Reduction In Total Cost Research Articles

366 Micro-Endoscopic Posterior Cervical Foraminotomy and Discectomy is Health Economically Dominant to Anterior Cervical Discectomy and Fusion for Unilateral Cervical Radiculopathy

INTRODUCTION: Micro-endoscopic posterior cervical foraminotomy and discectomy (MPCF) has served as a minimally invasive, motion sparing alternative to ACDF for unilateral cervical radiculopathy for decades. While growing data suggests similar effectiveness, the cost effectiveness and potentially superior healthcare value of MPCF vs ACDF remains largely unstudied. METHODS: The National Quality Outcomes Database (QOD) was queried for 323 consecutive ASA 1-3 patients (201 ACDF, 122 MPCF) performed at the authors' single institution for unilateral cervical radiculopathy at our ambulatory surgical center (ASC). Propensity-matching yielded 222 patients. Resource utilization, missed workdays, and EQ5D quality adjusted life year (QALY) gains were assessed over a one-year period. Direct cost (resource use x unit costs based on Medicare national allowable payment amounts) and indirect cost (missed workdays x average US daily wage) were recorded and incremental cost-effectiveness ratio (ICER) was calculated. RESULTS: Estimated blood loss, and length of surgery were less for MPCF vs. ACDF (p < 0.001). All other safety measures and patient-reported outcomes were similar between cohorts. MPCF vs. ACDF demonstrated reduction in total one-year costs of $6,709 (Medicare) and $13,061 (private payers) (p < 0.001), and comparable QALYs gained. ACDF vs. MPCF had a cost ineffective ICER of $91,773/QALY-gained and $178,668/QALY for Medicare and private payer patients, respectively. CONCLUSIONS: MPCF is a health-economically dominant option to ACDF for unilateral cervical radiculopathy given the increased healthcare costs despite comparable safety, outcome, and QALY gains associated with ACDF.

A Multi-Objective Virtual Network Migration Algorithm Based on Reinforcement Learning

Virtual network migration (VNM) helps improve network performance by remapping a subset of virtual nodes or links to physical infrastructure, aligning the resource allocation to the virtual network&#x0027;s changing conditions. However, existing VNM methods neglect integrating multiple objectives that affect network performance, such as energy, communication, migration, and service level agreement violation (SLAV). It is challenging to make VNM decisions to optimize the overall objective in a large-scale cloud environment. This article establishes a multi-objective optimization model and proposes a multi-objective VNM algorithm called MiOvnm. The MiOvnm employs the double deep <inline-formula><tex-math notation="LaTeX"><?TeX $Q$?></tex-math></inline-formula>-learning approach to cope with ample state space. It also applies an action selection method called actfilter to deal with large-scale action space. The MiOvnm finds the migration action with optimal potential reward from the candidate action set. Simulation results demonstrate the superiority of our MiOvnm to the state-of-the-art methods. More specifically, MiOvnm reduces average SLAV, communication cost, and total cost by 24.32&#x0025;, 4.95&#x0025;, and 12.45&#x0025;, respectively. Furthermore, evaluation results in a real-world OpenStack platform reveal that making full use of computation and network resources, the MiOvnm reduces the completion time of computation- and network-intensive benchmarks by 11.35&#x0025; and 10.31&#x0025;, respectively, with a total cost reduction of 26.02&#x0025;.

Implementation of a Streamlined Care Pathway to Reduce Cost and Length of Stay for Patients Undergoing Endoscopic Transsphenoidal Pituitary Surgery.

We implemented a streamlined care pathway for patients undergoing endoscopic transsphenoidal (TSA) pituitary surgery. Select patients are recovered in the postanesthesia care unit and transferred to a step-down unit for intermediate neurologic care (INCU), with clinicians trained to manage cerebrospinal fluid leak, diabetes insipidus (DI), and other complications. We evaluated all TSA surgeries performed at 1 academic medical center from 7th January, 2017 to 30th March, 2020, collecting patient factors, tumor characteristics, cost variables, and outcomes. The INCU pathway was implemented on 7th January 2018. Pathway patients were compared with nonpathway patients across the study period. Outcomes were assessed using multivariate regression, adjusting for patient and surgical characteristics, including intraoperative cerebrospinal fluid leak, postoperative DI, and tumor dimensions. One hundred eighty-seven patients were identified. Seventy-nine were on the INCU pathway. Mean age was 53.5years. Most patients were male (66%), privately insured (62%), and white (66%). Mean total cost of admission was $27,276. Mean length of stay (LOS) was 3.97days. Use of the INCU pathway was associated with total cost reduction of $6376.33 (P < 0.001, 95% confidence interval [CI]: $3698.21-$9054.45) and LOS reduction by 1.27days (P= 0.008, 95% CI: 0.33-2.20). In-hospital costswere reduced across all domains, including $1964.87 invariable direct labor costs (P < 0.001, 95% CI: $1142.08-$2787.64) and $1206.52 in variable direct supply costs (P < 0.001, 95% CI: $762.54-$1650.51). Pathway patients were discharged earlier despite a higher rate of postoperative DI (25% vs. 11%, P= 0.011), with fewer readmissions (0% vs. 6%, P= 0.021). A streamlined care pathway following TSA surgery can reduce in-hospital costs and LOS without compromising patient outcomes.

Cost Per Relapse Avoided for Ozanimod Versus Other Selected Disease-Modifying Therapies for Relapsing-Remitting Multiple Sclerosis in the United States.

This study assessed the cost-effectiveness of ozanimod compared with commonly used disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS). Annualized relapse rate (ARR) and safety data were obtained from a network meta-analysis (NMA) of clinical trials of RRMS treatments including ozanimod, fingolimod, dimethyl fumarate, teriflunomide, interferon beta-1a, interferon beta-1b, and glatiramer acetate. ARR-related number needed to treat (NNT) relative to placebo and annual total MS-related healthcare costs was used to estimate the incremental annual cost per relapse avoided with ozanimod vs each DMT. ARR and adverse event (AE) data were combined with drug costs and healthcare costs to manage relapses and AEs in order to estimate annual cost savings with ozanimod vs other DMTs, assuming a 1million USD fixed treatment budget. Treatment with ozanimod was associated with lower incremental annual healthcare costs to avoid a relapse, ranging from $843,684 vs interferon beta-1a (30μg; 95% confidence interval [CI] - $1,431,619, - $255,749) to $72,847 (95%CI - $153,444, $7750) vs fingolimod. Compared with all other DMTs, ozanimod was associated with overall healthcare cost savings ranging from $8257 vs interferon beta-1a (30μg) to $2178 vs fingolimod. Compared with oral DMTs, ozanimod was associated with annual cost savings of $6199 withteriflunomide 7mg, $4737 withteriflunomide 14mg, $2178 withfingolimod, and $2793 withdimethyl fumarate. Treatment with ozanimod was associated with substantial reductions in annual drug costs and total MS-related healthcare costs to avoid relapses compared with other DMTs. In the fixed-budget analysis, ozanimod demonstrated a favorable cost-effective profile relative to other DMTs.

Usefulness of Routine Bronchial Aspirate of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration

IntroductionEndobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is commonly used for the study of intrathoracic lymphadenopathy and centrally tumours but no report has discussed the contribution of routine cytological and microbiological BA during the procedure. The aim of the study was to analyse the diagnostic yield of BA during EBUS, and to determine the potential cost reduction. MethodsA prospective study of cytological and microbiological BA collected during EBUS-TBNA was conducted between January 2021 and June 2022. Demographic data, indication, previous BA bronchoscopy or EBUS diagnosis were recorded. The main variable tested was the number of patients in which the result of the BA obtained through EBUS-TBNA determined a change in the diagnosis. ResultsA total of 450 (70.9% male) patients were included. BA cytology showed abnormal cells in 33 (7.3%) of patients, and only 1 case (0.2%) provided a previously unknown diagnosis. All these cases were patients with suspected malignancy. BA microbiological samples found germens in 30 (6.7%) patients but only in 5 cases (1.1%) found microbiological specimens not detected in previous bronchoscopy. None of them received antibiotics and evolved correctly. The potential total cost reduction during the study period at our centre if routine BA was deleted would be 21,937.50€ for routinely combined study. ConclusionsThe low diagnostic yield of cytological and microbiological bronchial aspirate in EBUS-TBNA supports the idea of not performing routine BA. Although the potential for cost savings in caring for an individual patient is modest, many centres routinely perform BA, so the potential savings could be significant.

A demand response method for an active thermal energy storage air-conditioning system using improved transactive control: On-site experiments

Transactive control (TC) and active thermal energy storage (ATES) strategies can effectively achieve a supply–demand balance across energy sources in the power grid. However, past research mainly focused on one of these demand response (DR) strategies, and integrated DR strategies that combine TC and ATES are unavailable. Therefore, to fully utilize both TC and ATES strategies in the DR of air-conditioning systems and thus enhance power grid stability, a comprehensive DR strategy that combines an improved version of TC with ATES (ITC + ATES) was developed for energy storage air-conditioning systems. The ITC + ATES strategy utilizes the automatic feedback regulation effect of the real-time electricity price on the grid side to the air-conditioning users. Then, the system bids the cooling or heating demand on the user side in the power market, thus adjusting the dynamic temperature set-point in real time. The ATES system's automatic energy storage and release process is then regulated accordingly. Thus, this strategy not only allows the air-conditioning system to participate in the power DR, but ensures that the electricity consumption of the air-conditioning system conforms to the power market law and realizes the optimal social value of the power commodity. On-site test experiments of space cooling and heating conditions were conducted on a full-scale intelligent centralized air-conditioning experimental platform with an ATES system to test the effect of this strategy. Comparing the ITC + ATES strategy with the conventional control strategy, ATES strategy, and ITC strategy reveals that the ITC + ATES strategy is most effective in ensuring the thermal comfort of occupants, particularly during the DR period. Moreover, the maximum total electricity consumption reduction rate, the maximum total operating cost reduction rate, the maximum electricity consumption reduction rate during the DR period, and the maximum total operating cost reduction rate during the DR period of the ITC + ATES strategy were 33.20%, 49.69%, 76.14%, and 76.16%, respectively. These results suggest that the ITC + ATES strategy is an efficient and integrated DR approach.

Методические подходы к определению затрат труда при проектировании объектов строительства

The life cycle of buildings includes the labor costs of all categories of management and construction personnel involved in construction from the beginning of preparatory work to the commissioning of the facility. Additionally included here are the costs of developing project documentation. Qualitatively developed project documentation leads to a positive result of construction activity. The price of design works is determined based on the following costs: personnel labor costs, insurance payments, expenses for all types of repairs, material costs, maintenance of buildings and/or rent, taxes and fees. A competent assessment of labor costs and their systematization will help to identify promising segments of labor cost optimization that most significantly affect the reduction of total labor costs.

Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model

In the context of energy transformation, the importance of energy storage devices in regional integrated energy systems (RIESs) is becoming increasingly prominent. To explore the impact of energy storage devices on the design and operation of RIESs, this paper first establishes a bi-level dynamic optimization model with the total system cost as the optimization objective. The optimization model is used to optimize the design of three RIESs with different energy storage devices, including System 1 without an energy storage device, System 2 with a thermal energy storage (TES) device, and System 3 with TES and electrical energy storage (EES) devices. According to the design and operation results, the impact of energy storage devices on the operational performance of RIESs is analyzed. The results show that under the design conditions, energy storage devices can significantly increase the capacity of the combined heating and power units and absorption chillers in System 2 and System 3 and reduce the capacity of the ground source heat pumps and gas boilers; the impact of the TES device on System 3 is more significant. Affected by systems’ configuration, the operating cost, carbon tax, and total cost of System 2 are reduced by 2.9%, 5.5%, and 1.5% compared with System 1, respectively. The EES device can more significantly reduce the operating cost of System 3, with a reduced rate of 5.7% compared with that in System 1. However, the higher equipment cost makes the total cost reduction rate of System 3 less than that of System 1, which is 1.75%. Similar to the design conditions, under the operation conditions, the TES device can effectively reduce the carbon tax, operating cost, and total cost of System 2, while System 3 with an EES device can significantly reduce its operating cost regardless of whether the energy price changes or not. To some extent, this study systematically elucidated the impact of TES and EES devices on the optimal design and operation performance of RIESs and provided a certain reference for the configuration of energy storage devices.

Dynamic tradable credit scheme for multimodal urban networks

A Tradable Credit Scheme (TCS) is a demand management policy aiming for more sustainable travel behavior. The regulator defines the total credit cap and the credit distribution; it also determines the credit charges for each travel alternative at different times of the day, which modifies the perceived users’ costs. The credit price is determined by trading of credits between travelers. Defining the credit scheme at the urban level and estimating its impacts on user travel decisions and the network congestion dynamics is challenging. We propose a framework wherein travelers change their departure times and choose between solo car driving, Public Transportation (PT), and carpooling to complete their trips under a dynamic TCS, meaning the credit charge is time-dependent. A multimodal macroscopic traffic simulator based on a generalized bathtub model captures the congestion dynamics for the different transport modes. Additionally, we consider different values of time, trip lengths, and desired arrival times for the demand profile.The proposed TCS minimizes the total travel cost, (the sum of all travelers’ travel costs) and the carbon emissions by solving an optimization problem through an iterative method, including an inner loop that updates the users’ choices and credit price under the stochastic user equilibrium principle; and an outer loop that updates the credit charge profile. The methodology is implemented and applied to a realistic test case in Lyon (France). The dynamic TCS profiles result in 36% fewer carbon emissions than static TCS for a total travel cost reduction of 19%. Besides, 94% of the travelers benefit from the TCS as their user costs decrease in the case study. The final results are compared with a more advanced simulation framework, which is too computationally expensive to find the optimal TCS. The proposed TCS is effective with refined traffic dynamics representation.

Energy Storage State-of-Charge Market Model

This paper introduces and rationalizes a new model for bidding and clearing energy storage resources in wholesale energy markets. Charge and discharge bids in this model depend on the storage state-of-charge (SoC). In this setting, storage participants submit different bids for each SoC segment. The system operator monitors the storage SoC and updates their bids accordingly in market clearings. Combined with an optimal bidding design algorithm using dynamic programming, our paper shows that the SoC segment market model provides more accurate representations of the opportunity costs of energy storage compared to existing power-based bidding models. The new model also captures the inherent SoC-dependent operational characteristics of energy storage. We benchmark the SoC segment market model against an existing single-segment model in price-taker and price-influencer simulations. The simulation results show that compared to the existing power-based bidding model, the proposed model improves profits by 10-56% in the price-taker case study; the model also improves total system cost reduction from storage by around 5%, and helps reduce price volatilities in the price-influencer case study.

Abstract P6-08-01: A cost-consequence analysis of pertuzumab in the neoadjuvant treatment of high-risk HER2+ Early-Stage Breast Cancer (EBC): health-economic considerations for drug availability in Italy

Abstract Introduction: Neoadjuvant pertuzumab+trastuzumab+chemotherapy (TPC) combo is a well established treatment for HER2+ high-risk (EBC) as recommended by International and National guidelines. However, notwithstanding EMA approval, in some European countries (i.e Italy and France) pertuzumab drug-access is prevented by the NHS decision not to reimburse the drug in a value-driven sustainability balance. This study aims to estimate the cost and consequences of TPC vs. the same combo w/o pertuzumab (TC) in the neaodjuvant treatment of high-risk HER2+ eBC to better understand the value of TPC regimen. Methods: With a Markov model, we simulated the costs and consequences associated to TPC or TC neoadjuvant treatments, using 5 years time horizon and Italian Lombardy region Health System point of view. The model includes nine health states: Neoadjuvant treatment; Surgery; Invasive disease-free Survival (IDFS) with pathological complete response (pCR), IDFS with residual disease (RD), non-metastatic recurrence, remission, first-line treatment and subsequent-lines for metastatic cancer, and death. Transition probabilities and utilities were derived from relevant clinical trials and literature. For each neoadjuvant treatment, the model estimates: direct (drug, administration, hospitalization, disease management), indirect (patients’ loss of productivity), total costs and different outcomes, as cumulative incidence of metastatic recurrence, days of work lost, days with activity impairment, IDFS life years, and quality adjusted life years (QALY). Costs and outcomes were estimated per 100-treated patients. An alternative scenario analysis with a 10-year time horizon and a deterministic sensitivity analysis was performed to assess the impact of model time horizon and parameters value. Results: The estimated costs and outcomes for TPC and TC are reported in Table 1. TPC produces a total direct cost reduction of €75,630 per 100-treated patients, a small increase of TPC neoadjuvant treatment costs (+4.8%) is offset by the lower cost of metastatic treatment and management (-20.4%). Considering also the indirect costs, TPC is associated to a cost reduction of €124,956 per 100-treated patients. The cost saving is associated to a reduction of 5-year cumulative incidence metastatic recurrence (8.32% vs 10.42%, -20.14%), a reduction of days of work loss (-548 days) and days with activity impairment (-283 days) and a 10.5 QALY gained per 100-treated patients. Using a 10-year time horizon, the value of TPC compared to TC increases. Probabilities of pCR with TPC and TC were the parameter with the higher impact on model results. Conclusion: Use of TC instead of TPC in high-risk HER2+ EBC derives a marginal savings (4.8%) according to the first year of our cost-consequence analysis. However, this negligible savings comes with the need for a heavily and long-lasting adjuvant cytotoxic therapy escalation because of a lower clinical activity of TC vs TPC. Moreover, according to medium-term cost-consequence analysis (5 years) the early negligible savings is overwhelmed by the subsequent increase in costs for the patients’ management, because of the lower clinical efficacy of TC vs. TPC. In Italy, the lack of pertuzumab in the neoadjuvant setting of high-risk HER2+ eBC is questionable; our results support the opportunity to reconsider the pertuzumab availability in Italy and reduce inequalities within Europe. Cost and consequences of neoadjuvant treatments for high-risk HER2-Positive Early-Stage Breast Cancer: trastuzuamb+pertuzumab+chemotheraphy (TPC) vs trastuzumab+chemotheraphy (TC) IDFS, Invasive disease-free Survival; QALY, quality adjusted life years. Citation Format: Alberto Zambelli, Marina Elena Cazzaniga, Nicla La Verde, Elisabetta Munzone, Ippazio Cosimo Antonazzo, Lorenzo Giovanni Mantovani, Anna Mancuso, Daniele G. Generali, Paolo Angelo Cortesi. A cost-consequence analysis of pertuzumab in the neoadjuvant treatment of high-risk HER2+ Early-Stage Breast Cancer (EBC): health-economic considerations for drug availability in Italy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-08-01.

Distribution systems cost reduction based on switches upgrades: A stochastic approach

Power Distribution Systems are considered critical infrastructures, and their continuity to deliver and maintain electricity to the final customer is of extreme importance. The Optimal Switch Allocation address this topic by changing the network configuration to improve reliability, while minimizing power loss and cost. On previous researches economic constraints and dynamic failure models were considered, but neither the uncertainty in the environmental parameters nor stochastic models are applied. Additionally, the possibility to upgrade existing switches are often not considered. This work applies a Genetic Algorithm, coupled with Monte Carlo Simulation, as well as a Bayesian Inference Model, to address the probability of upgrading existing switches in a power distribution system. Economical constraints, fragility curves, variable load demand and weather scenarios are simulated. The Bayesian inference allows the model to be used as a support decision tool, when dealing with the possibility of upgrading switches in the network, especially in face of uncertainties in the distribution system. Results show that the upgrade of existing switches can achieve total cost reduction, but the uncertainties presented in the model can change the probability of upgrading an individual switch, thus sustaining the importance of the proposed approach. • A stochastic approach to deal with the upgrade of switches in a distribution system. • Monte Carlo method and genetic algorithm are used to simulate failure scenarios. • A Bayesian hierarchical approach fit the data into a final statistical model. • The final solution is the posterior probability of each switch upgrade. • The method quantifies the importance of each switch, enabling decision support.

Process control: simply a matter of efficiency or of survival and costs? A single-centre quality improvement project in living donor renal transplant

BackgroundRising incidence and prevalence of end-stage renal disease is a worldwide concern for sustainability of healthcare systems and societies. Living donor renal transplant [LDRT] provides highest health achievements and cost containment than any alternative form of renal replacement therapy. Nonetheless, about 25% of potential LDRTs are missed for causes directly related with inadequate timing in donor assessment. Our quality improvement (QI) project implement process control tools and strategy aiming at reducing total evaluation time for donor candidates and minimizing dialysis exposure for intended recipients, which are the two main determinants of clinical outcomes and costs.MethodsThe study includes patients who underwent donor nephrectomy between January 1, 2017 and December 31, 2021. Six Sigma DMAIC approach was adopted to assess Base Case performance (Jan2017-Jun2019) and to design and implement our QI project. Study of current state analysis focused on distribution of time intervals within the assessment process, analysis of roles and impacts of involved healthcare providers and identification of targets of improvement. Improved Scenario (Jul2019-Dec2021) was assessed in terms of total lead time reduction, total pre-transplantation dialysis exposure and costs reduction, and increase in pre-emptive transplantations. The study was reported following SQUIRE 2.0 Guidelines for QI projects.ResultsStudy population includes 63 patients, 37 in Base Case and 26 in Improved Scenario. Total lead time reduced from a median of 293 to 166 days and this in turn reduced pre-transplantation dialysis exposure and costs by 45%. Rate of potential pre-emptive donors’ loss changes from 44% to 27%.ConclusionsLean methodology is an effective tool to improve quality and efficiency of healthcare processes, in the interest of patients, healthcare professionals and payers.

Selection of eco-efficient downstream separation configuration for isopropanol–butanol–ethanol purification process

Nowadays, renewable and cleaner biofuel requirements increase with the increase in economic, environmental, and social concerns. Biobutanol is a preferable alternative fuel due to its outstanding properties compared to other alcohol-based biofuels. Two alternative downstream process configurations are designed in this study to obtain high-purity alcohol products from isopropanol–butanol–ethanol (IBE) fermentation broth with the same feed flowrate and compositions. In process configuration 1, the excess amount of water in the fermentation broth is mainly taken away using a preconcentration column. In process configuration 2, an extractor-extractive distillation hybrid system is used to remove the excess amount of water from the system. The results show that the first configuration is superior with a 62% reduction in total annual cost (TAC). Besides economic superiority, process configuration 1 is also quantitatively better than process configuration 2 in terms of gas emissions and energy demand to purify butanol. As a result, process configuration 1 is found as an eco-efficient downstream separation sequence for IBE purification process.

Optimizing the operation strategy of a combined cooling, heating and power system based on energy storage technology

Energy storage technology is the key to achieving a carbon emission policy. The purpose of the paper is to improve the overall performance of the combined cooling, heating and power-ground source heat pump (CCHP-GSHP) system by the battery. A new operation strategy (the two-point operation) is proposed by controlling the power generation unit work. The power generation unit has two operation modes of non-operation and rated efficiency operation by the storage electricity battery. The new operation strategy is compared with the traditional CCHP-GSHP that without a battery. The optimization goals include the primary energy saving ratio, the reduction ratio of carbon dioxide emissions, and the annual total cost saving ratio. The independent GSHP system is used as a reference system. Multipopulation genetic algorithms are selected to achieve the problem of optimization. A hotel building is selected for a case study. The optimal configuration of the coupling system is computed following the electric load strategy. Finally, the results show that the CCHP-GSHP system has a better performance under the new operation strategy compared with the traditional CCHP-GSHP (the primary energy saving ratio increases by 5.5%; the annual carbon dioxide emission reduction ratio increases by 1%; the annual total cost reduction ratio increases by 5.1%). This paper provides reference and suggestions for the integration and operation strategy of CCHP-GSHP in the future.

Impact of an optimized surveillance protocol based on the European Association of Urology substratification on surveillance costs in patients with primary high-risk non-muscle-invasive bladder cancer.

The optimal frequency and duration of surveillance in patients with high-risk non-muscle-invasive bladder cancer (NMIBC) remain unclear. The aim of the present study is to develop an optimal surveillance protocol based on the European Association of Urology (EAU) substratification in order to improve surveillance costs after transurethral resection of bladder tumor (TURBT) in patients with primary high-risk NMIBC. We retrospectively evaluated 428 patients with primary high-risk NMIBC who underwent TURBT from November 1993 to April 2019. Patients were substratified into the highest-risk and high-risk without highest-risk groups based on the EAU guidelines. An optimized surveillance protocol that enhances cost-effectiveness was then developed using real incidences of recurrence after TURBT. A recurrence detection rate ([number of patients with recurrence / number of patients with surveillance] × 100) of ≥ 1% during a certain period indicated that routine surveillance was necessary in this period. The 10-year total surveillance cost was compared between the EAU guidelines-based protocol and the optimized surveillance protocol developed herein. Among the 428 patients with primary high-risk NMIBC, 97 (23%) were substratified into the highest-risk group. Patients in the highest-risk group had a significantly shorter recurrence-free survival than those in the high-risk without highest-risk group. The optimized surveillance protocol promoted a 40% reduction ($394,990) in the 10-year total surveillance cost compared to the EAU guidelines-based surveillance protocol. The optimized surveillance protocol based on the EAU substratification could potentially reduce over investigation during follow-up and improve surveillance costs after TURBT in patients with primary high-risk NMIBC.

Evaluating a Care Management Program for Dual-Eligible Beneficiaries: Evidence from Rhode Island.

As health systems attempt to contain utilization and costs, care management programs are proliferating. However, there are mixed findings on their impact. In 2018, Rhode Island initiated a care management program for dually eligible Medicare and Medicaid beneficiaries at high risk of hospitalization or institutionalization. The objective of this study is to evaluate the association between health care utilization and costs and care management for dual-eligible participants (n = 169). The authors employed an interrupted time series analysis of administrative claims data using the Rhode Island All Payer Claims Database, which includes data from all major payers in the state, for 11 quarters (January 1, 2017 until September 1, 2019). On average, participants were younger (46.2% were 19-64 years of age vs. 41.9% of non-participants), female (71% vs. 62.6% of non-participants), and had a higher comorbidity burden (more commonly had anemia, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease, depression, diabetes, heart failure, hyperlipidemia, hypertension, ischemic heart disease, and stroke). Participation was associated with significantly fewer hospital admissions (118 fewer admissions per 1000 admissions per quarter; 95% confidence interval [CI] -11 to -22), and a reduction in Medicaid ($1841 less spent per quarter, 95% CI -2407 to -1275) and total ($2570 less spent per quarter; 95% CI -$4645 to -$495) costs. Participation was not significantly associated with a change in Emergency Department (ED) visits, preventable ED visits, Skilled Nursing Facility stays, or Medicare costs. These results suggest that targeted care management programs may provide dual-eligible beneficiaries with needed services while diverting inefficient health care utilization.

Optimization of the cutting process integrated to the lot sizing in multi-plant paper production industries

Many industrial production and cutting processes have costs associated with setup, production of objects, waste of material in the cutting process, inventory, and transport which can vary according to each plant’s location (factory). The production lot sizing, the planning of cuts, and the transport between plants of a company are interconnected problems that, if optimized in an integrated way, can lead to reduction in total costs. In the literature, such problems are widely addressed independently. Recently, the integrated lot sizing and cutting stock problem has been the subject of several studies. However, none have addressed the integrated problem, which also considers multiple plants. This paper presents an integer linear programming formulation for the integrated lot sizing and cutting stock problem with multiple plants and a solution methodology. The formulation is inspired by a practical situation in the paper-making industry. The developed solution methodology consists of a column generation method and a relax-and-fix with a feasibility heuristic. Computational tests were performed to evaluate the performance of the proposed approach and the solution methodology. The proposed approach presented lower total costs, demonstrating the potential for reducing all considered costs. The applied solution methodology showed satisfactory performance for all the studied instances.

Design of cost-based sizing and energy management framework for standalone microgrid using reinforcement learning

The standalone photovoltaic-battery energy storage (PV-BES) microgrid has gained substantial interest recently due to its ability to provide uninterrupted power to consumers in remote areas. In such microgrids, components must be precisely sized and energy must be supplied most cost-effectively at all times. This paper presents a cost-based framework for determining the optimal size and energy management of standalone microgrids using reinforcement learning. Fundamental to this framework is two essential phases; the first is finding the best size of PV-BES using an analytical and economic sizing (AES) model based on minimum levelized cost of energy (LCOE). The AES phase is then followed by optimizing the energy management strategy (EMS) of the microgrid using reinforcement learning to provide optimum cost savings. The novelty in this work can be outlined as optimizing both the size and EMS of a standalone PV-BES microgrid using the AES model and Q-learning in an integrated framework. This can lead to improved performance demonstrated in reducing the LCOE, decreasing diesel generator working hours, and enhancing PV utilization and system efficiency. The results show an advantageous reduction in total cost while meeting load requirements. Additionally, the proposed framework is evaluated using several metrics to measure the impact of employing Q-learning against the AES-finite automata model. For instance, a decrease of 22% in diesel generator working hours and an increase of 6% in PV utilization while a reduction of 11% in the LCOE is accomplished. On the other hand, the proposed framework is examined against two rule-based EMSs, load following strategy (LFS) and cycle charging strategy (CCS), and outperforms these two EMSs in terms of LCOE, PV utilization, and system efficiency.

Optimizing the location selection of urban consolidation centers with sustainability considerations in the city of Bordeaux

The delivery of parcels in city centers is nowadays a topical issue and a major challenge for the local authorities. In this paper, we tackle the parcels distribution network in the city of Bordeaux. This city is at the very beginning of the process of moving from direct deliveries towards city center, to a more rational organization based on joint deliveries. We focus on the potential contributions of a two-tier distribution system made up of warehouses, proximity logistics spaces and intermediate depots so-called urban consolidation centers (UCCs). We seek to optimize the costs of the distribution network (i.e. transport and UCCs) and the selection of UCCs, while assessing the impact in terms of sustainable development by measuring CO2 emissions. We analyze and compare different scenarios using different deliveries' variants (with or without UCCs), different total UCCs capacities and different truck speeds. The findings demonstrate the benefits of using UCCs for city center distribution. The reductions in total cost and CO2 are most significant when the size of the UCCs is balanced with the total deliveries demands.