Financial Model Research Articles

Investigating the Relationship Between Environmental, Social, and Governance Factors and the Capital Asset Pricing Model

This study delves into the intricate relationship between the Capital Asset Pricing Model (CAPM) and Environmental, Social, and Governance (ESG) factors in the investment landscape. Through an extensive review of existing literature and comparative analyses, the paper uncovers the historical development of CAPM, the rise of ESG considerations, and their convergence in modern financial theory. The research aims to shed light on the ongoing debates surrounding integrating ESG factors into the CAPM framework, revealing both supportive and critical viewpoints. Through a critical evaluation of empirical studies, the paper identifies gaps in the current body of knowledge, emphasizing the need for further research to understand the interplay between ESG factors and CAPM. The study concludes that while ESG considerations have increasingly influenced investment decisions, their precise relationship with traditional financial models, such as CAPM, remains an area ripe for exploration.

What's important in a contract beyond the salary? A primer for pain physicians and trainees.

This manuscript is designed to complement the previously published primer on salary structures for new pain physicians. The previous manuscript "Employment Contract Financial Models for the Pain Physician: A Primer" had a goal of increasing understanding of financial models by pain fellows when preparing for contract negotiations. This manuscript illustrates the many equally important considerations of "non-monetary" values that are a significant part of contract negotiation outside of salary. It contributes to the overall education for trainees and pain physicians on benefits and job responsibilities.

Navigating the Path to Electric Bus Integration: Ecological, Financial, and Strategic Analyses

Electric buses (E-buses) are gaining global attention for their positive impact on the environment and urban living. Governments worldwide recognize their potential to reduce air and noise pollution, ultimately enhancing urban environments. Despite their high energy conversion rates and economic advantages, widespread adoption faces challenges such as the need for extensive charging infrastructure, financial constraints, and concerns over long charging times and battery replacement costs. Due to these complexities, developed regions like Europe and North America have been cautious in fully embracing electric buses. To assess the pros and cons of transitioning to E-buses, this article examines factors including charging infrastructure, financial implications, and the challenges associated with long charging times and battery replacement costs. (1) Analysis of the ecological consequences of the E-bus transition is crucial for promoting its adoption, focusing on a five-dimensional comparison with diesel buses. Qualitative and quantitative methods were used to analyze air pollution using selected city data. (2) A financial implications model examined investment and returns, encompassing operational, capital, and overall costs for E-bus replacement. Expected returns were calculated considering three factors, providing a comprehensive financial overview. (3) Leveraging the financial analysis results, we devised a 10-year roadmap for full electric bus integration using linear programming. This approach maximizes expected returns by solving the investment portfolio proportions. Finally, we detailedly calculated the ecological sequence cost of conversion to fully electric flies for the selected city.

Systemic Financial Risk Forecasting with Decomposition–Clustering-Ensemble Learning Approach: Evidence from China

Establishing a scientifically effective systemic financial risk early warning model is of great significance for prudently mitigating systemic financial risks and enhancing the efficiency of financial supervision. Based on the measurement of systemic financial risk and the network sentiment index of 47 financial institutions, this study adopted the “decomposition–reconstruction–integration” approach, utilizing techniques such as extreme-point symmetric empirical mode decomposition (ESMD), empirical mode decomposition (EMD), variational mode decomposition (VMD), hierarchical clustering, fast independent component analysis (FastICA), attention mechanism, bidirectional long short-term memory neural network (BiLSTM), support vector regression (SVR), and their combination, to construct a systemic financial risk prediction model. The empirical results demonstrate that decomposing and reconstructing relevant indicators before predicting systemic financial risks can enhance prediction accuracy. Among the proposed models, the ESMD-HFastICA-BiLSTM-Attention model exhibits superior performance in systemic financial risk early warning.

Market Risk in Project Finance: Approaches to Review and Minimisation

Relevance. Development of an investment project is commonly associated with many risks, and one of the most significant risks is a market risk i.e. is a possible failure to achieve prices, volumes and sales projected in total compared to those planned in the business plan and financial model of a project. Modern literature pays not enough attention to many relevant and practical issues of the market risk (i.e. is a possible failure to achieve prices, volumes and sales projected) review and reduction in the project finance and investment review, as well as to issues of work with independent marketing consultants, possible areas and ways for risk reduction and quality improvement.Purpose. The previous article considered approaches to understanding significance of the market risk and measures to deal with the risk in the review of price forecasts for an investment project. This article is supposed to consider the issues of risk reduction by organising optimal work with an independent consultant on these issues.Objectives. It is supposed to consider the possibility of engaging an independent marketing consultant, the requirements to the consultant by the financing organisation or investor, to provide an example of detailed scope of work for the independent analysis, give examples of comments to the marketing report and proposed measures to adjust the analysis in the report. It is also necessary to consider approaches to the use of the financial model in order to reduce market risk effects in project financing.Methodology. Methods of analysis and synthesis, induction and deduction as well as modelling are used in the article.Results. The article considers two major issues related to the accounting for or reduction of the market risks in the development of investment projects and providing project finance: the range of questions regarding working with a marketing consultant in order to decrease market risk effects is discussed, examples of requirements to the consultant and potential scope of work as well as some possible errors examples are given; author discusses instruments for considering these risks in financial model, including increased required levels for liquidity and debt service ratios in case of high risks and uncertainties.Conclusion. The market risk is one of the key risks in the development of an investment project and project review in project finance. A set of measures is needed to reduce and account for the risk. Proper application of these and other reasonable measures should enable project initiators and sponsors to ensure their successful development and compliance with the debt service schedule to third-party lenders.

Deep calibration with random grids

We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural network perspective on pricing and calibration in (rough) volatility models. Quant. Finance, 2021, 21(1), 11–27]. with the pointwise two-stage calibration of Bayer and Stemper [Deep calibration of rough stochastic volatility models. Working Paper, arXiv:1810.03399, 2018] and Liu et al. [A neural network-based framework for financial model calibration. J. Math. Ind., 2019, 9(1), 1–28]. Our methodology inherits robustness from the former while not suffering from the need for interpolation/extrapolation techniques, a clear advantage ensured by the pointwise approach. The crucial point to the entire procedure is the generation of implied volatility surfaces on random grids, which one dispenses to the network in the training phase. We support the validity of our calibration technique with several empirical and Monte Carlo experiments for the rough Bergomi and Heston models under a simple but effective parametrization of the forward variance curve. The approach paves the way for valuable applications in financial engineering—for instance, pricing under local stochastic volatility models—and extensions to the fast-growing field of path-dependent volatility models.

Irrational behavioral models of personal finance and their evolution in the digital economy

Aim. To review the evolution of scientific concepts investigating the motives for decision[1]making based on irrational consumer behavior and to identify real changes in behavioral models   of personal finance.   Objectives. To examine the evolution of scientific concepts of the world’s leading scientists on   decision-making motives in the consumer market; to consider the effects of irrational consumer   behavior; to identify key changes in consumer buying decision behavior caused by digitalization. Methods. The article is based on the analysis of scientific works of leading classical economists,   interdisciplinary scientific research of modern foreign and domestic scientists devoted to the   issues of decision-making in the field of consumption. The institutional approach was applied,   which allowed us to study the evolution of irrational behavior in the field of personal finance   depending on the dominant social values. Results. In the process of analyzing theoretical provisions of famous scientists up to the middle   of the twentieth century, the justification of consumers’ decision-making in the consumer market   based on their desire to maximize pleasure, utility of welfare is presented. Such behavior can be   attributed to irrational behavior. Gradually, taking into account the market regulators of consumption opportunities, scientists come to the conclusion about the rational behavior of individuals. However, by the end of the twentieth century, the position of scientists changes towards   limited rationality due to the inability of individuals to adequately assess the array of information   affecting decision-making in the consumer market. On the basis of conclusions drawn by modern   scientists in the framework of interdisciplinary research, such a new direction of economic science   as “behavioral economics” emerges, which combined the knowledge of both economics and psychology. Modern research has shown some effects in behavioral finance related to the irrationality of   consumer behavior when making a purchase decision: the Veblen effect, the Diderot effect and   others. The latest research on the impact of digitalization on consumer behavior reflects the   changes taking place in consumer behavior towards rationalization.  Conclusions. The concepts and models describing the peculiarities of irrational behavior of   individuals related to decision-making and based on irrational spending of personal financial   resources from the point of view of classical economic science are considered. The evolution of   scientific concepts of irrational behavior of the world’s leading economists during two centuries   is presented. The effects of irrational consumer behavior proposed by scientists in the framework   of interdisciplinary research are studied. Among them are the Veblen effect, the Diderot effect.   The influence of digitalization on personal finance decision-making is shown. 

Impact of billing reforms on academic hospitalist physician and advanced practice provider collaboration: A qualitative study.

Medicare previously announced plans for new billing reforms for inpatient visits that are shared by physicians and advanced practice providers (APPs) whereby the clinician spending the most time on the patient visit would bill for the visit. To understand how inpatient hospital medicine teams utilize APPs in patient care and how the proposed billing policies might impact future APP utilization. We conducted focus groups with hospitalist physicians, APPs, and other leaders from 21 academic hospitals across the United States. Utilizing rapid qualitative methods, focus groups were analyzed using a mixed inductive and deductive method at the semantic level with templated summaries and matrix analysis. Thirty-three individuals (physicians [n = 21], APPs [n = 10], practice manager [n = 1], and patient representative [n = 1]) participated in six focus groups. Four themes emerged from the analysis of the focus groups, including: (1) staffing models with APPs are rapidly evolving, (2) these changes were felt to be driven by staffing shortages, financial models, and governance with minimal consideration to teamwork and relationships, (3) time-based billing was perceived to value tasks over cognitive workload, and (4) that the proposed billing changes may create unintended consequences impacting collaboration and professional satisfaction. Physician and APP collaborative care models are increasingly evolving to independent visits often driven by workloads, financial drivers, and local regulations such as medical staff rules and hospital bylaws. Understanding which staffing models produce optimal patient, clinician, and organizational outcomes should inform billing policies rather than the reverse.

Optimal decisions of retailer's loans from bank

AbstractThis study employs the Stackelberg game model to explore an innovative financing model where the retailer directly borrows from the bank under conditions of symmetric information. Diverging from traditional research, this study uniquely incorporates the concept of the margin rate into the decentralised decision analysis among retailer, supplier, and bank. The finding indicates that the capital of the retailer and margin rate significantly influence financing decisions within the supply chain, thereby impacting profitability for all stakeholders. Specifically, we find that the margin rate plays a crucial role in optimising retailer financing decisions, supplier pricing strategies, and bank risk management. These insights offer a fresh perspective for banks to establish appropriate margin rates and loan interest rates, effectively managing loan risks and maximising supply chain profitability.

Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings

Over recent years, the sustainability and resilience concept has increased its significance in the construction industry. Sustainability is associated with implementing best practices in the construction industry, while resilience is the adaptability and tolerance of systems in harsh conditions. The concepts are learned in the construction process. Moreover, building automation is growing rapidly, and buildings are becoming increasingly dependent on complex systems and technology and susceptible to unanticipated failure. Though sustainability and resilience concepts are interlinked, limited research quantifies their combination, resulting in a limited comprehension of how both concepts interact during application by developers in a smart building. Therefore, this study has established a financial model that employs Net Present Value (NPV) in studying the inference and clampdown of investment in both concepts. NPV was estimated using indirect and direct costs and benefits derived from the continuous integration of sustainability and resilience in a smart building. To quantify sustainability, its three components had to be quantified. Reduced energy expenditure and government environmental incentives were used to calculate the environmental component. Workers’ cost savings, fire insurance cost savings, and additional system maintenance costs were used to calculate the economic component. The social component of sustainability measured hard-to-quantify attributes like productivity, indoor environment quality, reputation, extra profit, services, and safety. To quantify them, a survey and RII method were used. The two concepts were then coupled by estimating the benefits and costs of installing and keeping resilience tools in design that are sustainable in the smart building and the impact study on the NPV outcome. Application of the design model was also carried out on four smart buildings that were selected in Dubai. The result indicated that coupling sustainable approaches and resilience yields higher NPV by at least 22%. Nevertheless, for NPV to be maintained positively and reduce the cost of failure, faulty detection tools should be assimilated while designing sustainable and smart buildings. The findings of this study will contribute to the benefit of other researchers, developers, investors, managers, engineers, and anyone who is involved in the design or construction process of intelligent buildings.

Lessons Learned from the Implementation of Youth Wellness Hubs Ontario, an Integrated Youth Services Network: Perspectives from Network Leads.

Mental health and substance use services for youth in Canada continue to be fragmented. In response, Integrated Youth Services (IYS) has been proposed to address gaps in youth mental health services that can lead to improved youth outcomes. Youth Wellness Hubs Ontario (YWHO) was launched in 2017 as Ontario's IYS Network for youth ages 12-25, prioritizing continuous improvement through evaluation. At the end of the first three years of the YWHO initiative, an evaluation was carried out to identify the barriers and facilitators to the initial implementation of YWHO and service delivery modifications resulting from the COVID-19 pandemic across ten sites. Reporting on these is the focus of this article. Key informant interviews were conducted in early 2021 with Network Leads from all ten initial YWHO sites. Reflexive thematic analysis was used to analyze all interview data. Facilitators to the implementation of the YWHO model included diversified funding models, YWHO Provincial Office implementation supports, clear hub processes, robust community partnerships, organizational support and dedicated staff. Common barriers included certain challenges related to staffing and finances, implementation of the shared data collection platform, implementation of measurement-based care, partnerships, integrated service delivery, and branding and communications. Implementation of IYS is highly collaborative and quite complex. As interest in such models increase, so does the need for knowledge related to optimal implementation. Learnings have informed developments and improvements made to the YWHO model. Insights will also inform how stakeholders support youth in their communities in designing and implementing services that improve youth mental health and overall well-being.

Towards efficient similarity embedded temporal Transformers via extended timeframe analysis

AbstractPrice prediction remains a crucial aspect of financial market research as it forms the basis for various trading strategies and portfolio management techniques. However, traditional models such as ARIMA are not effective for multi-horizon forecasting, and current deep learning approaches do not take into account the conditional heteroscedasticity of financial market time series. In this work, we introduce the similarity embedded temporal Transformer (SeTT) algorithms, which extend the state-of-the-art temporal Transformer architecture. These algorithms utilise historical trends in financial time series, as well as statistical principles, to enhance forecasting performance. We conducted a thorough analysis of various hyperparameters including learning rate, local window size, and the choice of similarity function in this extension of the study in a bid to get optimal model performance. We also experimented over an extended timeframe, which allowed us to more accurately assess the performance of the models in different market conditions and across different lengths of time. Overall, our results show that SeTT provides improved performance for financial market prediction, as it outperforms both classical financial models and state-of-the-art deep learning methods, across volatile and non-volatile extrapolation periods, with varying effects of historical volatility on the extrapolation. Despite the availability of a substantial amount of data spanning up to 13 years, optimal results were primarily attained through a historical window of 1–3 years for the extrapolation period under examination.

Adapting care provision in family practice during the COVID-19 pandemic: a qualitative study exploring the impact of primary care reforms in four Canadian regions

BackgroundOver the past two decades, Canadian provinces and territories have introduced a series of primary care reforms in an attempt to improve access to and quality of primary care services, resulting in diverse organizational structures and practice models. We examine the impact of these reforms on family physicians’ (FPs) ability to adapt their roles during the COVID-19 pandemic, including the provision of routine primary care.MethodsAs part of a larger case study, we conducted semi-structured qualitative interviews with FPs in four Canadian regions: British Columbia, Newfoundland and Labrador, Nova Scotia, and Ontario. During the interviews, participants were asked about their personal and practice characteristics, the pandemic-related roles they performed over different stages of the pandemic, the facilitators and barriers they experienced in performing these roles, and potential roles FPs could have filled. Interviews were transcribed and a thematic analysis approach was applied to identify recurring themes in the data.ResultsSixty-eight FPs completed an interview across the four regions. Participants described five areas of primary care reform that impacted their ability to operate and provide care during the pandemic: funding models, electronic medical records (EMRs), integration with regional entities, interdisciplinary teams, and practice size. FPs in alternate funding models experienced fewer financial constraints than those in fee-for-service practices. EMR access enhanced FPs’ ability to deliver virtual care, integration with regional entities improved access to personal protective equipment and technological support, and team-based models facilitated the implementation of infection prevention and control protocols. Lastly, larger group practices had capacity to ensure adequate staffing and cover additional costs, allowing FPs more time to devote to patient care.ConclusionsRecent primary care system reforms implemented in Canada enhanced FPs’ ability to adapt to the uncertain and evolving environment of providing primary care during the pandemic. Our study highlights the importance of ongoing primary care reforms to enhance pandemic preparedness and advocates for further expansion of these reforms.

Factors for the integration of prevention in primary care: an overview of reviews.

The global burden of non-communicable diseases is increasing and the need for prevention is huge. Policies have yet to produce results and prevention indicators remain low. Primary care (PC) represents an opportunity to optimise the practice of prevention, but GPs are coming up against barriers that are holding back their prevention practices. The aim of this overview of reviews is to identify the barriers and facilitators for the implementation of routine prevention practices in PC. This study is an international overview of reviews focusing on the integration of prevention in PC settings. The search was conducted on July 2022 in MEDLINE, EMBASE, Web of Science and the Cochrane Database of Systematic Reviews. Included reviews are: systematic reviews or scoping reviews adopting a systematic approach. The 35 reviews included identify multiple barriers and facilitators related to the integration of prevention in PC. These factors are very heterogeneous as regards their source (the patient, the professional and the health system) and their level of action (individual, organisational or contextual). The results show the need to organise PC at the professional level (e.g. in training), at the local level (e.g. partnerships) and at the political level (e.g. funding model). The factors influencing the integration of prevention in PC are multiple and act at different levels (individual, organisational and health system level). Organisation factors play a major role and seem to be a means of overcoming the difficulties encountered by healthcare professionals in developing preventive practices.

Transforming health care delivery: The role of primary health care nurses in rural and remote Australia.

This paper describes the policy context and approaches taken to improve access to primary health care in Australia by supporting nurses to deliver improved integrated care meeting community needs. In Primary Health Care (PHC), the nursing workforce are predominantly employed in the general practice sector. Despite evidence that nurse-led models of care can bridge traditional treatment silos in the provision of specialised and coordinated care, PHC nurses' scope of practice varies dramatically. Nurse-led models of care are imperative for rural and remote populations that experience workforce shortages and barriers to accessing health care. Existing barriers include policy constraints, limited organisational structures, education and financing models. The Australian Primary Health Care Nurses Association (APNA) received funding to implement nurse-led clinics as demonstration projects. The clinics enable PHC nurses to work to their full scope of practice, improve continuity of care and increase access to health care in under serviced locations. We reviewed a range of peer-reviewed literature, policy documents, grey literature and APNA provided sources, particularly those relevant to rural and remote populations. We argue more focus is needed on how to address variations in the scope of practice of the rural and remote PHC nursing workforce. Despite growing evidence for the effectiveness of nurse-led models of care, significant policy and financial barriers continue to inhibit PHC nurses working to their full scope of practice. If their potential to transform health care and increase access to health services is to be realised these barriers must be addressed.

Construction and evaluation of financial distress early warning model based on machine learning

As the economy of our nation has expanded, the harm resulting from the financial risks associated with listed corporations has intensified, significantly impeding the survival and expansion of businesses. We must create a reliable financial crisis early warning system to prevent financial risks from endangering the business. This article aims to analyse the development of financial early warning models that use machine learning techniques. The model employs the Archimedes optimization method (AOA) method to optimize the parameters of SVM and selects 20 financial risk assessment indices as the input to anticipate the financial crises. The results suggest that the proposed model surpasses current models in terms of both prediction accuracy and resilience. They also highlight the ensemble model's greater predictive capacity when compared to individual algorithms, highlighting its efficacy in spotting early warning signs of financial instability in a variety of market scenarios. Financial organisations and governments may improve their risk management procedures and prevent future crises by incorporating machine learning techniques into the early warning system.

Analyzing the Dynamics: EU and UN Perspectives on the African Union

This article presents a comprehensive analysis of the dynamics between the European Union (EU) and the United Nations (UN) in their interactions with the African Union (AU). Recognizing the AU's pivotal role in addressing Africa's challenges, the study investigates historical trajectories, policies, and key priorities shaping EU and UN perspectives on the AU. Through a multi-methodological approach, including document review and comparative analysis, it explores areas of convergence, divergence, and potential conflicts in their approaches, shedding light on implications for the AU's development and international relations. Tracing the historical evolution of EU-AU and UN-AU relations, pivotal moments such as the Cotonou Agreement and the establishment of the UN Office to the African Union (UNOAU) are highlighted. Analysis reveals shared objectives in peace, security, sustainable development, and governance, with nuanced differences in emphasis and approach. While areas of alignment exist, particularly in peacekeeping and sustainable development goals, divergences emerge in governance, human rights, and economic relations, posing challenges to collaboration.Case studies, including joint peacekeeping missions in Mali and development initiatives in Eastern Africa, offer insights into successes, challenges, and lessons learned, informing recommendations for future collaborations. Opportunities for enhanced cooperation, such as joint capacity-building initiatives and aligned development programs, are identified.The study contributes to a nuanced understanding of EU and UN perspectives on the AU, providing insights into their implications for Africa's development. Recommendations for improvements in coordination mechanisms, communication channels, and decision-making processes are proposed to enhance effectiveness. Future research avenues include evaluating economic partnerships' impacts and exploring innovative funding models to unlock transformative impact on the African continent. Ultimately, this analysis informs policymakers and international practitioners, fostering constructive partnerships for Africa's stability, prosperity, and sustainable development.

Symmetry and symmetric transformations in mathematical imaging

The article delves into the intricate relationship between symmetry and mathematical imaging, spanning various mathematical disciplines. Symmetry, a concept deeply ingrained in mathematics, manifests in art, nature, and physics, providing a powerful tool for understanding complex structures. The paper explores three types of symmetriesreflection, rotational, and translationalexemplified through concrete mathematical expressions. Evariste Galoiss Group Theory emerges as a pivotal tool, providing a formal framework to understand and classify symmetric operations, particularly in the roots of polynomial equations. Galois theory, a cornerstone of modern algebra, connects symmetries, permutations, and solvability of equations. Group theory finds practical applications in cryptography, physics, and coding theory. Sophus Lie extends group theory to continuous spaces with Lie Group Theory, offering a powerful framework for studying continuous symmetries. Lie groups find applications in robotics and control theory, streamlining the representation of transformations. Benoit Mandelbrots fractal geometry, introduced in the late 20th century, provides a mathematical framework for understanding complex, self-similar shapes. The applications of fractal geometry range from computer graphics to financial modeling. Symmetrys practical applications extend to data visualization and cryptography. The article concludes by emphasizing symmetrys foundational role in physics, chemistry, computer graphics, and beyond. A deeper understanding of symmetry not only enriches perspectives across scientific disciplines but also fosters interdisciplinary collaborations, unveiling hidden order and structure in the natural and designed world. The exploration of symmetry promises ongoing discoveries at the intersection of mathematics and diverse fields of study.

Accelerated numerical solutions for discretized Black–Scholes equations

Abstract Accepted by: Aris Syntetos This study thoroughly investigates the efficiency of advanced numerical extrapolation methods aimed at enhancing the convergence of vector sequences in the realm of mathematical finance. Our focus lies in the application of polynomial extrapolation techniques to calculate finite difference solutions for the Black–Scholes (BS) equation—an indispensable model in options pricing. The performance of our algorithms undergoes rigorous evaluation through a comprehensive analysis involving both simulated and real-world data. Notably, our experiments uncover that a stochastic scheme, incorporating two extrapolation strategies and a random relaxation parameter, outperforms other proposed methods, excelling in both convergence and stability metrics. Our findings underscore the potential of this numerical extrapolation method to enhance the efficiency of financial calculations, particularly in the realm of option pricing. This innovation holds promise for refining financial models and addressing specific challenges within the field of mathematical programming, providing effective solutions to the primary computational bottlenecks commonly encountered in financial decision-making.

516 Alternative Clinical Trials Staffing Models for Improved Efficiency, Retention, and Profitability

OBJECTIVES/GOALS: High turnover rates of clinical trials staff pose obstacles to the quality and efficiency of conducting clinical trials. We have explored alternative staffing models to address these translational barriers and to improve the financial viability and return on investment of a centralized clinical trials office. METHODS/STUDY POPULATION: Implementation of an alternative clinical trials staffing model that leveraged burnout rates in clinical service areas by hiring APPs, RNs, EMTs, OTs and PTs in tandem with traditional CRAs/CRCs. Financial modelling of employing higher salaried clinical professionals was analyzed with regards to greater staff retention, trials efficiency, and operational cost savings. RESULTS/ANTICIPATED RESULTS: Since 2014, 30 of 51 (59%) staff left the clinical trials office with 49% of these leaving prior to 2 years employment. Using average local CRCII compensation values, the costs associated with these transient staff amounted to $2.51 million (i.e., recruitment, replacement, and training). Models of staffing that replace 2 CRAs, 2 CRCIs and 2 CRCIIs with an RN, APP, CRCI and 3 CRAs increases compensation by 24.1%. This increase, however, is offset by greater workload capacity, retention, and more efficient trials operations. In addition, revenue generating PI clinical activity is sustained by employing credentialed APPs for study visits. DISCUSSION/SIGNIFICANCE: Long-term financial savings and greater clinical trial operational efficiency may be accomplished by seeking clinical professionals looking for alternative opportunities with greater work-life balance while leveraging their advanced clinical skills and licensing.