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Performance indicators for organ donation and transplantation programmes in Europe: modified Delphi consensus study
Get PDFBACKGROUND: Health system performance assessment helps identify areas for improvement and guides policy initiatives. Although well-validated indicators exist for measuring organ donation and transplantation performance at the facility level, consensus on indicators for assessing national programmes is lacking. The aim of this study was to develop a comprehensive scorecard for evaluating national organ donation and transplantation programmes. METHODS: A three-step approach was used. First, a targeted literature review identified potential indicators from regulatory documents, national transplant organization reports, and databases. Second, indicators were mapped to an established transplant system framework and refined through preliminary expert consultations. Third, a modified Delphi consensus process validated the indicators. The Delphi panel comprised international experts in health policy, organ donation, transplantation, and patient representation. Participants rated 168 indicators using a five-point Likert scale across two rounds (24 experts completed round 1 and 22 experts completed round 2). Consensus for inclusion required 80% agreement. RESULTS: Of 168 indicators evaluated, 103 achieved consensus for inclusion. After consolidation of organ-specific indicators, the final set contained 84 indicators across seven domains: monitoring and reporting (8 indicators), prevention and need (9 indicators), waiting lists (11 indicators), consent (4 indicators), donation (28 indicators), transplantation (14 indicators), and follow-up (10 indicators). The indicator set incorporates established metrics such as waiting list statistics, donation rates, and complication rates alongside novel system-level indicators addressing structural factors, patient-centredness, and equity in care delivery. CONCLUSION: This validated indicator set provides a standardized tool for assessing and comparing transplant system performance across European countries, supporting performance benchmarking and evidence-informed policy development
Deep surrogates for finance: with an application to option pricing
No full textWe introduce “deep surrogates” – high-precision approximations of structural models based on deep neural networks, which speed up model evaluation and estimation by orders of magnitude and allow for various compute-intensive applications that were previously infeasible. As an application, we build a deep surrogate for a high-dimensional workhorse option pricing model. The surrogate enables us to re-estimate the model at high frequency to construct an option-implied tail risk measure, which is highly predictive of future market crashes. It also helps us systematically examine the model’s out-of-sample performance, which reveals the tradeoffs between structural and reduced-form approaches for option pricing. Moreover, we construct a measure for the degree of parameter instability and connect it to option market illiquidity in the data. Finally, we use the surrogate to construct conditional distributions of option returns, which is useful for risk management and provides a new way to test the model
Prediction, interpolation and extrapolation of the bonding strength between FRP bars and UHPC with machine learning
No full textAccurately predicting the bond strength between Fiber-Reinforced Polymer (FRP) bars and Ultra-High-Performance Concrete (UHPC) is essential for the design of FRP–UHPC components. This study develops a simplified bond strength prediction model based on the extrapolation analysis of machine learning (ML) models to enable reliable design beyond existing experimental data. An ensemble ML framework was constructed and optimized through data preprocessing and algorithmic comparison. The model’s extrapolation capability was verified using Basalt Fiber Reinforced Polymer (BFRP)–UHPC pull-out tests, demonstrating strong consistency between predictions and experiments. When trained on a dedicated FRP–UHPC database, the model achieved Root Mean Squared Error (RMSE) = 3.64, Mean Absolute Error (MAE) = 2.58, and coefficient of determination (R²) = 0.96; when expanded to include FRP–Normal Concrete (NC) and Steel–UHPC datasets, it maintained robust accuracy (RMSE = 9.97, MAE = 6.40, R² = 0.92). Based on parameter analysis of 77,200 sets of data points, a simplified bond strength calculation formula was derived using the least-squares method, incorporating the effects of concrete strength, cover thickness, bar type, surface profile, elastic modulus, diameter, anchorage length, and specimen type. The proposed formula achieved RMSE = 6.69, MAE = 4.80, and R² = 0.49, offering a practical tool for engineering design and providing a foundation for future FRP–UHPC research
Private health insurance in Gulf Cooperation Council countries: a scoping review
Get PDFPrivate Health Insurance (PHI) in Gulf Cooperation Council (GCC) countries has experienced rapid growth over the past two decades, driven by demographic and economic changes. Although various analyses at the country level have been reported, no study has reviewed PHI systems in the GCC through a methodological approach. We provide a conceptual framework to review, describe and document the development of PHI in the GCC, based on literature from the scoping review. As of December 2023, all GCC countries have laws in place or have promulgated laws establishing mandatory PHI schemes. Most of these schemes are designed for expatriate populations residing in these countries, but there is a trend to extend them to nationals working in the private sector. The health system context plays a role in how PHI emerged and is designed in terms of role, eligibility, and coverage. PHI markets in the region are concentrated and dominated by local companies with performance levels that could be further improved. These markets are maturing and subject to more robust technical and prudential regulations as governments seek to enhance competition. Governments in the region must ensure the sustainable growth of these schemes and a more strategic alignment with health system objectives. Lessons learned from more mature markets are critical for future developments
Solar electricity without solar panels: changes in consumption behavior due to community solar programs
Get PDFHow does electricity consumption behavior change with different energy sources? We seek to understand how consumers change their consumption behaviors when they begin to use renewable electricity via a community solar program. Previous research has found that consumers distinguish the power sources of electricity and even change their consumption behavior. Recent studies have explored changes in consumption associated with utility-run green electricity programs and rooftop solar, finding mixed results; however, studies on community solar programs are lacking. This study explores household-level consumption behavior after adopting solar electricity without panel installation. We use household-level monthly electricity consumption data from a large electric co-op in Georgia, U.S., ranging from 2015 to 2023, for both community solar subscribers and non-subscribers. We use staggered difference-in-differences, along with matching, to compare consumption changes before and after the subscription. Findings reveal that the consumption does not change after subscription, but subscribers' monthly bills increase by about 3–4 %, indicating they pay more to make the grid greener. This study will broaden the understanding of electricity sources and consumer behavior by adding the analysis of prevalent but under-studied community solar electricity programs in the U.S. Southeast context. It will help utility planners understand the changing demand as a result of renewable energy adoption
Narrow formalisation: informal workers, social protection and digital registration in India
Get PDFOver the last decade, there has been growing global pressure to build digitised social protection systems as a means of enhancing access to welfare. This article explores one such case: ‘e-Shram’, a digital registration platform introduced in India in the aftermath of the COVID-19 pandemic. Emerging as a direct consequence of the hardships faced by informal workers during the pandemic, the article examines e-Shram in this context. It observes that while e-Shram is increasingly portrayed as the first step towards a comprehensive formalisation programme, it fails to address the main gaps and issues highlighted by the pandemic; it provides some registration but maintains substantial deficiencies in service provision. This case study underscores why formalisation should be understood as a multidimensional process, and consequently, why it is important to separate it from particular instances of ‘narrow formalisation’ – commonly formalisations of governance, but not necessarily of work. This analysis carries broader implications for countries pursuing formalisation through digital platforms, emphasising the need for policies that align state objectives with genuine improvements in social and economic protections for informal workers
Historicizing global environmental politics
Get PDFThis article makes the case for a deeper integration of historical perspectives into the study of global environmental politics (GEP). A review of the Global Environmental Politics journal’s first twenty-five years reveals how, despite its multidisciplinary ethos, history remains marginal to the research agenda that characterizes its output. The article identifies three uses of historical perspectives that can enrich GEP scholarship. First, historical methods help establish more reliable knowledge of the past and provide historical perspective to contemporary debates on how to tackle environmental problems. Second, historical approaches promote greater reflexivity in the use of social scientific frameworks, for example, when it comes to historical periodization and identifying relevant political agency. Third, history highlights the inherent temporality of our knowledge of the past and our social scientific theories. The article concludes with a call for greater engagement with environmental history to broaden GEP’s theoretical horizon and presents historicization as essential to fostering a more self-reflective, critical, and temporally grounded understanding of GEP
Empirically assessing corporate adaptation and resilience disclosure using AI
Get PDFThe extent to which firms are adapting and building resilience to environmental change is crucial information for financial institutions, regulators and governments. While corporates’ physical climate risk exposure of their assets to environmental change can be calculated using models, additional information is needed to evaluate their vulnerability to physical climate change, how well they are adapting and broader alignment with societal adaptation and resilience (A&R) goals. This paper empirically evaluates the extent of A&R-related information in current corporate sustainability reports to provide such insights. We build on established sustainability disclosure frameworks and develop an A&R disclosure framework that we combine with the latest advances in large language models to assess S&P 500 company sustainability reports. We prove that corporate A&R information in sustainability reports is lacking, particularly around risks, metrics and targets, underlining the need to consider other data sources when assessing firm-level risks and contributions to societal A&R goals
Bringing ownership in: a conjunctural approach to venture capital valuations
Get PDFHigh startup valuations are commonly perceived as expressions of venture capitalists’ (VCs) power. This study complicates this view and argues that the valuation process is a struggle for ownership, deepening inequalities within the venture capital sector. Drawing on interviews with 19 early-stage VCs in London, I show that VC funds’ ability to obtain ownership stakes has changed in the low interest, expansive monetary policy environment of the 2010s. Late-stage VC funds moved into early-stage investing, increasing competition and upsetting previous alignments. Valuation practices centred on obtaining ownership and led to an antagonistic relationship between early and late-stage VCs. Following this, only a small group of elite funds delivered outsized returns while most funds failed to deliver promised returns. By foregrounding material limitations and conflict in the making of valuations, this study suggests that the business model of many VC funds became increasingly embattled during the 2010s tech boom
