Unit Cost Research Articles

Pricing Strategies in Dual-channel Supply Chain with Discount and In-sales Service Consideration

Driven by increasing internet usage, Indonesia is experiencing a significant rise in e-commerce activities, with transactions projected to grow from 66 million to 99 million by 2029. This growth necessitates a hybrid approach combining online and offline sales channels to maximize market coverage. However, this dual-channel strategy poses challenges in pricing, as customer preferences heavily influence purchasing decisions. This study analyzes pricing strategies within a dual-channel supply chain (DCSC). It examines two main scenarios, centralized and decentralized systems, to determine optimal pricing strategies considering in-sales service and discount. The decentralized system employs a Stackelberg game model, where the manufacturer sets prices first, followed by the retailer. A clothing company is used as a practical case study to apply these mathematical formulations. The study highlights how parameter variations such as customer preferences, service, and unit costs influence price. Notably, the decentralized system often results in higher profitability than the centralized approach under specific conditions. Sensitivity analysis further reveals that while some parameters remain stable, customer preferences significantly affect pricing decisions. A preference for online shopping tends to favor a centralized strategy, indicating that coordinated pricing can mitigate channel cannibalization risks. The study underscores the complex interplay between pricing strategies, discounts, and in-sales services in dual-channel supply chains

Use of individualized starting dose and niraparib hematologic adverse event management costs in ovarian cancer.

Aim: To understand the impact of the niraparib individualized starting dose (ISD), compared with fixed starting dose (FSD), on the cost of hematologic adverse event (AE) management from a US payer perspective. Methods: The frequencies of grade ≥3 hematologic AEs that occurred in >1% of patients treated with niraparib were obtained from the primary analysis results of the phase III PRIMA/ENGOT-OV26/GOG-3012 trial. US unit costs for each grade ≥3 AE in the base case were obtained from the 2017 Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project database; unit costs were adjusted to 2020 US dollars. AE management costs per patient were calculated by multiplying AE unit cost by the frequency of each AE by niraparib starting dose. Because AEs were assumed to occur independently of one another, costs were added to derive the total cost. Results: For niraparib, the estimated AE management cost per patient was lower for the ISD than the FSD for all hematologic AEs (FSD vs ISD: thrombocytopenia, $4701.87 vs $1921.89; anemia, $2784.00 vs $1760.59; platelet count decreased, $2103.47 vs $922.51; neutropenia, $2112.50 vs $1369.56; neutrophil count decreased, $1285.87 vs $770.38). The total mean calculated AE management cost per patient was $12,987.71 with the FSD and $6744.93 with the ISD. Conclusion: For niraparib, the cost of managing hematologic AEs in the US was reduced by almost half with the ISD compared with the FSD. The cost reduction and improvements in safety associated with the niraparib ISD support its use in clinical practice.

Cost consequences analysis of early vocational rehabilitation compared with usual care for stroke survivors.

To compare costs and consequences of Early Stroke Specialist Vocational Rehabilitation (ESSVR) with usual care in working age, stroke survivors over 12 months. An economic evaluation nested within the pragmatic, multi-centre, randomised, controlled RETurn to work After stroKE (RETAKE) study. Twenty-one English and Welsh National Health Service (NHS) hospital-based stroke units. A UK NHS and Personal Social Services perspective was taken in the base-case and a wider perspective (participant, family, employer and other public services) in a secondary analysis. A total of 583 stroke survivors age ≥18 years (mean 54.0 years, 69% male). Participants were randomised to ESSVR, an early, individually tailored (in content, dose, intensity and duration) intervention, plus usual care or usual care alone. Disease-specific resource-use data and EQ-5D-5L (health-related quality of life) collected at baseline, 3, 6 and 12 months. Resource-use items were valued using unit costs in UK£ 2021/22. EQ-5D-5L was used to estimate Quality-adjusted life-years (QALYs). If ESSVR was found effective, an incremental cost-utility analysis was planned, otherwise a cost-consequence analysis. The clinical study found no evidence of a between-group difference in the proportion of participants returning to work at 12 months. This, and the level of missing data, means a cost-consequence analysis is reported. Using imputed data, ESSVR plus usual care is estimated to be more expensive with slightly higher QALYs compared with usual care. Early Stroke Specialist Vocational Rehabilitation is unlikely to be considered cost-effective over 12 months, which fits with the clinical finding of no between-group difference in return-to-work rates post-stroke. The ISRCTN registry: ISRCTN12464275 https://doi.org/10.1186/ISRCTN12464275.

Cost-effectiveness of the Healthy Options group psychosocial intervention for perinatal women living with HIV and depression in Tanzania

Healthy Options is a psychosocial support group intervention facilitated by community-based health workers (CBHWs) to reduce symptoms of depression in perinatal women living with HIV in Tanzania. The objective of this study was to determine incremental cost-effectiveness of Healthy Options intervention in comparison to enhanced usual care for depression (EUDC) intervention. This study is a cost-effectiveness analysis of Healthy Options intervention. The primary outcome for the Healthy Options intervention was level of depressive symptoms. We estimated disability adjusted life years (DALYs) by considering life years lived with disability and years of life lost due to premature mortality resulting from depression. This study applied ingredients approach to cost all resources used in the intervention. We estimated total cost, unit cost, and incremental cost-effectiveness ratio (ICER) from a health care provider perspective. We used 3-year time horizon, univariate sensitivity analysis, and adjusted costs to 2017 value. Healthy Options intervention demonstrated effectiveness in reducing depressive symptoms among pregnant women with HIV in Tanzania. Total cost of Healthy Options was $319,729. Cost per woman treated was $883. ICER at 6 weeks postpartum is $89,699 per mean decrease in depression score and $310,030 per mean decrease in depression score at 9 months. ICER per DALY averted is $24,754 at 6 months and $4,169 at 9 months. Benefits of Healthy Options are sustained through 9 months postpartum. Healthy Options is nevertheless not cost-effective because ICER is above cost-effectiveness threshold. However, since mental health care is scarce in Tanzania, working with CBHWs is likely to offer effective intervention for maternal depression among women with HIV and it can be a less costly alternative to formal mental health professionals.

Comprehensive analysis and optimization of an efficient combined power and refrigeration cycle suitable for recovering low/mid-grade waste flue gas

To effectively recover low/mid-grade waste flue gas and provide larger refrigeration capacity, an efficient combined power/refrigeration cycle only using ammonia water as the working fluid is proposed and studied. Parametric analysis is conducted from the perspectives of thermodynamics, exergoeconomics, and environment, the results demonstrate that the low/mid-grade waste flue gas within a wide range of temperature can be sufficiently recovered by the proposed cycle, and the cycle performance is significantly affected by the turbine inlet pressure, work/basic concentration and separation temperature of work solution. Based on the heat source condition of 300°C/10 kg·s-1, the results of single-objective optimization show that the maximum effective exergy efficiency, reduction amount of CO2 emission and waste heat recovery ratio that can be achieved are 0.5989, 262 kg/h and 0.97 respectively, and the achievable minimum unit cost of produced exergy is 8.432 $·GJ-1. Besides, the multi-objective optimization indicates that the optimal comprehensive thermodynamic efficiency is 0.5458 with net power output of 372.5 kW and larger refrigeration capacity of 545.7 kW, and the associated effective exergy efficiency, unit cost of produced exergy, reduction amount of CO2 emission and waste heat recovery ratio are 0.5701, 9.187 $/GJ, 258.3 kg/h and 0.9574, respectively.

Train assignment and handling capacity arrangement in multi-yard railway container terminals: An enhanced adaptive large neighborhood search heuristic approach

Expanding terminal scale and constructing multiple railway handling yards have become popular strategies for leading railway container terminals globally to cope with the ever-increasing handling volume. Although such an approach greatly enhances the terminal’s productivity, it also intensifies handling operations and introduces additional inter-yard interactions, complicating terminal management. To address these challenges, this paper investigates an integrated optimization approach for multi-yard railway container terminals, which feature both rail-road and rail-rail container transshipment operations. The train assignment plan for each yard and the handling capacity arrangement for each train are jointly optimized while considering inter-yard container transits, workload allocation for yards, and safety requirements in train shunting. This problem is formulated as a nonlinear programming model, with the objective to minimize operational delay and service time for each incoming train, and to minimize workload differences and container transit volume among yards. To efficiently solve this problem, this research develops an enhanced adaptive large neighborhood search (EALNS) heuristic, which includes several customized operators and feasibility repair methods, and is further enhanced with a local search method and backtracking mechanism compared to the standard ALNS framework. Computational experiments with different data scales and problem settings demonstrate the superiority of the EALNS in terms of solution quality and stability compared with three other solution methods. Additionally, practical insights for terminal operations are drawn through detailed analysis of different infrastructure configurations, transshipment train characteristics, and unit cost settings.

A thermo-economic comparison on new and conventional alternatives of pressurization of CO2 in CCS systems

The final stage of carbon capture and storage processes involves the pressurization of CO2 by a suitable method which is conventionally carried out through a series of compressors with intercoolers in between them. In the present study, the idea of liquefying the captured CO2 is considered. Four different systems for the liquefaction process are evaluated and compared Thermo-economically with the benchmark system of direct carbon dioxide compression. The results indicate that the EPLS system outperforms the others, with a product cost 5.89% lower than the benchmark system. Evaluations show that most of the costs are imposed by the initial compression stage in each system. A detailed investigation of the sensitivity analysis shows that the benchmark and claude systems have the largest dependency on pressure ratio and intercooling temperature, respectively. Additionally evaluation of the economic parameters indicates that the changes in unit cost of power have the most effect on the benchmark system while the interest rate affects the results of claude and DEBARS more than other options. Detailed evaluations reveal that the EPLS layout has the advantage of less dependency on the changes of operating parameters and on the other hand, the cost of input heat, the maintenance factor, and the generator and evaporator temperatures make a high difference in the final product cost of the DEBARS. Finally, the effect of pressure drops in heat exchangers is investigated and results reveal that the consideration of pressure drops leads to power penalties ranging from 0.97 to 8.52 $/hr in different systems.

Flexible and adjustable resource backup capacity planning method for port areas with a high percentage of new energy access

In view of the problem of insufficient flexibility in grid regulation caused by the large-scale integration of new energy sources, this paper proposes an interactive regulation method for flexible resources to participate in wind and solar energy consumption and establishes a two-layer optimization model of planning and operation. The planning layer considers the planned capacity of flexible adjustable resources, and the operation layer comprehensively considers economic costs. Flexible resources are coordinated and regulated to achieve multi-objective optimization using a hybrid swarm migration algorithm based on indicators such as the operating costs of each standby unit and the cost of standby resources. The optimization results are then fed back to the planning layer to obtain the optimal regulation scheme. Meanwhile, this paper expands the source of backup resources to include the source-load-storage. It proposes a strategy for coordinating the participation of diversified resources from the source-load-storage in the backup capacity planning. Finally, a simulation analysis is carried out based on the actual power grid of a port. The results show that the reasonable allocation of diversified flexible resources can improve the economy of the power grid, the wind and solar energy consumption capacity, the flexibility of regulation, and the reliable operation capacity, which verifies the rationality and effectiveness of the proposed method.

Costs during the first year after stroke by degree of functional disability: A societal perspective.

The aim of this study was to estimate societal costs during the first year after stroke by degree of functional disability. Descriptive study of the cumulative costs incurred during 1-year follow-up of a cohort of patients with stroke in Catalonia (Spain) participating in a multicentre, population-based, cluster-randomised trial (RACECAT). Patients were recruited between September 2017 and January 2019. Costs were collected for each patient from stroke onset to 1-year follow-up through hospital accounting records, electronic healthcare records and structured telephone-based interviews at 6 and 12-months follow-up. Disability was assessed using the 90-day modified Rankin Scale (mRS). Healthcare, community care, and patient/family costs were included. We used complete data from 567 eligible participants. Cost data were analysed using generalised linear models (GLMs) with gamma distributions and log link functions. For variables with >10% zero values, two-part models were applied. We performed sensitivity analyses modifying unit costs for patient/family costs. Of the 567 patients included, 53% had ischaemic large vessel oclusion (LVO) stroke, 24% intracranial haemorrhage and 23% ischaemic non-LVO stroke. Mean cost per patient during the first year after stroke was €29,673 ± 28,632, and increased with degree of disability (mRS 0-2: €18,568 ± 12,244; mRS 3: €38,214 ± 28,172; mRS 4-5: €52,859 ± 36,383). Healthcare costs represented the highest proportion of total costs (63%; €18,724/patient) across all disability levels, with index hospitalisation being the highest (€12,319 ± 17,675); however, community care and patient/family costs represented over 40% of total cost in patients with higher disability levels. Our results are in line with other studies; the costs during the first year after stroke are high and increase with disability. These results are valuable for calculating the cost of severe stroke cases.

A micro-costing study of mass-spectrometry based quantitative proteomics testing applied to the diagnostic pipeline of mitochondrial and other rare disorders

BackgroundMass spectrometry-based quantitative proteomics has a demonstrated utility in increasing the diagnostic yield of mitochondrial disorders (MDs) and other rare diseases. However, for this technology to be widely adopted in routine clinical practice, it is crucial to accurately estimate delivery costs. Resource use and unit costs required to undertake a proteomics test were measured and categorized into consumables, equipment, and labor. Unit costs were aggregated to obtain a total cost per patient, reported in 2023 Australian dollars (AUD). Probabilistic and deterministic sensitivity analysis were conducted to evaluate parameter uncertainty and identify key cost drivers.ResultsThe mean cost of a proteomics test was $897 (US$ 607) per patient (95% CI: $734-$1,111). Labor comprised 53% of the total costs. At $342 (US$ 228) per patient, liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was the most expensive non-salary component. An integrated analysis pipeline where all the standard analysis are performed automatically, as well as discounts or subsidized LC-MS/MS equipment or consumables can lower the cost per test.ConclusionsProteomics testing provide a lower-cost option and wider application compared to respiratory chain enzymology for mitochondrial disorders and potentially other functional assays in Australia. Our analysis suggests that streamlining and automating workflows can reduce labor costs. Using PBMC samples may be a cheaper and more efficient alternative to generating fibroblasts, although their use has not been extensively tested yet. Use of fibroblasts could potentially lower costs when fibroblasts are already available by avoiding the expense of isolating PBMCs. A joint evaluation of the health and economic implications of proteomics is now needed to support its introduction to routine clinical care.

A resilience-oriented approach to integrated energy management systems: Addressing energy conversion unit unavailability and cost efficiency

As integrated energy systems become increasingly complex, their vulnerability to energy conversion units unavailability poses a considerable threat to system resilience and cost efficiency. This research is motivated by the need to address the growing threat of energy conversion unit unavailability and its significant impact on both system performance and operational costs. The development of a comprehensive vulnerability assessment framework, coupled with the integration of machine learning techniques, is hypothesized to significantly enhance the resilience and cost-efficiency of integrated energy management systems when faced with various unavailability scenarios. A novel methodology is introduced to enhance integrated energy management systems, focusing on the critical role of diverse energy conversion units. The methodology includes a new vulnerability index to quantify the impact of energy conversion unit unavailability on system performance, alongside an energy conversion unavailability attack model from the malicious actor perspective. Results indicate that under worst-case energy conversion unavailability attack scenarios, integrated energy systems operational costs can increase by up to 26.19%. The proposed solution, incorporating a Deep Q-Network into the integrated energy management system, achieves an 85.24% F1-score and a 96.68% reduction in additional costs associated with energy conversion unavailability attacks. This research demonstrates the varied impacts of different energy conversion units on integrated energy systems and proposes an enhanced integrated energy management system framework that improves system resilience and cost efficiency.

Costing curative outpatient care for the poorest in Burkina Faso: informing universal health coverage and leaving no one behind

IntroductionThe poorest in Burkina Faso face numerous barriers to healthcare access, including financial and geographic obstacles, as well as a high burden of chronic conditions and multimorbidity. This study estimates the average cost of providing curative outpatient consultations at first-level healthcare facilities to the poorest in Burkina Faso. It also estimates the budgetary impact of scaling up free access to these services nationwide. The findings provide essential evidence on cost structures to inform decision-makers in developing policies aimed at achieving universal health coverage and ensuring that no one is left behind.MethodsWe conducted a micro-costing study to estimate the economic costs of providing curative outpatient healthcare services to the poorest at first-level healthcare facilities, considering a health system perspective. We measured the consumption of capital costs (building and equipment) using survey data from 32 primary health facilities and recurrent costs (drugs and consumables) from medical records of 1380 poor patients in Diébougou district. These individuals were targeted and exempted from user fees through a community-based targeting approach. We obtained unit costs from official price lists, pharmacy registries, and expert interviews. We calculated the national budget for providing curative care services to the exempted poorest based on the average cost per first-level consultation.ResultsThe estimated capital and recurrent costs of providing curative care services ranged between USD 0.59 - USD 0.61 and USD 2.58 - USD 5.00, respectively. The total cost ranged between USD 3.17 - USD 5.61 per first-level consultation. Providing curative care to the bottom 20% of the population, assuming 0.25 healthcare contacts per person per year, would result in an annual expense ranging from USD 2.77 M to USD 5.38 M (0.74-1.43% of the healthcare budget in 2019). With 2 healthcare contacts per person per year, costs increase to USD 22.19 M to USD 43.05 M (5.91-11.45% of the healthcare budget).ConclusionThe results can inform policies aimed at expanding access to curative care for the poorest in Burkina Faso, contributing to the goals of universal health coverage and leaving no one behind. Further research is needed to enhance cost estimation and budgeting for higher-level care in the country.

Sensitivity analysis of an imperfect maintenance policy for Proton-exchange membrane fuel cell based on geometric a semi-Markov model

This paper proposes a maintenance model for a Proton-Exchanged Membrane Fuel Cells system. Two types of failures are considered: non repairable internal failures and possibly repairable external failures. The maintenance involves replacing one or more cells. Therefore the maintenance can be perfect or imperfect. Moreover after each repair, the maintenance operator improves and the down time due to maintenance is reduced. A semi-Markov process is proposed to model the system’s lifetime. In this framework, the reliability measures and the remaining useful lifetime are derived. The long run average maintenance cost is studied. A sensitivity analysis of model parameters and maintenance unit costs is performed and a maintenance optimization strategy is proposed.

Unit costs of health services provided at hospitals and health centres in two provinces of Zambia

Unit costs of health services provided at hospitals and health centres in two provinces of Zambia

Advancing social value analysis: challenges and opportunities to understanding social outcomes in the United States and in the United Kingdom

This paper addresses the comparability and related scalability constraint of Maier et al. (VOLUNTAS 26: 1805–1830, 2015) of social impact measurement by deploying experimental mapping of the Sustainable Development Goals (SDGs) target indicators onto social return on investment (SROI) data proxies. Datasets on the unit cost database model hosted by the Greater Manchester Authority are derived for the UK and for the US. Discreet differences in data terminology between financial proxies in the UK and in the USA are translated with a contextual approach for data optimization. The resultant mapped datasets of financial proxies offer early evidence in support of the scalability of SROI. This is valuable for local measurement of progress towards the global 2030 Agenda for Sustainable Development. This research finds that there are comparatively wide differences in sufficient data both within and across the UK and the US datasets. Yet, mapped data counts show sufficient cross-geographic financial proxy overlaps, pointing to the viability of data collection with financial proxy sampling and mapping both for the better understanding of place-based social value creation and for comparative localised social value contribution. This paper concludes that initial mapping of data onto the SDG target indicators improves the comparability constraint of SROI.

Evaluating the environmental and financial performance of additive manufacturing at scale in the consumer goods industry

As corporate sustainability commitments and environmental regulations intensify, additive manufacturing users must balance the technology's maturing economic value with its application- and process-dependent environmental impact. With limited methods to navigate this multi-dimensional variability at scale, additive manufacturing stakeholders face challenges when making growth and investment decisions. To bridge this gap, this study applies system modeling methodologies to a case study of an additive manufacturing service unit in the sporting goods industry aiming to improve its product portfolio's economic and environmental impacts and scale its capabilities. A tradespace model compares the value of additive manufacturing to injection molding across product characteristics and life cycle decisions, and a flexible design analysis evaluates additive manufacturing scaling strategies, considering market and technology uncertainties. The tradespace analysis reveals that additive manufacturing reduces product environmental footprint by 95 % and unit cost by 93 % for 1-to-20-part production volumes compared to injection molding, while injection molding lowers environmental footprint by 72 % and unit cost by 56 % for 100-to-50,000-part production volumes compared to additive manufacturing. This analysis also suggests that additive manufacturing's economic and environmental value increases when located in geographies with low-carbon footprint energy and when manufacturing very low production quantities or small parts that maximize build capacity. The flexible design analysis indicates that expanding internal production capacity to a larger facility with renewable power, once higher demand is confirmed, can reduce part environmental footprint by up to 49 % and increase Net Present Value by more than 600 % compared to maintaining current operations that leverage external service bureaus. The results demonstrate the potential of these system modeling methodologies in integrating financial and environmental impact assessments at the company level for strategic scaling decisions. Future model developments are recommended to incorporate additive manufacturing's unique design impacts on the product life cycle, more nuance in the impact analyses, and the social component of the technology's sustainability.

Optimal allocation of electric vehicle charging stations and distributed generation in radial distribution networks

The widespread spread of electric vehicles requires the establishment of charging stations (EVCSs), and this is considered a large load on the network. This gives priority to distributing the stations in a way that reduces the load on the network, and in parallel, re-planning the network and supplying it with the necessary energy to maintain energy efficiency and power quality. Total energy loss minimization, voltage deviation minimization, and voltage stability index improvement are the considered power quality indices in the multi-objective function. Vehicle to grid (V2G) feature, distributed generation units (DG), and capacitor banks are used for improving system performance, by injecting the required active and reactive power. In addition, the initial and running costs of V2G, DG units, and capacitor banks are considered in the multi-objective function. The optimal sizing and allocation of charging stations, V2G, DG units, and capacitor banks are performed using a proposed Self-Adaptive Multi-Population Elitist JAYA (SAMPE-JAYA) algorithm and checked using the genetic algorithm (GA). The proposed algorithm is tested using various scenarios, two standard IEEE test systems. To emphasize the effectiveness and applicability of the proposed algorithm, it is applied on a real-world distribution system. To accommodate the optimal allocation of EVCS, which constitute 80.7 % and 78.9 % of the base active load for the IEEE 33 and 69 bus systems, respectively. Integrating DG amounting to 17.35 % and 18.25 % of the base load is necessary. Additionally, capacitor banks, contributing 36.84 % and 31.166 % of the reactive power load, are also required for effective voltage support and system reliability in each respective case.

New technical solutions for the design of NPP passive safety systems

The paper describes the new principle of passive NPP safety systems designing, in which the natural circulation of working fluid or gas is replaced by forced circulation in order to increase it’s capacity. The energy required by the system is converted from the emergency process itself, which this system resists when performing a given safety function. The goal is to expand the variety and capacity of passive NPP safety systems in order to optimize and reduce costs of NPP power units with various types of reactors while increasing the safety level. The proposed technical solutions are based on the use of direct non-mechanical conversion of the energy, comprised in emergency process, to electricity, and then to mechanical energy of hydraulic machine for working medium moving in a forced circulation mode. To demonstrate the proposed principles, the following technical solutions have been considered: • new passive electrochemical hydrogen recombiner for NPPs with light water reactors. Application of new techniques allowed increasing the performance by weight of the recommended hydrogen simultaneously with increasing the hydrogen torch threshold, as well as other important characteristics; • passive emergency core cooling system for heavy liquid metal cooled reactors. Application of new techniques allowed increasing the core remove heat capacity in order to scale down the main equipment; • passive system for in-vessel core melt retention of Pressurized Water Reactors of high thermal capacity (more than 3000 MWe). Application of new techniques allowed increasing the system thermal capacity in order to be able to apply to high thermal power reactors like VVER-1000 and more.

Hybrid Solar PV–Agro-Waste-Driven Combined Heat and Power Energy System as Feasible Energy Source for Schools in Sub-Saharan Africa

Poor access to electricity in rural communities has been linked to a poor educational system, as electricity is essential for supporting laboratories, technical practice, and long study hours for students. Therefore, this work presents the techno-economic analysis of a hybrid solar PV–agro-wastes (syngas) energy system for electricity, heat, and cooling generation to improve energy access in rural schools. The system is located in Ghana at Tuna (lat. 9°29′18.28″ N and long. 2°25′51.02″ W) and serves a secondary school for enhanced quality education. The system relies on agro-waste (gasifier-generator) and sunlight (solar PV), with a battery energy storage system, to meet the school’s energy demand. The study employs HOMER Pro Version 3.16.2 software to comprehensively analyze technical, economic, and environmental aspects. The system can generate 221,621 kWh of electricity (at a unit cost of electricity of 0.295 EUR/kWh) and 110,896 kWh of thermal energy yearly. The cost of electricity from the proposed system is cheaper than the cost of electricity from an equivalent diesel generator at 0.380 EUR/kWh. The thermal energy can meet the heating demand of the school in addition to powering a vapor absorption chiller. The system is environmentally friendly, with the capacity to sink 0.526 kg of CO2 yearly. Government policies that moderate interest rates for bioenergy/solar PV systems and social solution on feedstock pricing will favor the economic sustainability of the proposed system. The system will address the energy access challenge (SDG 7), enhance the quality of education (SDG 4), and contribute to climate mitigation through carbon sequestration (SDG 13).

Health Economic Evaluation of Antimicrobial Stewardship, Procalcitonin Testing, and Rapid Blood Culture Identification in Sepsis Care: A 90-Day Model-Based, Cost-Utility Analysis.

We evaluated the cost-effectiveness of a bundled intervention including an antimicrobial stewardship program (ASP), procalcitonin (PCT) testing, and rapid blood culture identification (BCID), compared with pre-implementation standard care in critically ill adult patients with sepsis. We conducted a decision tree model-based cost-effectiveness analysis alongside a previously published pre- and post-implementation quality improvement study. We adopted a public Canadian healthcare payer's perspective. Two intensive care units in Alberta with 727 adult critically ill patients were included. Our bundled intervention was compared with pre-implementation standard care. We collected healthcare resource use and estimated unit costs in 2022 Canadian dollars (CAD) over a time horizon from study entry to hospital discharge or death. We calculated the incremental net monetary benefit (iNMB) of the intervention group compared with the pre-intervention group. The primary outcome was cost per sepsis case. Secondary outcomes included readmission rates, Clostridioides difficile infections, mortality, and lengths of stay. Uncertainty was investigated using cost-effectiveness acceptability curves, cost-effectiveness plane scatterplots, and sensitivity analyses. Mean (standard deviation [SD]) cost per index hospital admission was CAD $83,251 ($107,926) for patients in the intervention group and CAD $87,044 ($104,406) for the pre-intervention group, though the difference ($3,793 [$7,897]) was not statistically significant. Costs were higher in the pre-intervention group for antibiotics, readmissions, and C. difficile infections. The intervention group had a lower mean expected cost; $110,580 ($108,917) compared with pre-intervention ($125,745 [$113,210]), with a difference of $15,165 ($8278). There were no statistically significant differences in quality adjusted life years (QALYs) between groups. The iNMB of the intervention group compared with pre-intervention was greater than $15,000 for willingness-to-pay (WTP) per QALY values of between $0 and $100,000. In our sensitivity analysis, the intervention was most likely to be cost-effective in roughly 56% of simulations at all WTP thresholds. Our bundled intervention of ASP, PCT, and BCID among adult critically ill patients with sepsis was potentially cost-effective, but with substantial decision uncertainty.