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This study aims to analyze the involvement of US colleges and universities in methane capture projects in the waste sector and their related educational initiatives aiming to build circular economies and reduce greenhouse gas (GHG) emissions.

The authors compiled a subset of 22 “early adopting” institutions – those that received media attention for solid or liquid waste methane capture projects from 1999 to the present. The authors included all cases found within a reasonable number of queries. The institutions fell into two groups: (1) schools directly involved in gas capture projects, and (2) schools that purchased third-party offsets tied to landfill gas (LFG) projects. The authors assessed transparency and accountability, which the authors determined as fundamental to GHG mitigation and climate education. The authors expanded on five innovative cases from our subset to illustrate pathways to improve equity and circularity in waste flows.

US higher education institutions (HEIs) can measure and educate more transparently about waste streams. While institutions using LFG offsets range in size, curriculum and geography, there were few methane capture projects supplying energy directly to campuses. Although HEIs generally rely on third-party providers for waste management, cases demonstrate how universities can play a role in methane use, and be incubators for climate action and related employment.

Illustrative cases demonstrate the educational and institutional benefits from methane use.

HEIs can generate pathways of a “just” transition to a fossil-free circular economy.

To the best of the authors’ knowledge, this is one of the first comparative studies examining waste sector methane capture and the potential for high-impact educational practices and sustainability training in US HEIs.

The purpose of this study is to evaluate the determinants of health outcomes of dialysis patients, while specifically focusing on the role of dialysis process measures and dialysis practice characteristics. The dialysis industry is facing a major transition from a volume-based health care system to a value-based cost-efficient care model, in the USA. Under the bundled Prospective Payment System, the treatment-based payment model is subject to meeting quality thresholds as defined by clinical process measures including dialysis adequacy and anemia management. Few studies have focused on studying these two processes and their association with the quality of patient health outcomes.

In this study, the authors focus on identifying the determinants of patient health outcomes among freestanding dialysis clinics, using a large cross-sectional data set of 4,571 dialysis clinics in the USA. The authors use econometric analyses to estimate the association between dialysis facility characteristics and practice patterns and their association with dialysis process measures and hospitalization risk.

The authors find that reusing dialyzers and increasing the number of dialysis stations is associated with higher levels of clinical quality. This research indicates that deploying more nurses on-site allows patients to avail adequate dialysis, while increasing the supply of physicians can hurt anemia control process. In addition, the authors report that offering peritoneal dialysis and late night shifts are not beneficial practices in terms of their impact on the hospitalization risk.

While early studies of dialysis care mainly focused on the associations between practice patterns and patient outcomes, this research reveals the underlying mechanisms of these relationships by exploring the mediation effects of clinical dialysis processes on patient outcomes. The results indicate that dialysis process measures mediate the impact of the operational characteristics of dialysis centers on patient hospitalization rates.

This study offers several managerial insights for owners and operators of dialysis clinics with respect to the association between managerial and clinical practices that they deploy within dialysis clinics and their impact on clinical quality measures as well as hospitalization risk of patients. Managers can draw on this study to optimize staffing levels in their dialysis clinics, and implement innovative clinical practices.

Considering the growth in healthcare expenditures in developing and developed countries, and specifically for costly diagnoses such as dialyses, this study offers several insights related to the inter-relationships between dialysis practice patterns and their clinical quality measures.

This study makes several major contributions. First, the authors address the extant gap in the literature on the relationships between dialysis facility and practice characteristics and clinical outcomes, while specifically highlighting the role of clinical process measures as antecedents of patient hospitalization ratio, a key metric used to measure performance of dialysis clinics. Second, this study sheds light on the underlying mechanisms that serve as enablers of the dialysis adequacy and anemia management. To the best of the authors’ knowledge, this is the first study to explore these relationships in the dialysis industry. The authors’ approach provides a new direction for future studies to explore the pathways that may impact clinical quality measures in the delivery of dialysis services.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.