evaluated the operational efficiency of urban employee basic medical insurance within China's 31 provinces. Results: The operational efficiency of urban employee basic medical insurance in China was notably low, displaying significant disparities across different regions and periods. Substantial room for improvement exists. Environmental factors, including urbanization level and unemployment rate, wielded a pronounced influence on the operational efficiency of China's employee medical insurance. Conversely, the fiscal revenue and expenditure ratio hindered the enhancement of employee medical insurance efficiency. Conclusion: This study held valuable insights for enhancing the operational efficiency of China's urban employee basic medical insurance. To effectively improve insurance efficiency, the following recommendations are put forth: firstly, relevant departments should escalate resource investments and optimize resource utilization based on rational allocation; secondly, enhance legislation and regulations, fortify fund oversight, and ensure equitable and judicious utilization of the medical insurance fund; finally, leveraging modern high-tech advancements can comprehensively elevate the operational efficiency of the employee medical insurance fund. Ultimately, with the advent of cutting-edge technology, the operational efficiency of employee medical insurance fund can be comprehensively elevated.

Enhancing Kidney Transplant Care through the Integration of Chatbot.

Kidney transplantation is a critical treatment option for end-stage kidney disease patients, offering improved quality of life and increased survival rates. However, the complexities of kidney transplant care necessitate continuous advancements in decision making, patient communication, and operational efficiency. This article explores the potential integration of a sophisticated chatbot, an AI-powered conversational agent, to enhance kidney transplant practice and potentially improve patient outcomes. Chatbots and generative AI have shown promising applications in various domains, including healthcare, by simulating human-like interactions and generating contextually appropriate responses. Noteworthy AI models like ChatGPT by OpenAI, BingChat by Microsoft, and Bard AI by Google exhibit significant potential in supporting evidence-based research and healthcare decision making. The integration of chatbots in kidney transplant care may offer transformative possibilities. As a clinical decision support tool, it could provide healthcare professionals with real-time access to medical literature and guidelines, potentially enabling informed decision making and improved knowledge dissemination. Additionally, the chatbot has the potential to facilitate patient education by offering personalized and understandable information, addressing queries, and providing guidance on post-transplant care. Furthermore, under clinician or transplant pharmacist supervision, it has the potential to support post-transplant care and medication management by analyzing patient data, which may lead to tailored recommendations on dosages, monitoring schedules, and potential drug interactions. However, to fully ascertain its effectiveness and safety in these roles, further studies and validation are required. Its integration with existing clinical decision support systems may enhance risk stratification and treatment planning, contributing to more informed and efficient decision making in kidney transplant care. Given the importance of ethical considerations and bias mitigation in AI integration, future studies may evaluate long-term patient outcomes, cost-effectiveness, user experience, and the generalizability of chatbot recommendations. By addressing these factors and potentially leveraging AI capabilities, the integration of chatbots in kidney transplant care holds promise for potentially improving patient outcomes, enhancing decision making, and fostering the equitable and responsible use of AI in healthcare.

Relationship between Racial Diversity in Medical Staff and Hospital Operational Efficiency: An Empirical Study of 3870 U.S. Hospitals.

Demand for foreign nurses and medical staff is rapidly increasing due to the severe labor shortage in U.S. hospitals triggered by the COVID-19 pandemic. However, empirical studies on the effect of the racial diversity of medical staff on hospital operations are still lacking. This research gap is thus investigated based on the foreign medical staff working in 3870 U.S. hospitals. Results show that workforce racial diversity has a significantly positive relationship with hospital operational efficiency regarding occupancy rate, manpower productivity, capacity productivity, and case mix index. Notably, this study empirically supports that increasing the ratio of foreign nurses positively affects the overall operational efficiency of hospitals. In addition, the study results also indicate that the hospital location, size, ownership, and teaching status act as significant control variables for the relationship between racial diversity and hospital efficiency. These results imply that hospitals with these specific operating conditions need to pay more attention to racial diversity in the workplace, as they are structurally more sensitive to the relationship between racial diversity and operational efficiency. In short, the findings of this study suggest that hospital efficiency can be operationally improved by implementing workforce ethnic diversity. For this reason, hospital stakeholders and healthcare policymakers are expected to benefit from this study's findings. Above all, the results of this study imply that if an organization adapts to extreme external environmental changes (e.g., the COVID-19 pandemic) through appropriate organizational restructuring (i.e., expanding the workforce racial diversity by hiring foreign medical staff), the organization can gain a competitive advantage, a claim that is supported by contingency theory. Further, investors are increasingly interested in ESG, especially companies that embody ethical and socially conscious workplaces, including a diverse and inclusive workforce. Thereby, seeking racial diversity in the workforce is now seen as a fundamental benchmark for organizational behavior that predicts successful ESG business practices, a claim that is supported by stakeholder theory. Therefore, in conclusion, the findings of this study suggest that workforce racial diversity is no longer an optional consideration but should be considered as one of the essential determinants of competitive advantage in organizations, particularly in the healthcare sector.

Machine Learning Prediction of Clinical Trial Operational Efficiency.

Clinical trials are the gatekeepers and bottlenecks of progress in medicine. In recent years, they have become increasingly complex and expensive, driven by a growing number of stakeholders requiring more endpoints, more diverse patient populations, and a stringent regulatory environment. Trial designers have historically relied on investigator expertise and legacy norms established within sponsor companies to improve operational efficiency while achieving study goals. As such, data-driven forecasts of operational metrics can be a useful resource for trial design and planning. We develop a machine learning model to predict clinical trial operational efficiency using a novel dataset from Roche containing over 2,000 clinical trials across 20 years and multiple disease areas. The data includes important operational metrics related to patient recruitment and trial duration, as well as a variety of trial features such as the number of procedures, eligibility criteria, and endpoints. Our results demonstrate that operational efficiency can be predicted robustly using trial features, which can provide useful insights to trial designers on the potential impact of their decisions on patient recruitment success and trial duration.

Application of lean Six Sigma methodology using DMAIC approach for the improvement of bogie assembly process in the railcar industry.

The quest for waste reduction, quality improvement and operational efficiency during the assembly process of the railcar bogie necessitates this study. Using a case study approach, this study employs the Lean Six Sigma (LSS) approach for process improvement of the railcar bogie assembly process. Primary data relating to the assembly process such as the labour and material flow, up and down times were collected at every stage of the assembly operation. The improvement process of the assembly process featured the use of some Lean tools such as the Kaizen, Value Stream Mapping, Pareto chart, Single-Minute Exchange of Die (SMED) and 5S. The investigation of the current assembly process with the use of the LSS technique indicates that the process efficiency is low due to waste generation. The results obtained showed significant improvement in the process cycle efficiency (PCE) by 46.8%, via the implementation of the Kaizen continuous process improvement approach, 27.9% reduction in the lead-time, 59.3% increase in the value added time and 71.9% reduction in the non-value added time after the implementation of the LSS approach. The findings of this work demonstrated the feasibility of the LSS approach for waste minimisation and process performance improvement in a bid to achieve operational excellence in a manufacturing organisation.

Can Public-Private Partnership Wastewater Treatment Projects Help Reduce Urban Sewage Disposal? Empirical Evidence from 267 Cities in China.

Human activities have placed enormous pressure on the world's water resources. To improve the efficiency of water supply and wastewater treatment, public-private partnerships (PPPs) are widely used for sewage treatment. However, an academic question remains about whether PPP sewage treatment projects (PPPSTs) help reduce urban sewage disposal when responsibilities shift from the public sector to the private sector. This study used panel data of 267 prefecture-level cities in China from 2009 to 2020 to construct a difference-in-difference (DID) model based on the counterfactual framework to answer this question empirically. The model results significantly support the effect of PPPSTs on sewage disposal reduction. Furthermore, these results passed the parallel trend test and the placebo test, and the results were still achieved when the quadratic term of the core variable was introduced, indicating that the model is reliable. In addition, the moderating effect models were used to expand the analysis. That is, the regressions were derived by multiplying the relevant extended variables and the core independent variables. This analysis indicates that the operation mode of PPPST and the characteristics of national demonstration play an essential role in reducing the amount of urban sewage disposal. However, the effect of fiscal decentralization is not apparent. These conclusions were also confirmed in the model using the investment scale of PPPSTs. Therefore, paying attention to the formation of PPPST contracts and adopting a practical supervision system is of great significance for improving the effect of sewage disposal reduction.