System Cost Savings Research Articles

A Developer's Perspective on Clinical Evidence and Benefits for Rituximab Biosimilar Uptake, with a Focus on CT-P10.

To date, four rituximab biosimilars have received regulatory approval from the European Medicines Agency and/or US Food and Drug Administration. CT-P10 was the first rituximab biosimilar to be approved by each agency, in 2017 and 2018, respectively. Regulatory approval of CT-P10 followed demonstration of pharmacokinetic equivalence to the reference product in a phase I study in patients with rheumatoid arthritis. Phase III pivotal studies of CT-P10 subsequently demonstrated equivalence or non-inferiority of pharmacokinetics and efficacy between CT-P10 and reference rituximab in patients with rheumatoid arthritis, advanced-stage follicular lymphoma, and low-tumour-burden follicular lymphoma. Almost 5 years after its initial regulatory approval, significant real-world experience has accumulated with CT-P10 use, particularly in diffuse large B-cell lymphoma, one of the indications approved by extrapolation. This article summarises the pivotal data underlying regulatory approval for the four licensed rituximab biosimilars, before focusing on real-world data gathered with CT-P10. These data provide further support for the safety and effectiveness of CT-P10 and should boost healthcare professional and patient confidence in its use. Pharmacoeconomic analyses support the potential healthcare system cost savings offered by rituximab biosimilar uptake, which could lead to improved patient access to biologic treatments. Opportunities arising from biosimilar uptake extend further, potentially enabling innovative investigator-led research and therapeutic advances.

Implementing Home Health Monitoring for Chronic Disease Management in British Columbia

Home health monitoring (HHM) enables health care providers to monitor a patient’s health status remotely using digital technology. In 2013, the government of British Columbia (BC) partnered with a telecommunications provider and invested $52M in HHM programs for patients with complex care needs. Telehealth has evolved over the past two decades to improve access and delivery of care, with HHM emerging as a strategy for proactive chronic disease management. The goals of the provincial HHM initiative are to reduce acute care utilization, reduce health system costs and improve patient self-management of chronic conditions. Following a series of successful pilot projects, funding for expanded HHM initiatives was made available through a provincial Strategic Investment Fund and continued support from Canada Health Infoway. Evaluations of several HHM programs demonstrated high levels of patient satisfaction, reduced emergency department visits, health system cost savings, and improved patient self-care and quality of life. Optimizing referral rates and expanding HHM programs to include a wider range of chronic conditions are opportunities for future growth, with sustainability dependent on securing long-term funding sources.

Abstract P4-06-03: Clinical-risk assessment of ER positive, Her2 negative breast cancer patients: Correlation between the average modified magee score and mammaprint

Abstract Background: MammaPrint (MP) is an FDA approved early breast cancer prognostic genomic assay that examines the expression levels of 70 genes and classifies clinically high-risk patients with early-stage breast cancer into low or high risk of distant metastasis. Current ASCO guidelines do not support using MP testing in clinically low-risk patients. Historically, assessing a patient’s clinical risk for breast cancer recurrence has relied on a subjective evaluation of histologic factors, immunohistochemical features, and clinical characteristics. Genomic assay testing provides more objective prognostic and predictive information than those more traditional methods; however, several studies have shown that statistical models using standard histologic variables can give valuable prognostic information, and might be used as an alternative approach to genomic assays for clinical risk-assessment and risk-stratification, particularly in lower risk breast cancer patients, potentially resulting in significant cost savings for health care systems. One of these statistical models, the average Modified Magee equation, has been shown to be prognostic for a low risk of recurrence in ER positive Her2 negative breast cancer patients who have an average Modified Magee score (aMMs) of ≤ 12. The aMMs has been shown to correlate well with the Oncotype DX recurrence score; however, there is limited data on the correlation between the aMMs and MP. In this study, we evaluated the concordance between the aMMs and the MP index (MPI). Methods: 222 consecutive patients with a new diagnosis of hormone receptor positive Her-2 negative breast cancer at the University of Rochester between April 2020 and December 2020 were sent for MP testing. The aMMs was determined for each patient based on the estrogen receptor status, progesterone receptor status, HER-2 status, Ki-67 proliferation index, Nottingham score, and tumor size. Based on the previous literature, patients were risk-stratified by the aMMs into three groups: 1) low risk (aMMs ≤ 12; n = 75); 2) low - intermediate risk (aMMs >12 and ≤ 18; n = 96); and, 3) high risk (aMMs >18, n = 51). Based on the previous literature, patients were risk-stratified by the MPI into two groups: 1) low risk (MPI 0 to +1); and, 2) high risk (MPI -1 to 0). The correlation between the aMMs and the MPI was evaluated using the Pearson correlation coefficient. Results: The aMMs showed a negative correlation (r= -0.55) with the MPI, consistent with a lower risk aMMs more likely being associated with a lower risk MPI. 92% of patients with an aMMs ≤ 12 (very low risk) were classified as low risk by MP. 72% of patients with an aMMs > 12 and ≤ 18 (low - intermediate risk) were classified as low risk by MP. 47% of patients with an aMMs > 18 (high risk) were classified as high risk by MP (Table 1). All patients with an aMMs ≥ 24.7 (n=8) were classified as high risk by MP. Conclusion: Our study suggests that hormone receptor positive, Her-2 negative breast cancer patients with a lower risk aMMs are likely to have a lower MPI, suggesting that these patients have a decreased risk for breast cancer recurrence. As the aMMs approaches higher risk, the concordance with the MPI decreases; however 100% of patients with an aMMs ≥ 24.7 were classified as high risk by MP. The aMMs can be helpful in clinical risk-assessment prior to making a decision about sending a patient specimen out for MP testing. Additional studies are warranted. Table 1.Risk of recurrence using the average Modified Magee score (aMMs) and the MammaPrint (MP) IndexaMMs Risk-stratification categoryMP Low risk n (%)MP High risk n (%)Very low (aMMs ≤ 12)69 (92%)6 (8%)Low - Intermediate (aMMs > 12 and ≤ 18)69 (72%)27 (28%)High (aMMs >18)27 (53%)24 (47%) Citation Format: Hani Katerji, Huina Zhang, David Hicks, Bradley M Turner. Clinical-risk assessment of ER positive, Her2 negative breast cancer patients: Correlation between the average modified magee score and mammaprint [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-06-03.

Abstract P4-06-07: Clinical risk-assessment, risk-stratification, and outcomes of ER positive, HER2 negative breast cancer patients using the Rochester modified Magee algorithm (RoMMA)

Abstract INTRODUCTION: In 2013, Klein and Dabbs et al. published three linear regression equations (the new Magee equations) using different combinations of standard histopathologic variables. In 2015, our group published a modification of the new Magee equations. Based on this modification, we published an algorithmic approach using an average Modified Magee equation. This algorithmic approach supported reflex Oncotype DX (ODX) testing based on several cutoff points using an average Modified Magee score. In 2019, we validated this algorithmic approach as the Rochester Modified Magee Algorithm (RoMMA) in a multi-institutional study, with outcome data in 247 patients, suggesting that ER positive breast cancer patients with an average Modified Magee score of ≤ 12 had a low risk of breast cancer recurrence. There has been limited published outcome data on the Magee equation since that 2019 study. We have further refined our risk-stratification approach, with additional outcome data in 416 ER positive breast cancer patients. METHODS: 416 patients with an ODX recurrence score who had at least five years of follow-up data or a breast cancer recurrence were included in the final outcome analysis (2008-2017). All patients received either Tamoxifen or an aromatase inhibitor. None of the patients received adjuvant systemic chemotherapy. The average Modified Magee score was calculated and patients were stratified into four risk-stratification categories: 1) very low, 2) low ≤ 50 years of age, 3) low > 50 years of age, and 4) high. We compared these four risk-stratification categories, with outcomes, between the average Modified Magee score and the ODX recurrence score. A p-value of < 0.05 was considered statistically significant. RESULTS: 27/416 (6.5%) patients had a recurrence of breast cancer. When comparing the same risk category groups, there was no significant difference between the average Modified Magee score and the ODX recurrence score (Table 1). CONCLUSION: Our study further reinforces that breast cancer patients can be confidently stratified into low and high risk recurrence groups using the average Modified Magee score. The average Modified Magee score may be an alternative to ODX for clinical risk-assessment and risk-stratification, particularly in lower risk patients, offering breast cancer patients increased access to clinical risk-assessment and risk-stratification, both domestically and internationally, with a potential significant cost savings for health care systems. A large prospective evaluation, similar to the studies done by ODX, using multi-institutional data or data from studies like the NSABP trial B-14 and the NSABP trial B-20, is necessary. Table 1.Risk-stratification categories and outcomes using the average Modified Magee score (aMMs) and the Oncotype DX recurrence score (ODXRS)RECURRENCENO RECURRENCEP-VALUEVERY LOW (N)aMMs ≤ 12 (76)1 (1.3)75 (98.7)0.65ODXRS < 11 (108)4 (3.7)104 (96.3)LOW ≤ 50 years of age (N)aMMs > 12, ≤ 18 (50)3 (6.0)47 (94.0)1.0ODXRS 11 - 15 (32)1 (3.1)31 (96.9)LOW >50 years of age (N)aMMs > 12, ≤ 18 (153)8 (5.2)145 (94.8)0.52ODXRS 11 - 25 (214)16 (7.5)198 (92.5)HIGH (N)aMMs > 18 (137)15 (10.9)122 (89.1)1.0ODXRS ≥ 16 - 25 (33)* and ODXRS > 25 (29)**6 (9.7)56 (90.3)* Patients ≤ 50 years of age with an ODXRS of ≥16 - 25. ** All patients with an ODXRS of > 25 Citation Format: Numbereye Numbere, Ioana Moisini, Ajay Dhakal, Kristin Skinner, Michelle Shayne, Mary Ann Gimenez Sanders, Huina Zhang, David Hicks, Bradley M Turner. Clinical risk-assessment, risk-stratification, and outcomes of ER positive, HER2 negative breast cancer patients using the Rochester modified Magee algorithm (RoMMA) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-06-07.

Benefits of cross-border citizen energy communities at distribution system level

One challenge of the EU energy transition is the integration of renewable electricity generation in the distribution system. EU energy law proposes a possible solution by introducing “citizen energy communities” (Directive 2019/944/EU) which may be open for “cross-border participation”. This article proposes an innovative way of implementing such cross-border communities by linking distribution systems via a “switchable element”, a generation, storage, or consumption asset with a connection to each country. An optimization model has been developed to calculate the system cost savings of such a connection. Linking regions with complementary characteristics regarding electricity generation and demand via a switchable element leads to more efficient system utilization. Findings are relevant for the transposition of “citizen energy communities” in national laws.

An opaque selling scheme to reduce shortage and wastage in perishable inventory systems

Effective management of perishable inventory systems is often strewn with challenges, especially when a strong trade-off relationship exists between shortage and wastage of perishables: A smaller inventory increases the chance to lose sales (leading to higher expected shortage cost), while a larger inventory increases the chance to waste perishables (leading to higher expected wastage cost). The root cause of this strong trade-off relationship is high product demand variability. To mitigate the issue and reduce the cost of operating perishable inventory systems, some grocery stores utilize an opaque selling scheme: selling an anonymous product whose brand or exact specification is shielded from customers at the time of sale. The use of opaque products has now become a popular means to reduce shortage/wastage at grocery stores. However, there has been little discussion of the effectiveness of opaque schemes applied to perishable inventory systems.In this paper, we propose an opaque scheme based on the balancing policy on demand, which tries to average out orders for products. We confirm both analytically and numerically that this opaque scheme effectively reduces product demand variability, thereby reducing both shortage and wastage for perishable inventory systems under a base-stock policy. We also present an analytical formula that reveals insights into the opaque scheme: The ratio between the opaque proportion and the coefficient of variation of product demands plays a key role to determine the effectiveness of our opaque scheme. Furthermore, we provide a rule of thumb to find the threshold opaque scheme parameters needed to achieve the maximum total cost savings for perishable inventory systems. We hope that many retailers selling perishables (e.g., fresh produce and baked goods) find the opaque scheme useful, implement it, and contribute to the reduction of the food wastage.

From demand forecasting to inventory ordering decisions for red blood cells through integrating machine learning, statistical modeling, and inventory optimization.

The demand and supply of blood are highly variable over time. Blood inventory management that relies heavily on experience-based decisions may not be adaptive to real demand, leading to high operational costs, wastage, and shortages. We combined statistical modeling, machine learning, and optimization methods to develop a data-driven demand forecasting and inventory management strategy for red blood cells (RBCs). We then used the strategy to inform daily blood orders. A secondary semi-weekly (twice per week) ordering strategy was developed to handle the last-mile split delivery problem for blood suppliers, characterized by multi-deliveries to the same location multiple times during a short period of time. Both strategies were evaluated using the TRUST database including all patient data across four hospitals in Hamilton, Ontario. We identified 227,944 RBC transfusions for 40,787 patients in Hamilton, Ontario from 2012 to 2018. The predicted daily demand from the hybrid demand forecasting model was not significantly different from the actual daily demand (paired t-test p-value=0.163); however, the proposed daily ordering quantity from the model was significantly lower than the actual ordering quantity (p-value <0.001). The proposed daily ordering strategy reduced inventory levels by 38.4% without risk of shortages, leading to an overall cost reduction of 43.0% (95% confidence interval [CI]: 42.3%, 43.7%) compared with the actual cost. The semi-weekly ordering strategy reduced ordering frequency by 62.6% (95% CI: 61.5%, 63.7%). The proposed data-driven ordering strategy combining demand forecasting and inventory optimization can achieve significant cost savings for healthcare systems and blood suppliers.

Optimal configuration and diversification of wind turbines: A hybrid approach to improve the penetration of wind power

Literature indicates a decline in the market value of wind power with increasing market penetration. Two promising measures to mitigate this market value drop are system-friendly turbines and geographic diversification. This study analyzes the combined potential of these two measures, introduced in this paper as the hybrid approach, to simultaneously improve market values, and to reduce system costs and the overall subsidy need in Germany. Therefore, promising diversification regions and site optimal turbine configurations are identified. The corresponding market values, levelized cost of electricity and system costs are predicted for variable renewable energy penetration rates of up to 65% (2030). The analysis shows that the market value drop in diversified regions using system-friendly turbines is less severe. Furthermore, the hybrid approach results in system cost and subsidy savings. Additional sensitivities show that the dominant share of the hybrid approach benefits can be attributed to the use of system-friendly turbines as only a small fracture of the hybrid approach savings is realized when using standard turbines instead of system-friendly ones. This leads to the conclusion that geographic diversification alone is not a promising approach to improve system costs and overall market values in Germany.

Identifying interactions between size effects in New South Wales local government

ABSTRACT Size effects such as economies of scale and economies of scope can be utilised to achieve cost savings in local government systems. Numerous municipal reform policies in Australia and elsewhere have historically been premised on size effects. In this paper, we investigate whether an interaction effect exists between scale economies and scope economies in New South Wales local government using a 2011 sample of local councils. We estimate the effects of scale and specialisation on efficiency by way of a multiple regression, using a novel approach to measure specialisation. We find empirical evidence that indicates economies of scale and economies of scope are both likely to be present across a broad range of scales. However, we find no evidence of any interaction effect between scale and scope economies.

A lifecycle cost model considering both component and system burn-in for operationally unrepairable systems

PurposeThis study presents a lifecycle cost model considering multi-level burn-in for operationally unrepairable systems including assembly and warranty costs. A numerical method to obtain system reliability under component replacement during burn-in is also presented with derived error bounds.Design/methodology/approachThe final system reliability after component and system burn-in is obtained and warranty costs are computed. On failure during operation, the system is replaced with another that undergoes an identical burn-in procedure. Cost behaviours for a small and large system are shown in a numerical example.FindingsThere are more cost savings when system burn-in is conducted for a large system whereas a strategy focusing on component burn-in only can also result in cost savings for small systems. In addition, a minimum system burn-in duration is required before cost savings are achieved for these operationally unrepairable systems.Originality/valueThe operationally unrepairable system is a niche class of systems which small satellites fall under and no such study has been conducted before. The authors present a different approach towards the testing of small satellites for a constellation mission.

Evaluation of benefits through coordinated control of numerous thermal energy storage in highly electrified heat systems

This paper proposes a novel decentralised control approach dedicated to coordinating the operation of a large population of residential thermal energy storage characterised by diversified specifications, while innovatively considering the operational constraints on both the national and the local level. The presented iterative algorithm sequentially updates the storage operational schedule under the real-time electricity price scheme to achieve cost savings for each individual participant and the total system, while effectively avoiding the violation of local distribution network restrictions. The transmission topology is explicitly considered to investigate the impacts of transmission congestion on the electricity marginal prices. The results of a series of case studies demonstrate that the proposed coordination approach can effectively enable individual energy arbitrage and achieve 22.53 % system cost savings compared to the 10.34 % savings when coordination is absent. Moreover, the simulation results manifest that the coordinated control approach can cost-effectively perform distribution congestion management to ensure no local network is overloaded, which will cause 12.3 % increase in system operational costs. Overall, through coordinating the operation of numerous residential thermal energy storage to perform both energy arbitrage and distribution network congestion management, the proposed control approach can benefit the system operation at both the national and local levels.

Estimating the Public Health and Economic Impact of Introducing the 13-Valent Pneumococcal Conjugate Vaccine or 10-Valent Pneumococcal Conjugate Vaccines into State Immunization Programs in India.

IntroductionAlthough the pneumococcal conjugate vaccine (PCV) has been introduced into select state immunization programs (SIPs) in India, many children remain unvaccinated. Recently, India’s Advisory Committee on Vaccines & Immunization Practices recommended PCV on the pediatric immunization schedule nationally. This study estimates the public health and economic impact of introducing either Pfizer’s 13-valent PCV (PCV13-PFE), GlaxoSmithKline’s 10-valent PCV (PCV10-GSK), or Serum Institute of India’s 10-valent PCV (PCV10-SII) into every pediatric SIP.MethodsA model was developed to predict the disease cases, deaths, and costs associated with implementing PCV13-PFE, PCV10-GSK, or PCV10-SII in SIPs compared to no vaccination program across a 5-year period (2021–2025). State and national-level uptake rate and clinical and economic input parameters were collected from published literature. Disease outcomes included invasive pneumococcal disease, inpatient and outpatient pneumonia, and otitis media. Costs were estimated as vaccine-related costs and direct medical costs incurred to the healthcare system. Results were reported by individual state and aggregated nationally. ResultsEstimated over 5 years, implementing PCV13-PFE in SIPs could avert 12.1 million cases and save 626,512 lives among children under 5 years old compared to no vaccination. This corresponds to net national cost savings of over $1.0 billion. Both lower-valent PCVs are estimated to provide less economic savings than PCV13-PFE inclusive of vaccine-related costs. Compared with PCV13-PFE, implementing PCV10-GSK or PCV10-SII nationally is estimated to have a smaller public health impact, with PCV10-GSK averting 8.4 million cases (436,577 deaths) and PCV10-SII preventing 10.3 million cases (531,545 deaths) in India compared to no vaccination, respectively.ConclusionImplementation of PCV13-PFE throughout India is estimated to provide greater public health and economic benefits than PCV10-GSK or PCV10-SII SIPs. Our analysis highlights the substantial disease cases, deaths, and health system cost savings that may be realized from implementing PCV programs throughout India.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40121-021-00498-4.

PRO41 The Economic and Quality of Life impact of Entrectinib on CNS metastasis control

Most anticancer drugs cannot achieve adequate CNS exposure due to being P-gp substrates, a key efflux transporter of the blood–brain barrier. Entrectinib is a weak P-gp substrate and achieves CNS therapeutic levels. Crizotinib and larotrectinib (inhibitors of the same class) are strong P-gp substrates with poor CNS exposure. Therefore, the potential economic and patient quality of life value of entrectinib in targeting and resolving CNS metastases is patient and healthcare system relevant. Entrectinib is a potent and selective inhibitor of ROS1/TRK/ALK tyrosine kinase activity in vitro with systemic and CNS activity. Intracranial ORRs of 79.2% and 62.5% were observed in adult patients with ROS1 fusion positive NSCLC and NTRK fusion positive solid tumours, respectively, who had measurable baseline CNS metastases. For ROS1-positive NSCLC, the median intracranial PFS was 12.0 months, while for NTRK it was 10.1 months. Published costs incurred by patients with early brain metastases vs. patients without were applied to the average duration in which the cohort was free of CNS metastases (ie. in the CNS Progression Free state). Similarly, the QALY benefit was estimated by applying literature EQ-5D utility estimates for patients with CNS metastases vs. the utilities derived from the entrectinib trials for patients without CNS metastases; again, informed by the average duration of the CNS Progression Free state. The CNS effect of entrectinib could result in significant cost savings of $62K and $58K USD per patient with baseline CNS metastases and ROS1-positive NSCLC or NTRK solid tumours respectively. Similarly, resolving CNS metastases with entrectinib would contribute additional QALYs of 0.24 and 0.28 per patient for ROS1-positive and NTRK solid tumours respectively. Entrectinib has demonstrated important CNS clinical benefit relative to other available treatments, which could lead to significant healthcare system cost savings and substantial quality of life improvements for patients.

A Pragmatic Non-Randomized Trial of Prehabilitation Prior to Cancer Surgery: Study Protocol and COVID-19-Related Adaptations.

BackgroundExperimental data highlight the potential benefits and health system cost savings related to surgical prehabilitation; however, adequately powered randomized controlled trial (RCT) data remain nascent. Emerging prehabilitation services may be informed by early RCT data but can be limited in informing real-world program development. Pragmatic trials emphasize external validity and generalizability to understand and advise intervention development and implementation in clinical settings. This paper presents the methodology of a pragmatic prehabilitation trial to complement emerging phase III clinical trials and inform implementation strategies.MethodsThis is a pilot pragmatic clinical trial conducted in a large academic hospital in Toronto, Ontario, Canada to assess feasibility of clinical implementation and derive estimates of effectiveness. Feasibility data include program referral rates, enrolment and attrition, intervention adherence and safety, participant satisfaction, and barriers and facilitators to programming. The study aims to receive 150 eligible referrals for adult, English-speaking, preoperative oncology patients with an identified indication for prehabilitation (e.g., frailty, deconditioning, malnutrition, psychological distress). Study participants undergo a baseline assessment and shared-decision making regarding the intervention setting: either facility-based prehabilitation or home-based prehabilitation. In both scenarios, participants receive an individualized exercise prescription, stress-reduction psychological support, nutrition counseling, and protein supplementation, and if appropriate, smoking cessation program referrals. Secondary objectives include estimating intervention effects at the week prior to surgery and 30 and 90 days postoperatively. Outcomes include surgical complications, postoperative length of stay, mortality, hospital readmissions, physical fitness, psychological well-being, and quality of life. Data from participants who decline the intervention but consent for research-related access to health records will serve as comparators. The COVID-19 pandemic required the introduction of a ‘virtual program’ using only telephone or internet-based communication for screening, assessments, or intervention was introduced.ConclusionThis pragmatic trial will provide evidence on the feasibility and viability of prehabilitation services delivered under usual clinical conditions. Study amendments due to the COVID-19 pandemic are presented as strategies to maintain prehabilitation research and services to potentially mitigate the consequences of extended surgery wait times.

A decision integration strategy for short-term demand forecasting and ordering for red blood cell components

Blood transfusion is one of the most crucial and commonly administered therapeutics worldwide. The need for more accurate and efficient ways to manage blood demand and supply is an increasing concern. Building a technology-based, robust blood demand and supply chain that can achieve the goals of reducing ordering frequency, inventory level, wastage and shortage, while maintaining the safety of blood usage, is essential in modern healthcare systems. In this study, we summarize the key challenges in current demand and supply management for red blood cells (RBCs). We combine ideas from statistical time series modeling, machine learning, and operations research in developing an ordering decision strategy for RBCs, through integrating a hybrid demand forecasting model using clinical predictors and a data-driven multi-period inventory problem considering inventory and reorder constraints. We have applied the integrated ordering strategy to the blood inventory management system in Hamilton, Ontario using a large clinical database from 2008 to 2018. The proposed hybrid demand forecasting model provides robust and accurate predictions, and identifies important clinical predictors for short-term RBC demand forecasting. Compared with the actual historical data, our integrated ordering strategy reduces the inventory level by 40% and decreases the ordering frequency by 60%, with low incidence of shortages and wastage due to expiration. If implemented successfully, our proposed strategy can achieve significant cost savings for healthcare systems and blood suppliers. The proposed ordering strategy is generalizable to other blood products or even other perishable products.

Two-stage fuzzy-logic-based for optimal energy management strategy for SOFC/PV/TEG hybrid polygeneration system with electric charging and hydrogen fueling stations

Integration between supplies for stationary power and vehicles is potentially useful for increasing the efficiency and the reliability of energy generation systems. Solid oxide fuel cell is one matured technology, which is suitable for a polygeneration system and provides an integration of supply for stationary power and vehicles. However, a combination of solid oxide fuel cell with photovoltaic thermal and thermoelectric generation increases the complexity of a polygeneration system. The system needs a management strategy for dispatching the energies produced. Therefore, in this work, a fuzzy energy management strategy was applied for this polygeneration system by considering two different configurations: an off-grid system with electric vehicle supply and an on-grid system with hydrogen vehicle supply. A two-stage fuzzy energy management strategy considering optimization and management of multi-parameters of the polygeneration components was considered. The evaluation of the optimum fuzzy was analyzed based on energy, economic, and environmental criteria. From the results obtained, the optimal strategy increased the reliability, energy, and system cost savings by 22.05%, 22.4%, and 32.58%, respectively. Moreover, the optimum management reduced the power loss of the polygeneration system by about 48.82%, which was achieved by the configuration with electric vehicles supply and off-grid connection.

Enhancing Value-Based Care With a Walk-in Clinic: A Primary Care Provider Intervention to Decrease Low Acuity Emergency Department Overutilization.

BackgroundEmergency department overutilization is a known contributor to the high per-capita healthcare cost in the United States. There is a knowledge gap regarding the substitution effect of walk-in clinic availability in primary care provider (PCP) offices and emergency department utilization (EDU). This study evaluates associations between PCP availability and EDU and analyzes the potential cost savings for health systems.MethodsA retrospective cohort analysis compared low acuity EDU rates in established patients at a family medicine residency's PCP office before and after walk-in clinic implementation. The practice had 12 providers, 12 residents, and a patient panel of approximately 7,000-8,000. Inclusion criteria were met if patients were: (1) established with the PCP office, (2) had a low acuity emergency department (ED) visit (emergency index score level 4 or 5) OR had a walk-in clinic visit at the family practice. ED visits were tracked from January 2018 to January 2020 and encounters were compared numbers to pre and post-implementation of a walk-in clinic. Cost savings for comparable management was estimated with average price differences for low acuity encounters in the ED versus clinic.ResultsOver the two-year timeframe, there were 10,962 total visits to the ED by family practice patients, 4,250 of these visits were low acuity. Despite gross monthly increases of EDU from 2018-2020, after implementation of a walk-in clinic in 2019, rates of total EDU decreased by 1.5% and low acuity utilization rates also decreased. The average annual patient census nearly doubled from 5,763 to 8,042. T-tests confirmed statistical significance with p-values <0.05. Average low acuity ED visits ($437) cost 4.9 times more than comparable PCP office visits ($91). Managing 2,387 patients in the walk-in clinic resulted in an estimated annual cost savings of $825,902.ConclusionExtended walk-in availability in primary care offices provides non-ED capacity for low acuity management and might mitigate low acuity ED utilization while providing more cost-effective care. This study supports similarly described pre-hospital diversions in reducing ED over-utilization by increasing access to care. Higher levels of evidence are needed to establish causality.

Durability and Performance Limitations in Currently Available Alkaline Exchange Membrane Electrolysis Materials and the Relationship to Total System Cost

Anion exchange membrane (AEM) electrolyzers have the potential to reduce the cost of hydrogen generated via. electrolysis through reducing the cost of stack materials, improved electrochemical kinetics, and exhibiting a higher tolerance range for water purity (e.g. brackish and saltwater electrolysis). These potential benefits have resulted in a large amount of research funding, and as a result several commercial AEMs are now available. Additionally, several commercial, AEM specific catalysts are also available.With the increasing maturity of AEM electrolysis (still in the very early stages), there is a growing need for benchmark performance and durability using only membrane electrode assembly (MEA) materials that are commercially available. Several materials, both polymers and catalysts, will be discussed for both performance and durability under differential pressure. The incumbent technology, proton exchange electrolyzers, typically operate up to 435 psig differential H2 pressure accomplished through a combination of electrolysis and electrochemical compression. To provide a more direct comparison to the current technology, durability will be measured under differential H2 pressure. Additionally, test will be performed to identify presence of electronic shorting or cross-cell leaks, both cell failures that will result in apparent improved performance due to the lower operating voltage.For industry to adopt AEMs, there must be demonstrated device reliability and projected system cost savings. A techno-economic analysis will be performed to compare AEM and PEM electrolysis in several different scenarios to better understand the state of the technology.

Response time analysis of multiframe mixed-criticality systems with arbitrary deadlines

The well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterized by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the new multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Criticality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. A constrained-deadline model is initially targeted, and then extended to the more general, but also more complex, arbitrary-deadline scenario. The corresponding optimal priority assignment for our schedulability analysis is also identified. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the static and adaptive mixed-criticality scheduling tests oblivious to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 20% and 31.4% higher scheduling success ratio (in absolute terms) for constrained-deadline analyses and arbitrary-deadline analyses, respectively, when compared to the best of their corresponding frame-oblivious tests.

Managing Heat in Underground Mines: the Importance of Incorporating the Thermal Flywheel Effect into Climatic Modeling

Understanding the effects of various ventilation and climatic parameters on the work conditions and comfort in underground mines is critical for efficient ventilation system design and cost savings and to ensure the health and safety of mine workers. To understand the effects that the thermal damping effect (TDE) and the thermal flywheel effect (TFE) have on the ventilation system design and potential cooling system, this paper compares and analyzes the wet and dry-bulb temperatures at the bottom of an intake shaft using two modeling software packages, Ventsim™ and Climsim™. The comparison shows the consequences and importance of taking into account the TDE/TFE when predicting the climatic conditions in future underground mines, especially when deciding on whether a cooling system should be employed in order to provide adequate climatic conditions in the production stopes, dead-end development headings, and throughout the mine. Ventsim™ is able to account for the TFE, while Climsim™ does not. Both software packages have their uses and are used within the mining industry, but it is useful to understand their limitations and where the future of underground climatic modeling will lead.