The implementation of green supply chain management (GSCM) and environmental management system (EMS) practices and its impact on market competitiveness during COVID-19.

Despite great academic interest in global green supply chain management (GSCM) practices, its effectiveness for environmental management systems (EMS) and market competitiveness during COVID-19 remains untapped. Existing literature suggests that a fundamental link between GSCM, EMS, and market competitiveness is missing, as supply management is critical to maintain market competitiveness. To fill this gap in the literature, this study examines whether environmental management systems influence the link between GSCM practice and market competitiveness in China. We also propose the articulating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility toward these associations in the context of the COVID-19 pandemic. We evaluated the proposed model using regression-based structural equation modeling (SEM) with primary data (n = 330). This result provides empirical evidence of the impact of GSCM on EMS and market competitiveness. Moreover, the results show that the BDA-AI and the environmental visibility enhanced the positive relationship between GSCM-EMS and EMS and market competitiveness in China. Recent research shows that supply chain professionals, policymakers, managers, and researchers are turning to formal EMS, BDA-AI, and environmental visibility to help their organizations achieve the competitiveness that the market indicates they need.

COVID-19 and clinic workflow optimization using lean six sigma.

OBJECTIVES: The COVID-19 pandemic has fundamentally changed the workflow of clinics. We applied Lean Six Sigma processes to optimize clinic workflow to reduce patient wait times and improve the patient experience. STUDY DESIGN: Prospective cohort study. METHODS: We implemented (1) pushing most extended wait times to the end of the workflow by rooming the patient directly and (2) using distractions during the waiting process by using educational videos and a timer for physician arrival in the patient exam room. We compared the patient wait times and subcomponents of Press Ganey scores as a surrogate for changes in patient experience and satisfaction from the preimplementation period (n = 277) to the 3-month (September 1, 2020, to November 30, 2020) postimplementation period (n = 218). RESULTS: There was a significant reduction in overall throughput time (38 vs 35 minutes) and wait before rooming (11 vs 8 minutes), and increased physician time with patients (15 vs 17 minutes) (P < .0001 for all). These results corresponded with a significant improvement in Press Ganey subcomponents of (1) waiting time in the exam room before being seen by the care provider, (2) degree to which you were informed about any delays, (3) wait time at clinic (from arriving to leaving), and (4) length of wait before going to an exam room (P < .001 for all). CONCLUSIONS: Simple, inexpensive measures can improve patient engagement and provide a safe setting for patients for clinic visits in the wake of COVID-19. In the future, clinics' common wait areas could be reappropriated to increase the number of clinic exam rooms.

Managing inpatient bed setup: an action-research approach using lean technical practices and lean social practices.

PURPOSE: This article aims to introduce a guide to improving hospital bed setup by combining lean technical practices (LTPs), such as kaizen and value stream mapping (VSM) and lean social practices (LSPs), such as employee empowerment. DESIGN/METHODOLOGY/APPROACH: Action research approach was employed to analyze the process of reconfiguration of bed setup management in a Brazilian public hospital. FINDINGS: The study introduces three contributions: (1) presents the use of VSM focused specifically on bed setup, while the current literature presents studies mainly focused on patient flow management, (2) combines the use of LSPs and LTPs in the context of bed management, expanding current studies that are focused either on mathematical models or on social and human aspects of work, (3) introduces a practical guide based on six steps that combine LSPs and LSPs to improve bed setup management. RESEARCH LIMITATIONS/IMPLICATIONS: The research focused on the analysis of patient beds. Surgical beds, delivery, emergency care and intensive care unit (ICU) were not considered in this study. In addition, the process indicators analyzed after the implementation of the improvements did not contemplate the moment of the COVID-19 pandemic. Finally, this research focused on the implementation of the improvement in the context of only one Brazilian public hospital. PRACTICAL IMPLICATIONS: The combined use of LSPs and LTPs can generate considerable gains in bed setup efficiency and consequently increase the capacity of a hospital to admit new patients, without the ampliation of the physical space and workforce. SOCIAL IMPLICATIONS: The improvement of bed setup has an important social character, whereas it can generate important social benefits such as the improvement of the admission service to patients, reducing the waiting time, reducing hospitalization costs and improving the hospital capacity without additional physical resources. All these results are crucial for populations, their countries and regions. ORIGINALITY/VALUE: While the current literature on bed management is more focused on formal models or pure human and social perspectives, this article brings these two perspectives together in a single, holistic framework. As a result, this article points out that the complex bed management problem can be efficiently solved by combining LSPs and LTPs to present theoretical and practical contributions to the important social problem of hospital bed management.

Analyzing the efficiency of Chinese primary healthcare institutions using the Malmquist-DEA approach: Evidence from urban and rural areas.

Background: China has been increasing the investment in Primary Health Care Institutions (PHCIs) since the launch of the New Health Care System Reform in 2009. It is a crucial concern whether the PHCIs can meet residents' need both in urban and rural with the limited government finance, especially encountering the challenge of the COVID-19. This study aimed to reveal the trend of the primary health service efficiency in the past decade, compare the urban-rural differences, and explore relevant factors. Methods: DEA and Malmquist models were applied to calculate the health service efficiency of PHCIs among 28 provinces in China, with the input variables including the number of institutions, number of beds, number of health technicians, and the outputs variables including the number of outpatients and emergency visits, number of discharged patients. And the Tobit model was used to analyze the factors on the efficiency in urban and rural. A sensitivity analysis for model validations was also carried out. Results: The average technical efficiency (TE) of urban PHCIs fluctuated from 63.3% to 67.1%, which was lower than that in rural (75.8-82.2%) from 2009 to 2019. In terms of dynamic efficiency, the urban PHCIs performed better than the rural, and the trends in the total factor productivity change were associated with favorable technology advancement. The population density and dependency ratio were the key factors on TE in both of the urban and rural PHCIs, and these two factors were positively correlated to TE. In terms of TE, it was negatively correlated with the proportion of total health expenditure as a percentage of GDP in urban PHCIs, while in rural it was positively correlated with the urbanization rate and negatively correlated with GDP per capita. Besides, the tests of Mann-Whitney U, and Kruskal-Wallis H indicated the internal validity and robustness of the chosen DEA and Malmquist models. Conclusions: It needs to reduce the health resource wastes and increase service provision in urban PHCIs. Meanwhile, it is necessary to strengthen medical technology and gaining greater efficiency in rural PHCIs by technology renovation.

Technical Efficiency Evaluation of Primary Health Care Institutions in Shenzhen, China, and Its Policy Implications under the COVID-19 Pandemic.

(1) Background: Primary health care institutions (PHCI) play an important role in reducing health inequities and achieving universal health coverage. However, despite the increasing inputs of healthcare resources in China, the proportion of patient visits in PHCI keeps declining. In 2020, the advent of the COVID-19 pandemic further exerted a severe stress on the operation of PHCI due to administrative orders. This study aims to evaluate the efficiency change in PHCI and provide policy recommendations for the transformation of PHCI in the post-pandemic era. (2) Methods: Data envelope analysis (DEA) and the Malmquist index model were applied to estimate the technical efficiency of PHCI in Shenzhen, China, from 2016 to 2020. The Tobit regression model was then used to analyze the influencing factors of efficiency of PHCI. (3) Results: The results of our analysis reflect considerable low levels of technical efficiency, pure technical efficiency, and scale efficiency of PHCI in Shenzhen, China, in 2017 and 2020. Compared to years before the epidemic, the productivity of PHCI decreased by 24.6% in 2020, which reached the nadir, during the COVID-19 pandemic along with the considerable reduction of technological efficiency, despite the significant inputs of health personnel and volume of health services. The growth of technical efficiency of PHCI is significantly affected by the revenue from operation, percentage of doctors and nurses in health technicians, ratio of doctors and nurses, service population, proportion of children in the service population, and numbers of PHCI within one kilometer. (4) Conclusion: The technical efficiency significantly declines along with the COVID-19 outbreak in Shenzhen, China, with the deterioration of underlying technical efficiency change and technological efficiency change, regardless of the immense inputs of health resources. Transformation of PHCI such as adopting tele-health technologies to maximize primary care delivery is needed to optimize utilization of health resource inputs. This study brings insights to improve the performances of PHCI in China in response to the current epidemiologic transition and future epidemic outbreaks more effectively, and to promote the national strategy of Healthy China 2030.

Implementation of Lean Management Tools Using an Example of Analysis of Prolonged Stays of Patients in a Multi-Specialist Hospital in Poland.

Healthcare institutions in Poland constantly encounter challenges related both to the quality of provided services and to the pressures associated with treatment effectiveness and economic efficiency. The implemented solutions have a goal of improving the service quality of lowering the continuously increasing operational costs. The aim of this paper is to present the application of Lean Management (LM) tools in a Polish hospital, which allowed for the identification of prolonged stays as one of the main issues affecting the service costs and the deteriorating financial results of the hospital. The study was conducted in the neurology department and involved an analysis of data for the whole of 2019 and the first half of 2022. In addition, surveys were conducted among the medical staff to help identify the main causes of prolonged stays. Methods of data analysis and feasible solutions were developed in order to improve the economic efficiency of the unit. The analysis shows that the application of LM tools may contribute to improvement in the functioning of hospitals and that further studies should focus on the development of the method to evaluate efficiency of the implemented solutions intended at shortening the hospital stays of the patients.

Turnover Time Between Elective Operative Cases: Does the Witching Hour Exist for the Operating Room?

BACKGROUND: Efficient resource management in the operating room (OR) contributes significantly to healthcare expenditure and revenue generation for health systems. We aim to assess the influence that surgeon, anesthesiology, and nursing team assignments and time of day have on turnover time (TOT) in the OR. METHODS: We performed a retrospective review of elective cases at a single academic hospital that were completed between Monday and Friday between the hours of 0700 and 2359 from July 1, 2017, through March 31, 2018. Emergent cases and unplanned, add-on cases were excluded. Data regarding patient characteristics, OR teams, TOT, and procedure start and end times were collected and analyzed. RESULTS: A total of 2174 total cases across 13 different specialties were included in our study. A multivariate regression of relevant variables affecting TOT was performed. Consecutive specialty (p < 0.0001), consecutive surgeon (p < 0.0001), anesthesiologist (p < 0.0001), and prior case ending before 1400 (p < 0.0001) were independent predictors of lower TOT. A receiver operating characteristic analysis demonstrated an area under the curve of 0.848 and a cutoff of 1400 having the highest sensitivity and specificity for TOT difference. CONCLUSIONS: TOT can be significantly affected by the time of the day the procedure is performed. Staffing availability during late procedures and the differences in how OR team staff are scheduled may affect OR efficiency. Additional studies may be needed to determine the long-term implications of changes implemented to decrease organizational operational costs related to the OR.

Assessing the Efficiency and Productivity of the Hospital Clinics on the Island of Rhodes during the COVID-19 Pandemic.

(1) Background: The aim was to measure the efficiency and productivity of 15 specialty clinics during the COVID-19 pandemic period 2020-2021 in the General Hospital of Rhodes. (2) Methods: An input-oriented data envelopment analysis and the Malmquist productivity index are used. Labor and capital were used as inputs, and in-patient discharges and days were used as outputs. (3) Results: Five out of the seven clinics in the pathology sector appeared fully efficient with an optimal productivity, and the rest showed progress in 2021. In 2020 the COVID-19 pathology clinic appeared to be inefficient and less productive, while in 2021, it showed a positive performance change. The surgical sector showed very high efficiency rates or even reached an optimal efficiency in both years. The productivity measurement, in most of the surgical clinics, was satisfactory to very high. In 2020 the COVID-19 surgical clinic appeared to be more efficient and productive than in 2021 when its performance declined. (4) Conclusions: The hospital responded to the pressure during the pandemic, by increasing its efficiency and productivity from 2020 to 2021. This was due to the accomplishment of the appropriate organizational changes in the infrastructure, human resources, and technology. The efficiency and productivity assessments should be incorporated in the hospitals' decision making.

Surgical productivity did not suffer despite the states of emergency against the COVID-19 pandemic in Japan: a retrospective observational study.

BACKGROUND: The purpose of this study is to compute surgical total factor productivity with Malmquist index, and to evaluate the effects of states of emergency against the novel coronavirus disease 2019 (COVID-19) pandemic on its productivity change. We hypothesized that the states of emergency significantly reduced surgical total factor productivity in Japan. METHODS: The authors collected data from all the surgical procedures performed in Teikyo University Hospital from April 1 through September 30 in 2019-21. Non-radial and non-oriented Malmquist model under the variable returns-to-scale assumptions was employed. The decision making unit (DMU) was defined as a surgical specialty department. Inputs were defined as (1) the number of medical doctors who assisted surgery, and (2) the duration of surgical operation from skin incision to closure. The output was defined as the surgical fee for each surgery. The study period was divided into fifty-one ten- (or eleven-) day periods. We added all the inputs and outputs of the surgical procedures for each DMU during these study periods, and computed its Malmquist index, efficiency change and technical change. RESULTS: Seven thousand nine hundred and thirty-one surgical procedures were analyzed. The overall productivity and efficiency progressed significantly both during states of emergency and during no states of emergency. Our subgroup analysis demonstrated that there were no surgical specialties that had significantly different productivity, efficiency or technical changes between states of emergency and no states of emergency. CONCLUSIONS: We demonstrated that the surgical productivity did not suffer despite the states of emergency against the COVID-19 pandemic in Japan.

Productivity Change of Surgeons During the Coronavirus Disease 2019 Pandemic in Japan.

The purpose of this study is to compute surgical total factor productivity before and during the pandemic with Malmquist index, and to evaluate the effect of coronavirus disease 2019 (COVID-19) on its productivity change. The COVID-19 pandemic has significantly shifted healthcare resources allocation; more healthcare resources have focused on measures against the COVID-19 pandemic. The authors collected data from all the surgical procedures performed in Teikyo University Hospital from April 1 through September 30 in 2019 and in 2020. Non-radial and non-oriented Malmquist model under the constant return-to-scale assumptions was employed. The decision-making unit was defined as a surgeon with the highest academic rank in surgery. Inputs were defined as (1) the number of medical doctors who assisted surgery and (2) the duration of surgical operation from skin incision to closure. The output was defined as the surgical fee for each surgery. The study period was divided into four 3-month periods. We added all the inputs and outputs of the surgical procedures for each decision-making unit during these study periods, and computed his/her Malmquist index, efficiency change, and technical change. Four thousand six hundred and two surgical procedures performed by 75 surgeons were analyzed. The productivity progressed significantly during 2019 (P = .008) while the productivity changes in 2020 were not significantly different from 0. On year-on-year comparisons, the productivity change was not significantly different from 0. The COVID-19 pandemic had a negative impact on the productivity progress of surgery that was unrelated to its countermeasures.

Effects of Lean Interventions Supported by Digital Technologies on Healthcare Services: A Systematic Review.

Despite the increasing utilization of lean practices and digital technologies (DTs) related to Industry 4.0, the impact of such dual interventions on healthcare services remains unclear. This study aims to assess the effects of those interventions and provide a comprehensive understanding of their dynamics in healthcare settings. The methodology comprised a systematic review following the PRISMA guidelines, searching for lean interventions supported by DTs. Previous studies reporting outcomes related to patient health, patient flow, quality of care, and efficiency were included. Results show that most of the improvement interventions relied on lean methodology followed by lean combined with Six Sigma. The main supporting technologies were simulation and automation, while emergency departments and laboratories were the main settings. Most interventions focus on patient flow outcomes, reporting positive effects on outcomes related to access to service and utilization of services, including reductions in turnaround time, length of stay, waiting time, and turnover time. Notably, we found scarce outcomes regarding patient health, staff wellbeing, resource use, and savings. This paper, the first to investigate the dual intervention of DTs with lean or lean-Six Sigma in healthcare, summarizes the technical and organizational challenges associated with similar interventions, encourages further research, and promotes practical applications.

Recovering from COVID - Improving operating room capacity.

INTRODUCTION: COVID-19 pandemic required that health systems made great efforts to mitigate the impact of high demands of patients requiring treatment. Triaging surgical cases reduced operating room capacity. Immunizations, massive testing, and personal protective equipment enabled re-activation of operating rooms. Delayed and newly added cases has placed stress on the system. We hypothesize that standardization in practice for tasks performed between anesthesia ready and surgery start time, also known as "prepping time", can reduce operative time, improve efficiency and increase capacity. The aim of our project was to create and implement a best practice standardized prepping protocol, to explore its impact on operating room capacity. METHODS: Once local policies allowed re-opening of the operating rooms, our multidisciplinary group developed a working plan following Adaptive Clinical Management (ACM) principles to optimize surgical prepping time. Using electronic medical record (EMR) data, surgeons with the lowest surgical prepping times were identified (positive deviants). Their surgical prepping time workflows were reviewed. A clinical standard work (CSW) protocol was created by the team leader. New CSW protocol was defined and implemented by the leader and then by the rest of the surgeons. Baseline data was automatically extracted from EMR and analyzed by statistical process control (SPC) charts using AdaptX. Balancing measures included "last case end time" and rates of surgical site infections. RESULTS: A total of 2506 patients were included for analysis with 1333 prior to intervention and 1173 after. Team leader implementated the new CSW prepping protocol showing a special cause variation with an average time improvement from 14.6 min to 11.6 min and for all surgeons from 13.8 to 12.0 min. Total cases per month increased from 70 to 90 cases per month. Baseline 'Last Case End Time' was 15.7 min later than the scheduled. New CSW improve end time with an average of 20.8 min before the schedule. Baseline surgical site infection was 0.1% for the study population. No difference was seen after implementation. DISCUSSION: Variations in performance can be quantified using funnel plots showing individual practices allowing best practice to be identified, tested and scaled. Implementation of our surgical prepping time protocol showed a sustainable increase in efficiency without affecting quality, safety or workload. This additional increase is estimated to represent approximately $2-2.5M additional revenue per year. CONCLUSION: Adaptive clinical management is a practical solution to increase OR capacity by improving efficiency to reduce extra burden presented during COVID19 pandemic.

Recovering staff, recovering services: massive-online support for recovering a paediatric service using Lean and compassionate communication.

The COVID-19 pandemic has infected tens of millions worldwide. Healthcare systems have been stretched caring for the most seriously ill and healthcare workers have struggled to maintain non-COVID services leading to backlogs.Strategies proposed to support the recovery of backlogs include additional administration support; waiting list data validation; enhanced patient communication; and use of systematic improvement methods to make rapid incremental improvements.As part of COVID-19 recovery, a hospital trust in northern England used the Lean systematic improvement approach to recover the waiting list of a paediatric service to pre-COVID levels. The intervention strategy used a massive-open-online-course (Lean Fundamentals) to support the improvement project lead to follow a structured improvement routine to apply Lean improvement techniques.By acknowledging that staff were overburdened by the requirements of COVID-19 and that patients were stuck in a system of disconnected processes, administrative activities were redesigned around an ethos of compassionate communication that put patients first.Over a period of 8 weeks, the project reduced the waiting list from 1109 to 212. Waiting times were reduced from a maximum of 36 months to a 70-day average.Lean is often described in terms of increasing process efficiency and productivity. It is not often associated with staff benefits. However, when seen in the context of unburdening staff to deliver patient care, Lean has potential to support the recovery of both staff and services. Lean Fundamentals, with its accessible massive-online design, may provide a means of supporting such improvement at scale.

The management of emergency spinal surgery during the COVID-19 pandemic in Italy.

AIMS: The current pandemic caused by COVID-19 is the biggest challenge for national health systems for a century. While most medical resources are allocated to treat COVID-19 patients, several non-COVID-19 medical emergencies still need to be treated, including vertebral fractures and spinal cord compression. The aim of this paper is to report the early experience and an organizational protocol for emergency spinal surgery currently being used in a large metropolitan area by an integrated team of orthopaedic surgeons and neurosurgeons. METHODS: An organizational model is presented based on case centralization in hub hospitals and early management of surgical cases to reduce hospital stay. Data from all the patients admitted for emergency spinal surgery from the beginning of the outbreak were prospectively collected and compared to data from patients admitted for the same reason in the same time span in the previous year, and treated by the same integrated team. RESULTS: A total of 19 patients (11 males and eight females, with a mean age of 49.9 years (14 to 83)) were admitted either for vertebral fracture or spinal cord compression in a 19-day period, compared to the ten admitted in the previous year. No COVID-19 patients were treated. The mean time between admission and surgery was 1.7 days, significantly lower than 6.8 days the previous year (p < 0.001). CONCLUSION: The structural organization and the management protocol we describe allowed us to reduce the time to surgery and ultimately hospital stay, thereby maximizing the already stretched medical resources available. We hope that our early experience can be of value to the medical communities that will soon be in the same emergency situation. Cite this article: Bone Joint J 2020;102-B(6):671-676.

Evaluation of the Efficiency in Public Health Centers in Greece Regarding the Human Resources Occupied: A Bootstrap Data Envelopment Analysis Application.

In this paper, the overall efficiency of health centers in Greece is measured by applying the input-oriented model of Data Envelopment Analysis. In addition, four different models were subjected to the input-oriented Data Envelopment Analysis to investigate the contribution of each category of human resources to the efficiency results of the health centers. The bootstrap technique was performed to generate confidence intervals for the models. Data for 155 health centers in Greece were provided by the Ministry of Health. The health centers submitted in the analysis obtained an average efficiency value of 0.932. The average results of the partial models in terms of each input show that the efficiency values achieved by the health centers are mostly influenced by the number of physicians and the number of managers employed. The second factor influencing the efficiency values of the health centers are the number of nursing staff occupied in the health centers. Non-medical staff employed in the health centers had the least contribution to the efficiencies measured. This paper provides important information for the stakeholders and the Government of Greece so as to better allocate the personnel employed in primary health care according to the efficiencies attained by the health centers.

Resilient Clinical Trial Infrastructure in Response to the COVID-19 Pandemic: Lessons Learned from the TOGETHER Randomized Platform Clinical Trial.

In response to the COVID-19 pandemic, clinical research groups across the world developed trial protocols to evaluate the safety and efficacy of treatments for COVID-19. Despite this initial enthusiasm, only a small portion of these protocols were implemented. Of those implemented, a fraction successfully recruited their target sample size to analyze and disseminate findings. More than a year and a half into the COVID-19 pandemic, only a few clinical trials evaluating treatments for COVID-19 have generated new evidence. Productive randomized platform clinical trials evaluating COVID-19 treatments may attribute their success to intentional investments in developing resilient clinical trial infrastructures. Health system resiliency discourse provides a conceptual framework for characterizing attributes for withstanding shocks. This framework may also be useful for contextualizing the attributes of productive clinical trials evaluating COVID-19 therapies. We characterize the successful attributes and lessons learned in developing the TOGETHER Trial infrastructure using a health system resiliency framework. This framework may be considered by clinical trialists aiming to build resilient trial infrastructures capable of responding rapidly and efficiently to global health threats.

Why enterprise resource planning initiatives do succeed in the long run: A case-based causal network.

Despite remarkable academic efforts, why Enterprise Resource Planning (ERP) post-implementation success occurs still remains elusive. A reason for this shortage may be the insufficient addressing of an ERP-specific interior boundary condition, i.e., the multi-stakeholder perspective, in explaining this phenomenon. This issue may entail a gap between how ERP success is supposed to occur and how ERP success may actually occur, leading to theoretical inconsistency when investigating its causal roots. Through a case-based, inductive approach, this manuscript presents an ERP success causal network that embeds the overlooked boundary condition and offers a theoretical explanation of why the most relevant observed causal relationships may occur. The results provide a deeper understanding of the ERP success causal mechanisms and informative managerial suggestions to steer ERP initiatives towards long-haul success.

Utilization of lean project management principles and health informatics to reduce operating room delays in a vascular surgery practice.

OBJECTIVES: Perioperative inefficiency can increase cost. We describe a process improvement initiative that addressed preoperative delays on an academic vascular surgery service. METHODS: First case vascular surgeries from July 2019-January 2020 were retrospectively reviewed for delays, defined as late arrival to the operating room (OR). A stakeholder group spearheaded by a surgeon-informaticist analyzed this process and implemented a novel electronic medical records (EMR) preoperative tool with improved preoperative workflow and role delegation; results were reviewed for 3 months after implementation. RESULTS: 57% of cases had first case on-time starts with average delay of 19 min. Inappropriate preoperative orders were identified as a dominant delay source (average delay = 38 min). Three months post-implementation, 53% of first cases had on-time starts with average delay of 11 min (P < 0.05). No delays were due to missing orders. CONCLUSIONS: Inconsistent preoperative workflows led to inappropriate orders and delays, increasing cost and decreasing quality. A novel EMR tool subsequently reduced delays with projected savings of $1,200/case. Workflow standardization utilizing informatics can increase efficiency, raising the value of surgical care.