Cost Estimation Research Articles

Estimating the Incremental Cost Per QALY Produced by the Spanish NHS: A Fixed-Effect Econometric Approach.

Knowing the health opportunity costs of funding decisions is crucial to assess whether the health gains associated with new interventions are larger than the health losses imposed by the displacement of resources. Empirical estimates based on the effect of health spending on health outcomes have been proposed in several countries, including Spain, as a proxy to capture these opportunity costs. However, there is a need to regularly update existing health opportunity cost estimates and to explore the role of omitted variable bias in these estimations. The aim of this paper is to provide an updated and refined estimate of the causal impact of health spending on health in Spain that can be translated into an estimate of the incremental cost per quality-adjusted life-year produced by the Spanish national health system. We applied fixed-effect models using data for 17 Spanish regions from 2002 until 2022 to estimate the impact of public health spending on health outcomes and explored the extent of omitted variable bias. Changes in these estimates over time were assessed and alternative specifications were tested. Based on fixed-effect models with control variables, the estimated spending elasticity was 0.061, which translated into an incremental cost per quality-adjusted life-year of approximately €34,000. The bias-corrected elasticity was 0.075, with a corresponding incremental cost per quality-adjusted life-year of €27,000. We found that the estimated impact of spending on health decreases when recent years of data are added, and that the extent of omitted variable bias appears to increase, particularly when adding the COVID-19 pandemic period. This study provides an updated estimation of the incremental cost per quality-adjusted life-year produced by the Spanish national health system. The estimates provided can be easily updatable as new data become accessible, and the methods applied might be transferable to other settings with similar available data.

Construction Cost-Influencing Factors: Insights from a Survey of Engineers in Saudi Arabia

Cost overruns represent a continuous challenge within the construction industry, frequently affecting the success of projects. This study explores the factors influencing cost during the construction phase in Saudi Arabia, utilizing data from a survey of 1076 engineers working in the Saudi construction industry. The results identify a number of cost-related factors, including inadequate project management, poor cost estimation, and design errors. Interestingly, some factors, such as currency exchange rate fluctuations and social and cultural influences, were found to have a limited impact on construction costs. Furthermore, the study highlights the role of experience and education level in shaping engineers’ perceptions of these cost factors. The study employs statistical analysis, including Pearson’s chi-squared test, to demonstrate associations between demographics, project characteristics, and cost-influencing factors. The findings suggest the need for refined project management practices, enhanced technical training, and the implementation of digital technologies such as Construction 4.0 to mitigate cost-related risks. This research provides significant insights for construction professionals and policymakers seeking to enhance cost management within the Saudi construction sector, thereby contributing to the ongoing development initiatives aligned with Saudi Arabia’s Vision 2030.

A comprehensive quantitative lifecycle cost and environmental impact analysis model for computing infrastructure

This paper presents a comprehensive quantitative model for quantitative assessment of the lifecycle costs and environmental impacts of computing infrastructure, with a focus on internet data centers (IDCs) and high-performance computing (HPC) facilities. The key innovation lies in the integration of interdisciplinary cost evaluation and carbon emission methods for the establishment of this quantitative model. This framework, which outlines key cost components and carbon emission factors, enables the calculation of total costs, electricity expenses, and greenhouse gas emissions throughout the lifecycle of infrastructure. With IDCs as a case study, the research clarifies the intricate cost structure associated with equipment procurement, energy usage, land acquisition, and operational expenses. This paper provides an in-depth understanding of the cost structure and environmental impact of computing infrastructure in support of sustainable decision-making in its development.•Based on established cost estimation methods, such as Lifecycle Cost Analysis (LCCA) and the Analogous Estimating Method, this study examines costs across construction and operation phases.•The Emission Factor Method is used to quantify environmental impact, emphasizing the significance of regional energy mix and power usage effectiveness (PUE).

The financial impact of participant attrition from randomised trials: a case-study from the Occupational Therapist Intervention Study (OTIS).

Loss to follow-up of participants can compromise the statistical validity of randomised trials. Moreover, it can have financial consequences for trial teams and funders. This study explores the Occupational Therapist Intervention Study (OTIS) where, despite a withdrawal rate of less than 10%, the trial team incurred opportunity costs related to participants who were initially recruited but subsequently decided to withdraw from the trial. To estimate the cost of participant losses to follow-up in the OTIS trial and thus introduce a costing framework to research teams on how they could estimate the opportunity costs of participant withdrawal from their randomised trials. The participants lost to follow-up are differentiated by (1) the time point at which they were lost to follow-up; (2) the treatment group they were allocated to; (3) their response patters to follow-up questionnaires; these elements were considered to identify the relevant types of attrition. Protocol-driven costs of trial materials, including administration, print, and shipping, were gathered. We calculated unit costs for each type of attrition by multiplying protocol-driven and intervention costs with the relevant number of participants. Summing up unit costs by type of loss to follow-up yields aggregate figures, enabling the estimation of aggregate and average opportunity costs of attrition. The average cost per participant loss to follow-up in the OTIS trial is £98.41. The aggregate cost of participant loss to follow-up is £10,234.90 from the economic perspective of the trial team. Therefore, 1.42% of the allocated funding has been misallocated because of participant loss to follow-up. Despite the low attrition rate of the OTIS trial, loss to follow-up has still generated considerable opportunity costs. It is recommended that decision makers focus on identifying strategies which could improve participant retention in randomised trials to optimise their budget.

Predicting the most economical option of managing electric vehicle battery at the end of its serviceable life

It is predicted that millions of electric vehicle batteries (EVBs) will retire in the next decade. With the global Electric Vehicles (EVs) market share increasing to over 40 million by 2030, the replacement of unwanted EVBs will become more abundant and may end up in landfills. These discarded EVBs can become a threat to the environment and to human health if they are not treated, disposed of, and recycled appropriately. Numerous end-of-life (EOL) cost estimation methods that have been developed are mainly for evaluating fossil fuel vehicle components. Research within the scope of EOL of EVBs however, is slow in progress, therefore, this work focuses on developing a cost estimation method for predicting EOL costs of EVBs by adopting a circular economy approach. This proposed method is validated through a case study using two Nissan's EV battery packs. The significance of this study may provide valuable information which could, indirectly lead to the redesign of EVBs for better business circular economy and less waste pollution for future EVs. The main results show that the potential economic benefit that generated by reusing/repurposing EOL EVBs is 92% more profitable than recycling and 52% more profitable than remanufacturing. This study concludes that reuse/repurpose becomes the most profitable process when EVBs reach the end of their serviceable life. Remanufacturing method can also be economically viable if it considers multi-cell replacement of an EVB.

Understanding Power Gating Mechanism Based on Workload Classification of Modern Heterogeneous Many-Core Mobile Platform in the Dark Silicon Era

The rapid progress in mobile computing necessitates energy efficient solutions to support substantially diverse and complex workloads. Heterogeneous many core platforms are progressively being adopted in contemporary embedded implementations for high performance at low power cost estimations. These implementations experience diverse workloads that offer drastic opportunities to improve energy efficiency. In this paper, we propose a novel per core power gating (PCPG) approach based on workload classifications (WLC) for drastic energy cost minimization in the dark silicon era. Core of our paradigm is to use an integrated sleep mode management based on workloads classification indicated by the performance counters. A number of real applications benchmark (PARSEC) are adopted as a practical example of diverse workloads, including memory- and CPU-intensive ones. In this paper, these applications are exercised on Samsung Exynos 5422 heterogeneous many core system showing up to 37% to 110% energy efficient when compared with our most recent published work, and ondemand governor, respectively. Furthermore, we illustrate low-complexity and low-cost runtime per core power gating algorithm that consistently maximize IPS/Watt at all state space.

Pelatihan Peningkatan Kapasitas UMKM dan Kepariwisataan

On July 15, 2024, a community service activity was held in Kampung Dadap Timur with the topic "Training for Enhancing the Capacity of MSMEs and Tourism." The primary goal of this activity was to improve the skills and capacity of Micro, Small, and Medium Enterprises (MSMEs) and tourism destination management in the area. Initial observations identified fundamental needs in MSME management, budgeting for traditional food businesses, and applying the Sapta Pesona tourism concept. These findings served as the basis for designing relevant and targeted training materials. Preparations for the activity included intensive coordination among the service team to ensure the readiness of materials and equipment. Preparations also involved selecting and setting up the training venue, including audiovisual facilities and printed materials. The training covered: (1) MSME management strategies, including business planning, marketing, and product development; (2) budgeting techniques for traditional food MSMEs, including cost estimation, financial management, and pricing strategies; (3) application of the Sapta Pesona concept in tourism to enhance the quality of tourist experiences; and (4) practical sessions teaching how to make chicken dumplings and Es Kuwut. The training was designed to provide practical skills and in-depth knowledge to participants. Evaluation of the activity indicated that the training had a significant positive impact. Participants felt more confident and prepared in managing their businesses and tourism. However, the evaluation also identified some challenges, including the need for more specific case studies and ongoing support. It is recommended that future activities include follow-up sessions and more diverse training materials.

A taxonomy of machine learning techniques for construction cost estimation

A taxonomy of machine learning techniques for construction cost estimation

Forecasting Construction Cost Indices: Methods, Trends, and Influential Factors

The Construction Cost Index (CCI) is an important tool that is widely used in construction cost management to monitor cost fluctuations over time. Numerous studies have been conducted on CCI development and forecasting models, including time series, artificial intelligence, machine learning, and hybrid models. Therefore, this study seeks to reveal the complexity of CCI forecasting and identify the leading indicators, trends, and techniques for CCI prediction. A bibliometric analysis was conducted to explore the landscape in the CCI literature, focusing on co-occurrence, co-authorship, and citation analysis. These analyses revealed the frequent keywords, the most cited authors and documents, and the most productive countries. The research topics and clusters in the CCI forecasting process were presented, and directions for future research were suggested to enhance the prediction models. A case study was conducted to demonstrate the practical application of a forecasting model to validate its prediction reliability. Furthermore, this study emphasizes the need to integrate advanced technologies and sustainable practices into future CCI forecasting models. The findings are useful in enhancing the knowledge of CCI prediction techniques and serve as a base for future research in construction cost estimation.

Evaluation of Reporting Quality of Systematic Reviews on Health Economic Evaluation Studies Based on the CHEERS Statement: An Overview of Reviews.

Economic evaluations in healthcare are designed to inform decisions by the estimation of cost and effect trade-off of two or more interventions. We aimed to evaluate the standards of systematic reviews on health economic evaluation studies using the CHEERS (Consolidated Health Economic Evaluation Report Standards) tool. We searched the PubMed database with keywords CHEERS and its complete form in combination with keywords related to cost or economic evaluation without language and time limits until November 17, 2021. The CHEERS tool was then used to include systematic reviews. Overall, 32 systematic reviews, included 610 primary studies were included. Of the 32 included studies, only 1 study (3.1%) had poor quality, 5 studies (15.6%) had good quality, remaining studies had very good and excellent quality. Some studies still have problems in expressing the standards. The necessity of standards for reporting economic evaluation studies in the field of health is very serious, and Cheers is one of the most important tools.

Efficient removal of COD, BOD, oil & grease, and turbidity from oil-field produced water via electrocoagulation treatment.

The simple design, compactness, simultaneous treatment of multiple contaminants, absence of chemical usage, minimal sludge formation (reducing secondary pollution), low maintenance cost, and versatility to operate in both batch and continuous modes make electrocoagulation (EC) a promising choice for treating various types of industrial wastewater. In this study, EC was employed in batch mode to treat produced water obtained from an oil drilling site, to reuse it for injection purposes in the reservoir. Produced water typically contains high levels of total dissolved solids (TDS), turbidity, chemical oxygen demand (COD), biological oxygen demand (BOD), and oil & grease (O&G) contaminants. High-performing aluminum (Al) electrodes were chosen due to their stability, conductivity, and, most significantly, their high capacity for generating aluminum hydroxide ([Al(OH)₃]ₙ) flocs, which serve as carriers for contaminant capture. This compound has demonstrated remarkable effectiveness in trapping the aforementioned contaminants from produced water under various operating conditions, including the number of electrodes, supplied current, and electrode configuration (bipolar and monopolar). The impact of several factors, including the number of electrodes (varying from 4 to 8), current density (varying as 16, 79, 158 A/m2), and electrode configuration (bipolar and monopolar), was studied at room temperature and 250rpm agitation speed. Initial turbidity, COD, BOD, and O&G concentrations were measured at 38 NTU, 700.7ppm, 120ppm, and 32.8ppm, respectively. The EC treatment exhibited removal efficiencies of 51% for TDS, 85% for turbidity, 78% for COD, 80% for BOD, and 85% for O&G using a monopolar configuration with 8 electrodes, and 59% for TDS, 90% for turbidity, 85% for COD, 84% for BOD, and 86% for O&G using a bipolar configuration with eight electrodes. Additionally, cost estimation, considering electrode dissolution rate and power requirements, was conducted for the operation of both configurations.

Sustainable Stabilizer Derived from Calcium- and Phosphorus-Rich Biowaste for Remediation of Heavy Metal-Contaminated Soil: A Critical Review

Soil pollution by heavy metals (HMs) is a major environmental problem around the world. The addition of biowaste-based stabilizers for HM remediation has recently gained attention due to its relatively low cost and eco-risk, abundance, ease of operation, and quick remediation results. Among these stabilizers, shell (crustacean shell, bivalve shell, and eggshell), starfish, and bone-based stabilizers are particularly attractive because of their high Ca and P contents, allowing for highly efficient HM immobilization and simultaneous supplement of nutrients to the soil. However, a comprehensive review focusing on these stabilizers is currently missing. Therefore, this review attempts to summarize the HM immobilization efficiency of these stabilizers and the mechanisms associated with HM stabilization, and perform an operation cost estimation and cost comparison. Cost comparisons among different stabilizers are widely ignored in reviews due to the lack of reliable cost estimation tools or methods. However, for practical application in soil remediation, cost is one of the most important factors to consider. Thus, a simple but reasonable cost estimation method is developed and discussed in this review. Bivalve shell-based stabilizers demonstrated the most promising results for the immobilization of soil HMs in terms of higher performance and lower cost. Current research limitations, challenges, and recommendations regarding possible future research directions are also provided.

Challenges and recommendations for collecting and quantifying implementation costs in practice: a qualitative interview study

BackgroundThe cost of implementation is typically not accounted for in published economic evaluations, which determine the relative value for money of health innovations and are important for allocating scarce resources. Despite key papers outlining relevant implementation costs, they continue to be under reported in the literature and often not considered in practice. This study sought to understand and outline current practices for capturing the costs associated with implementation efforts, with examples from the digital health setting.MethodsA qualitative study of semi-structured interviews with purposefully sampled experts in implementation science, health economics and/or digital health was conducted. The interview guide was informed by a literature review and was pilot tested. Interviews were digitally recorded and transcribed. A hybrid inductive/deductive framework analysis was conducted using thematic analysis to elicit key concepts related to the research question.ResultsInterviews were conducted with sixteen participants with specialist expertise in implementation science (n = 8), health economics (n = 6), and/or digital health (n = 8). Five participants were experienced in more than one field. Four key themes were elicited from the data: difficulty identifying and collecting implementation cost data; variation in approaches for collecting implementation cost data; the value of implementation costs; and collaboration enables implementation costing. Broadly, while interviewees recognised implementation costs as important, only some costs were considered in practice likely due to the perceived ill-defined boundaries and inconsistencies in terminology. A variety of methods were used to collect and estimate implementation costs; the most frequent approach was staff time tracking. Multidisciplinary collaboration facilitated this process, but the burden of collecting the necessary data was also highlighted.ConclusionsIn current practice, standardised methods are not commonly used for data collection or estimation of implementation costs. Improved data collection through standardised practices may support greater transparency and confidence in implementation cost estimates. Although participants had industry exposure, most were also academic researchers and findings may not be representative of non-academic industry settings.

Economic burden of healthcare-associated infections (HAI) in a pediatric hospital in Honduras

Abstract Background In numerous reports, the World Health Organization has published that in LMICs approximately 15% of hospitalized patients acquire an HAI. In the Region of the Americas, many countries have made considerable progress in implementing IPC Programs. At Hospital María Especialidades Pediátricas (HMEP), the IPC Program aims to generate a patient safety culture mainly, but also reduce costs for the hospital and the patient. However, in LMICs, non-quality costs, including those associated with HAI, are rarely measured. This abstract aims to demonstrate the economic burden of HAI in hospitalized patients at HMEP between January 2020 and October 2023 and estimate the number of HAIs and associated costs prevented by the IPC Program. Methods At HMEP the IPC Program started in 2017, and the Accounting Department has measured the costs associated with treating and managing every HAI reported since January 2020. Provider costs for every HAI are estimated using a bottom-up (microcosting) approach in which three variables are considered: days of stay, all laboratory tests used for diagnosis and follow-up, and antimicrobials administered to treat the infection. The costs for each variable derive from the hospital’s purchasing system. This process allows us to estimate the annual HAI expenditure. For the estimation of costs avoided, we first calculated the average cost of each HAI using the yearly amount spent and dividing this amount by the number of HAIs registered in the same period. Considering the proportion of patients who suffered an HAI at HMEP compared to the 15% incidence reported by the WHO, we calculated a difference in proportions and were able to estimate the number of HAIs prevented and subsequent costs avoided. We use the NHSN HAI definitions since Honduras does not have a National IPC Program with standardized epidemiological criteria. The results are presented using descriptive statistics. Results During this time, 260 HAIs were identified at HMEP, average 5.6 per month, 57-70 yearly. The proportion of patients who developed an HAI was found to have decreased from 8.6% in 2020 to 5.2% in 2023. The total expenditure attributed to HAIs during the period was USD 913,774.21 (USD 19,865.0 pm). The costliest HAIs were CVC-associated bloodstream infections. HMEP is a public hospital and operates with funds provided by the government, which are deemed insufficient considering the complexity of the patients receiving care at the hospital. The estimated costs represent 2-3% of the hospital’s annual budget. Without the IPC Program, the predicted number of HAIs, according to the WHO, would have been 570 (15% of inpatients). We estimate 310 prevented HAIs, with an associated total cost of USD 1,103,577.99. Conclusion Regardless of the hospital’s methodology, measuring the economic burden related to HAIs is important for decision-making. The main objective of an IPC Program is to guarantee patient safety; however, especially in low-resource settings, it is also important to aim for a cost reduction. Limitations: our methodology does not include other variables (e.g. human resources); therefore, the data underestimates the real expenditure. We aim to improve the costing methodology for more accurate data.

Impact and critical factors in Heijunka implementation an action research study

Purpose: Although Heijunka (production levelling or smoothing) is a lean tool designed to balance changing customer needs and production efficiency, this study aims to analyze the impact of Heijunka and identify various factors which can generally affect its successful implementation.Design/methodology/approach: We adopted an action research (AR) approach to analyze the consequences of implementing Heijunka in a factory that successfully operates in a lean environment but faces demand that is increasingly less predictable, and customers who require ever more individualized products at low prices with extremely demanding delivery timescales. An estimation of costs was carried out to compare three alternative production planning scenarios: (1) make to order (MTO) production, (2) weekly levelled production and (3) production with minimal changeovers.Findings: The analysis of the impact of implementing Heijunka in this factory demonstrated that MTO production planning without Heijunka is the most efficient option for the factory. We explore the reasons why Heijunka is not suitable for this factory even though other lean principles and tools have been successfully implemented. In this way we identify the main factors which might influence the successful implementation of Heijunka, such as changeover time, the number of different product types (and lot sizes) and the capacity that the production lines are running at.Originality/value: Based on close collaboration between researchers and practitioners in the field of Operations Management, this AR study provides important information for decision making in lean environments (applying Heijunka or not), as well for the advancement of the academic debate about successful lean implementation nowadays.

Catalytic performance of FeCo2O4 spinel cobaltite for degradation of ethylparaben in a peroxymonosulfate activation process: Response surface optimization, reaction kinetics and cost estimation

The presence of cosmetics and personal care products in water resources has become an increasing concern for environment due to their toxicity and persistence in aquatic medium. Peroxymonosulfate mediated advanced oxidation methods have a great potential for the efficient removal of complex organic compounds due to the generation of highly reactive radicals with high oxidation ability. Iron cobaltite, FeCo2O4 catalyst was used as a peroxymonosulfate (PMS) activator for the degradation of ethylparaben which was selected as a model personal care product ingredient. Paraben degradation was modelled and the optimum operating parameters were determined by using Box-Behnken design. The ethylparaben degradation efficiency was calculated as 94.6 % under the optimized conditions which were determined as 0.9 g/L FeCo2O4 loading, pH 6.15, and 0.26 g/L PMS dosage. The ethylparaben degradation reaction followed second-order reaction kinetics. The activation energy was evaluated as 40.1 kJ/mol. Quenching radical tests showed that the dominant reactive species were hydroxyl radicals. Toxicity of the treated samples in terms of L. sativum growth inhibition was evaluated as 1.5 %. The total cost of the treatment including the operating and the amortization costs was calculated as 0.91 €/L.

Prediction and Estimation of Highway Construction Cost using Machine Learning

Prediction and Estimation of Highway Construction Cost using Machine Learning

A cost-effectiveness analysis of stereotactic ablative radiotherapy versus conventionally fractionated radiotherapy in the management of stage 1 non-small-cell lung cancer: Results from the TROG 09.02 CHISEL study.

Stereotactic ablative radiotherapy (SABR) is a standard of care treatment for medically inoperable early-stage non-small-cell lung cancer (NSCLC). The CHISEL trial was a phase 3 randomised controlled trial that compared SABR to conventional radiation therapy (CRT). Using patient-level data, we compared the cost-effectiveness of SABR and CRT for early-stage NSCLC. Data on treatment exposure, outcomes (recurrence, survival) and quality of life (QoL; EORTC QLQ-C30) were sourced from the trial. Quality-adjusted life years (QALYs) were estimated for the trial period using Australian utility weights for the EORTC QLQ-C30-derived QLU-C10D. Costs related to simulation, planning, delivery, verification and post-treatment monitoring were estimated by applying Australian Medicare Benefits Schedule fees. The costs of post-progression therapy and grade ≥3 toxicity were estimated using trial data and relevant literature sources. Cost-effectiveness was investigated as the incremental cost per QALY gained for SABR compared to CRT. Complete QoL data were available for 21 patients: 14 in the SABR arm and 7 in the CRT arm. Mean QALYs discounted at 5% per annum were similar between arms: 12.68 months for SABR and 12.12 months for CRT. The mean costs of delivering SABR and CRT were $4763 and $6817, respectively. The costs of monitoring were similar in both arms, $4856 and $4853 for SABR and CRT. The mean costs of post-progression therapy were $24,572 for SABR and $42,801 for CRT. The mean costs of grade ≥3 toxicity were $809 in the SABR arm and $132 in the CRT arm. Therefore, the total mean cost for SABR over the period of interest was lower for SABR than CRT. Given lower mean costs and numerically higher QALYs for SABR compared with CRT, an incremental cost-effectiveness ratio was not calculated. Compared to CRT, SABR is a cost-effective treatment for early-stage NSCLC as the estimated upfront treatment cost and the cost of subsequent care are lower for SABR for comparable mean QALYs. Assessment of the lifetime QALYs and projections of cost estimation will provide a better indication of the long-term cost-effectiveness of SABR.

How Do Managerial Biases Affect Foreign Market Entry Decisions?

In this practitioner-focused study, we discuss how cognitive biases impair foreign market entry decisions. Focusing on three factors that are central to the evaluation of foreign markets: cost, control, and uncertainty, we explain how decision-making biases undermine their assessment and the ways in which the biases can be mitigated. Specifically, overconfidence bias and the sunk cost fallacy negatively affect the estimation of entry costs which can be mitigated by a strong governance structure and independent reviews; anchoring and confirmation biases undermine the assessment of an appropriate level of control requiring the use of systematic decision frameworks and decision extension tools; and representativeness and availability biases limit the comprehension of environmental uncertainty suggesting mitigation strategies such as the challenging of internal assumptions and devil’s advocacy. By explicating how managerial biases turn into flawed assessments of foreign markets, our study uncovers the mechanisms that explain and potentially remedy cognitive pitfalls during internationalization.

Ergot alkaloid control in biotechnological processes and pharmaceuticals (a mini review).

The control of ergot alkaloids in biotechnological processes is important in the context of obtaining new strain producers and studying the mechanisms of the biosynthesis, accumulation and secretion of alkaloids and the manufacturing of alkaloids. In pharmaceuticals, it is important to analyze the purity of raw materials, especially those capable of racemization, quality control of dosage forms and bulk drugs, stability during storage, etc. This review describes the methods used for qualitative and quantitative chemical analysis of ergot alkaloids in tablets and pharmaceutic forms, liquid cultural media and mycelia from submerged cultures of ergot and other organisms producing ergoalkaloid, sclerotias of industrial Claviceps spp. parasitic strains. We reviewed analytical approaches for the determination of ergopeptines (including their dihydro- and bromine derivatives) and semisynthetic ergot-derived medicines such as cabergoline, necergoline and pergolide, including precursors for their synthesis. Over the last few decades, strategies and approaches for the analysis of ergoalkaloids for medical use have changed, but the general principles and objectives have remained the same as before. These changes are related to the development of new genetically improved strains producing ergoalkaloids and the development of technologies for the online control of biotechnological processes and pharmaceutical manufacturing ("process analytical technologies," PAT). Overall, the industry is moving toward "smart manufacturing." The development of approaches to production cost estimation and product quality management, manufacturing management, increasing profitability and reducing the negative impact on personnel and the environment are integral components of sustainable development. Analytical approaches for the analysis of ergot alkaloids in pharmaceutical raw materials should have high enough specificity for the separation of dihydro derivatives, enantiomers and R-S epimers of alkaloids, but low values of the quantitative detection limit are less frequently needed. In terms of methodology, detection methods based on mass spectrometry have become more developed and widespread, but NMR analysis remains in demand because of its high accuracy and specificity. Both rapid methods and liquid chromatography remain in demand in routine practice, with rapid analysis evolving toward higher accuracy owing to improved analytical performance and new equipment. New composite electrochemical sensors (including disposable sensors) have demonstrated potential for real-time process control.