Transfer Decisions Research Articles

Hospital transfers from care homes: conceptualising staff decision-making as a form of risk work

When making decisions about whether to transfer residents to hospital, care home staff consider the possible benefits and risks of different courses of action. However, to date, an in-depth and theoretically informed engagement with these decision-making processes and their associated behaviours has been lacking. We conducted an ethnographic study of care home staff’s decision-making about resident hospital transfers in England between May 2018 and November 2019. We combined staff interviews at six care home sites, with 30 members of staff, with 113 hours of ethnographic observation at three care homes sites. ‘Risk’ and risk management emerged as important overarching themes. In this article we conceptualise staff decision-making about potential hospital transfers for residents as a form of risk work. In doing so, we identify the different forms of risk knowledge that staff used to conceptualise risk and explore the ways staff navigated tensions between different forms of risk knowledge. We highlight the ways individual understandings of risk were influenced by social interactions with others, both at an interpersonal and organisational level, before identifying strategies that staff use to manage risk. By understanding transfer decisions explicitly in terms of the different forms of risk that care home staff manage, our analysis provides new insights into hospital transfers from care homes and contributes to the wider literature around risk work, demonstrating the utility of this concept in researching organisations that fall under the umbrella of social care, which have been previously neglected in academic research.

Use of reverse shock index times Glasgow coma scale (rSIG) to determine need for transfer of pediatric trauma patients to higher levels of care

IntroductionMost children in the US live more than one hour from a Level 1 PTC. The Need For Trauma Intervention (NFTI) score was developed to assess trauma triage criteria and is dependent on whether someone requires one of six urgent interventions (NFTI+). We sought to determine if a novel scoring tool, rSIG, could predict NFTI and facilitate the transfer decision making process. MethodsChildren 1–18 years old transferred to our level 1 PTC from 2010 - 2020 with complete vital signs and Glasgow Coma Scale (GCS) score at the transferring facility were included. rSIG was calculated as previously described [(SBP/HR) x GCS], and the following cutoffs were used for each age group: ≤13.1, ≤16.5, and ≤20.1 for 1–6, 7–12, and 13–18 years, respectively. Clinical outcomes upon arrival to the PTC were collected to determine if patients met any NTFI criteria. ResultsA total of 456 patients met inclusion criteria. The proportion of patients with an abnormal rSIG was 60.1% (274) and 37.0% (169) were NFTI+. Patients with an abnormal rSIG had an odds ratio of 6.18 (95% CI: 3.90, 10.07), p < 0.001 of being NFTI+ compared to those with a normal rSIG. ConclusionChildren with an abnormal rSIG are more likely to be NFTI+ and require higher levels of care, indicating this scoring tool can identify pediatric trauma patients who may benefit from expedited transfer. Incorporating rSIG into initial evaluation and triage of traumatically injured children may expedite the transfer decision making process and limit delays in transport to a PTC. Type of studyRetrospective Comparative Study Level of evidenceIII

A study of the impact of land transfer decisions on household income in rural China.

As an important measure to enhance the allocation of land resources and achieve moderate scale operation in China, land transfer has an irreplaceable role in giving full play to the social and economic value of land. This paper uses data from the China Family Panel Studies in 2018 and applies OLS, PSM and mediator effects to study the impact of land transfer on household income. The results of the study show that: firstly, participation in land transfer can significantly increase the income level of farming households, but the impact of different land transfer acts on household income varies. Secondly, the age and physical condition of the household head, the number of agricultural and non-agricultural members in the household and the poverty status of the household all have a negative effect on household income. On the other hand, the education level of the household head, the household size and the presence of village officials in the household, agricultural subsidies, land titling and land size all have a positive effect on household income. Thirdly, the impact on household income for households that did not participate in land transfer is greater than for those that did. The results of the mediator effect test show that land transfer has a significant effect on household farm income, and that farm income has a full mediator effect, but all have a positive significant effect on household income.

Impact of inter-hospital transfer on outcomes of urgent cholecystectomy

BackgroundThis study used a national cohort to characterize the impact of inter-hospital transfer status on outcomes following nonelective cholecystectomy for cholecystitis. MethodsNonelective cholecystectomies were identified using the 2016–2019 National Inpatient Sample. Multivariable models adjusting for patient and hospital characteristics were utilized to assess outcomes of interest. ResultsOf an estimated 530,696 patients, 5.3% were transferred. Transferred patients were older, more often male, and more likely to report income in the 0th-25th percentile, compared to others. After adjustment, transfer was associated with increased odds of infectious complications (AOR 1.31, 95%CI 1.06–1.60) and non-home discharge (AOR 1.59, 95%CI 1.45–1.74), but not mortality. Transfer was linked to a $600 cost decrement at the operating hospital (95%CI -$880-330). ConclusionsTransfer status is associated with greater postoperative infection, but not mortality. Given that disparities may play a role in transfer decisions, more work must be done to identify transfer drivers and improve patient outcomes.

Transferring With TACT: A Novel Tool to Standardize Transfer Decisions From a Level IV NICU.

Neonatal patients who no longer require level IV neonatal intensive care unit care are transferred to less acute levels of care. Standardized assessment tools have been shown to be beneficial in the transfer of patient care. However, no standardized tools were available to assist neonatal providers in the assessment and communication of the infants needs at transfer. The purpose was to develop a Transfer Assessment and Communication Tool (TACT) that guides provider decision making in the transfer of infants from a level IV neonatal intensive care unit to a less acute level of care within a regionalized healthcare system. Phase 1 included developing the first draft of the TACT using retrospective data, known variables from published literature, and study team expertise. In phase 2, the final draft of the TACT was created through feedback from expert neonatal providers in the regionalized care system using e-Delphi methodology. The first draft of the TACT, developed in phase 1, included 36 characteristics. In phase 2, nurses, nurse practitioners, and physician experts representing all levels of newborn care participated in 4 e-Delphi surveys to develop the final draft of the TACT, which included 74 weighted characteristics. Potential benefits of the TACT include improved communication across healthcare teams, reduced risk for readmission, and increased caregiver visitation. The next steps are to validate the TACT for use either retrospectively or in real time, including characteristic weights, before implementation of this tool in the clinical setting.

Pediatric Patient Insurance Status and Regionalization of Admissions.

Pediatric hospital care is becoming increasingly regionalized, and previous data have suggested that insurance may be associated with transfer. The aims of the study are to describe regionalization of pediatric care and density of the interhospital transfer network and to determine whether these varied by insurance status. Using the New York State ED Database and State Inpatient Database from 2016, we identified all pediatric patients and calculated regionalization indices (RI) and network density, overall and stratified by insurance. Regionalization indices are based on the likelihood of a patient completing care at the initial hospital. Network density is the proportion of actual transfers compared with the number of potential hospital transfer connections. Both were calculated using the standard State ED Database/State Inpatient Database transfer definition and in a sensitivity analysis, excluding the disposition code requirement. We identified 1,595,566 pediatric visits (emergency department [ED] or inpatient) in New York in 2016; 7548 (0.5%) were transferred and 7374 transferred visits had eligible insurance status (Medicaid, private, uninsured). Of the transfers, 24% were from ED to ED with discharge, 28% from ED to ED with admission, 31% from ED to inpatient, 16% from inpatient to inpatient, and 1.2% from inpatient to ED. The overall RI was 0.25 (95% confidence interval [95% CI], 0.20-0.31). The overall weighted RI was 0.09 (95% CI, 0.06-0.12) and was 0.09 (95% CI, 0.06-0.13) for Medicaid-insured patients, 0.08 (95% CI, 0.05-0.11) for privately insured patients, and 0.08 (95% CI, 0.05-0.11) for patients without insurance. The overall network density was 0.018 (95% CI, 0.017-0.020). Network density was higher, and transfer rates were lower, for patients with Medicaid insurance as compared with private insurance. We found significant regionalization of pediatric emergency care. Although there was not material variation by insurance in regionalization, there was variation in network density and transfer rates. Additional work is needed to understand factors affecting transfer decisions and how these patterns might vary by state.

Effect of Hemadsorption Therapy in Critically Ill Patients with COVID-19 (CYTOCOV-19): A Prospective Randomized Controlled Pilot Trial

Introduction: Immunomodulatory therapies have shown beneficial effects in patients with severe COVID-19. Patients with hypercytokinemia might benefit from the removal of inflammatory mediators via hemadsorption. Methods: Single-center prospective randomized trial at the University Medical Center Hamburg-Eppendorf (Germany). Patients with confirmed COVID-19, refractory shock (norepinephrine ≥0.2 µg/kg/min to maintain a mean arterial pressure ≥65 mm Hg), interleukin-6 (IL-6) ≥500 ng/L, and an indication for renal replacement therapy or extracorporeal membrane oxygenation were included. Patients received either hemadsorption therapy (HT) or standard medical therapy (SMT). For HT, a CytoSorb® adsorber was used for up to 5 days and was replaced every 18–24 h. The primary endpoint was sustained hemodynamic improvement (norepinephrine ≤0.05 µg/kg/min ≥24 h). Results: Of 242 screened patients, 24 were randomized and assigned to either HT (N = 12) or SMT (N = 12). Both groups had similar severity as assessed by SAPS II (median 75 points HT group vs. 79 SMT group, p = 0.590) and SOFA (17 vs. 16, p = 0.551). Median IL-6 levels were 2,269 (IQR 948–3,679) and 3,747 (1,301–5,415) ng/L in the HT and SMT groups at baseline, respectively (p = 0.378). Shock resolution (primary endpoint) was reached in 33% (4/12) versus 17% (2/12) in the HT and SMT groups, respectively (p = 0.640). Twenty-eight-day mortality was 58% (7/12) in the HT compared to 67% (8/12) in the SMT group (p = 1.0). During the treatment period of 5 days, 6/12 (50%) of the SMT patients died, in contrast to 1/12 (8%) in the HT group. Conclusion: HT was associated with a non-significant trend toward clinical improvement within the intervention period. In selected patients, HT might be an option for stabilization before transfer and further therapeutic decisions. This finding warrants further investigation in larger trials.

Enrollment in public pension program and household land transfer behaviour: Evidence from rural China

ABSTRACT Although farmland transfer is a radical solution to the problem of sustainable development of the land rental market in China, there is insufficient research that attempted to quantitatively explore the determinants of land transfer behaviour, particularly the effects of enrolment in public pension programs. In this paper, we examine how enrolment in the recently established and expanded New Rural Pension Scheme (NRPS) can affect land transfer decisions among the age-eligible and age-ineligible rural residents. Specifically, our study employs balanced panel data from the first two waves of the China Family Panel Studies (CFPS) in the year 2010 and 2012. It reveals that, although the enrolment in the public pension system increases the scale of farmland transfer among age-eligible people, this effect is not shown among age-ineligible members. Moreover, for households with members over the age of 60, the positive income effects are concentrated among farmers from low-income family; for other groups, the heterogeneous outcomes are insignificant. These estimates may offer insights for the dynamic adjustments of the public pensions for the elderly population and for enhancing the vitality of land transfer in rural China.

Critically Ill COVID-19 Patients Show Reduced Point of Care-Measured Butyrylcholinesterase Activity-A Prospective, Monocentric Observational Study.

A biomarker for risk stratification and disease severity assessment in SARS-CoV-2 infections has not yet been established. Point of care testing (POCT) of butyrylcholinesterase (BChE) enables early detection of systemic inflammatory responses and correlates with disease severity in sepsis and burns. In acute care or resource-limited settings, POCT facilitates rapid clinical decision making, a particularly beneficial aspect in the management of pandemic situations. In this prospective observational study, POCT-measured BChE activity was assessed in 52 critically ill COVID-19 patients within 24 h of ICU admission and on the third and seventh day after ICU admission. Forty (77%) of these patients required venovenous extracorporeal membrane oxygenation (vvECMO). In critically ill COVID-19 patients, BChE activity is significantly decreased compared with healthy subjects, but also compared with other inflammatory conditions such as sepsis, burns, or trauma. POCT BChE activity reflects the severity of organ dysfunction and allows prediction of 28-day mortality in critically ill COVID-19 patients. Implementing early POCT BChE measurement could facilitate risk stratification and support admission and transfer decisions in resource-limited settings.

Management of Transfer Prices in Professional Football as a Function of Fan Numbers

The intention of this paper is to provide new academic insights regarding an economically explainable valuation of transfer prices for European football players based on mathematical modeling. Football is the most popular sport in the world followed by approximately 3.5 billion people. The increasing commercialization and professionalization of the industry implies that every area of a football club is constantly put to the test for improvements. Especially after suffering financially under the consequences of the worldwide pandemic, clubs focus not only on sporting success but also on financial survival. Only financially stable clubs have the resources to be more successful. An expensive team does not have to be successful in terms of sports performance. However, a successful team in sports is expensive in the long run. Increasing digitalization offers new revenue potentials for football clubs that focus on selling merchandise in addition to gameday revenues and its media exploitation rights. However, player transfers have become increasingly important because these costs and revenues increased substantially in the relevance of a club’s financial situation. Regarding transfer costs, the question arises as to how transfer fees are determined and which factors have a major influence here. Clubs try to find new ways of evaluating the potential profit of player transfers to lower the risk of failed player investments. The aim of this article is to quantify the popularity of a football player in terms of his merchandising potential to amortize his transfer price. The mathematically formulated relationship calculates a reference value for a player, taking performance, age, number of customers purchasing merchandise, and player position into account. The information gained can be used by managers of European football clubs as a guide in transfer negotiations. For 6907 players of the European top leagues, we analyzed data in the period from 2003 to 2019. For 409 players in the season of 2018/2019 complete data sets were available, so that a model for calculating a theoretical transfer fee for a player during that season could be determined. The results of the study and the developed model suggest that, based on the available data, a football club should offer either one-year or three-year contracts to a transferred player, depending on the anticipated profit margin of merchandise sales and the quota of potential buyers of the products representing a percentage of the number of customers purchasing merchandise. This information gives football club’s management the chance to make better transfer decisions for the individual situation of the player and the club itself. Due to the increased importance of transfers on a football club’s financial performance, better transfer decision making leads to an improved financial stability of the respective clubs and eventually to sporting success.

Decision Model for Unplanned ICU Transfer in a Hospital with Association Rule Learning

The initial decision after treatment in the hospital emergency room is very important because apart from being an indicator of the quality of care for emergency room practitioners, it is also needed to achieve health goals, namely improving the quality of critical care and preventing death. The initial decision was also for an unplanned ICU transfer. Unplanned ICU transfer is the transfer of patients who originally came from the ER (Emergency Room), then to the Inpatient Room (having been treated for 24-48 hours), then to the ICU. Many studies have been carried out to predict the initial decision of unplanned ICU transfer using univariate analysis, logistic regression analysis, and association rules. The association rule algorithm generates rules between patient diagnosis features that form a decision model for unplanned ICU transfers, so it is essential to get an association rule algorithm that is more efficient in generating rules. In this study, we compare two association rule algorithms to get a more efficient algorithm; then, the rules are used to form a decision model for unplanned ICU transfers. The study results obtained that the Apriori algorithm requires a completion time of 3 ms and the FP-Growth algorithm requires a completion time of 31 ms. Hence, the FP-Growth algorithm is 28 ms more efficient than the Apriori algorithm, while the resulting rule generation is the same number of 67 rules. Only 11 rules meet the minsupp and minconf threshold and include the set of Class Association Rules (CAR), which are used to form a decision model for unplanned ICU transfers with binary integer programming

Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA

AbstractBuilding continental‐scale hydrologic models in data‐sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS‐based hydrologic regions discern process differences across a data‐sparse and hydrologically diverse landscape. Process importance rankings from random forest‐derived BCs provided model‐independent information for making modeling decisions.Key points Fundamental daily streamflow statistics produce distinct hydrologic regions across Alaska, USA Distinct hydrologic processes are recognizable in the identified hydrologic regions Using basin characteristics, random forest modeling was best able to assign ungaged locations to hydrologic regions Random forest‐derived predictor importance suggests that hydroclimatic factors and permafrost presence/absence drive hydrologic region assignment

Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study.

BackgroundA clinical decision support system (CDSS) is recognized as a technology that enhances clinical efficacy and safety. However, its full potential has not been realized, mainly due to clinical data standards and noninteroperable platforms.ObjectiveIn this paper, we introduce the common data model–based intelligent algorithm network environment (CANE) platform that supports the implementation and deployment of a CDSS.MethodsCDSS reasoning engines, usually represented as R or Python objects, are deployed into the CANE platform and converted into C# objects. When a clinician requests CANE-based decision support in the electronic health record (EHR) system, patients’ information is transformed into Health Level 7 Fast Healthcare Interoperability Resources (FHIR) format and transmitted to the CANE server inside the hospital firewall. Upon receiving the necessary data, the CANE system’s modules perform the following tasks: (1) the preprocessing module converts the FHIRs into the input data required by the specific reasoning engine, (2) the reasoning engine module operates the target algorithms, (3) the integration module communicates with the other institutions’ CANE systems to request and transmit a summary report to aid in decision support, and (4) creates a user interface by integrating the summary report and the results calculated by the reasoning engine.ResultsWe developed a CANE system such that any algorithm implemented in the system can be directly called through the RESTful application programming interface when it is integrated with an EHR system. Eight algorithms were developed and deployed in the CANE system. Using a knowledge-based algorithm, physicians can screen patients who are prone to sepsis and obtain treatment guides for patients with sepsis with the CANE system. Further, using a nonknowledge-based algorithm, the CANE system supports emergency physicians’ clinical decisions about optimum resource allocation by predicting a patient’s acuity and prognosis during triage.ConclusionsWe successfully developed a common data model–based platform that adheres to medical informatics standards and could aid artificial intelligence model deployment using R or Python.

'Weighing up risks': a model of care home staff decision-making about potential resident hospital transfers.

Backgroundcare home staff play a crucial role in managing residents’ health and responding to deteriorations. When deciding whether to transfer a resident to hospital, a careful consideration of the potential benefits and risks is required. Previous studies have identified factors that influence staff decision-making, yet few have moved beyond description to produce a conceptual model of the decision-making process.Objectivesto develop a conceptual model to describe care home staff’s decision-making when faced with a resident who potentially requires a transfer to the hospital.Methodsdata collection occurred in England between May 2018 and November 2019, consisting of 28 semi-structured interviews with 30 members of care home staff across six care home sites and 113 hours of ethnographic observations, documentary analysis and informal conversations (with staff, residents, visiting families, friends and healthcare professionals) at three of these sites.Resultsa conceptual model of care home staff’s decision-making is presented. Except in situations that staff perceived to be urgent enough to require an immediate transfer, resident transfers tended to occur following a series of escalations. Care home staff made complex decisions in which they sought to balance a number of potential benefits and risks to: residents; staff (as decision-makers); social relationships; care home organisations and wider health and social care services.Conclusionsduring transfer decisions, care home staff make complex decisions in which they weigh up several forms of risk. The model presented offers a theoretical basis for interventions to support deteriorating care home residents and the staff responsible for their care.

Property rights and market participation: evidence from the land titling program in rural China

The incomplete and unstable property rights of farmland in rural China hinder the development of the nation’s farmland rental market. The Chinese government implemented a land titling program in 2008 and conducted several pilot programs in various provinces to remove the barriers resulting from ambiguous property rights. Using data from the China Health and Retirement Longitudinal Study, this paper investigates the effects of rural land titling on market participation in rural China. First, we provide novel evidence regarding the impact of land titling on land market participation and investigate the heterogeneous wealth effects and geographic locations of land rental decisions. Second, we examine the endogeneity of land titling program implementation through empirical analysis. Our results indicate that clear and well-defined farmland property rights increase land rental activities and raise rental prices. We also find a significantly negative wealth effect in land transfer decisions, indicating that land titling encourages poorer farmers to rent out farmland. Land titling is found to promote land transfer, with the strongest effect in central China, and raise rental rates, with the largest increase in western China.

Do Public Caregiving Subsidies and Supports affect the Provision of Care and Transfers?

We study whether caregiving and intergenerational transfer decisions are sensitive to changes in economic incentives following the inception of a new unconditional and universal system of allowances and supports, after the introduction of the 2006 Promotion of Personal Autonomy and Care for Dependent Persons Act (SAAD in Spanish), and the ensuing effects of its austerity cuts after 2012. We find that whilst the introduction of a caregiving allowance (of a maximum value of €530 in 2011) increased the supply of informal caregiving by 20-22 percentual points (pp), the inception of a companion system of publicly subsidised homecare supports did not modify the supply of care. Consistent with an exchange motive for intergenerational transfers, we estimate an average 17 pp (8.2-8.7pp) increase (decrease) in downstream (upstream) transfers among those receiving caregiving allowances. Our estimates resulting from the reduction in the allowances and supports after the austerity cuts in 2012 are consistent with our main estimates, and suggest stronguer effects among lower-income families.

Understanding peasant household’s land transfer decision-making: A perspective of financial literacy

This paper investigates the effect of peasant households’ financial literacy on their land transfer, using representative survey data conducted in less-developed rural regions of China (N = 1302). The empirical results show that: (1) Financial literacy significantly influences land transfer. (2) Financing condition and risk tolerance work as mediators in this relationship. (3) Land transfer decisions of households characterized as high agricultural dependence, low income, large size of arable land ownership, and female, elder, and high education decision-makers are more sensitive to financial literacy. (4) Financial literacy has a greater impact on land inflow than outflow; advanced literacy is more beneficial for land transfer than basic literacy; and consistency in subjective and objective literacy moderates the relationship between financial literacy and land transfer. Our findings could provide some implications for stimulating the development of rural land transfer markets.

Seed Menus: An integrated decision-support framework for native plant restoration in the Mojave Desert.

The combination of ecosystem stressors, rapid climate change, and increasing landscape‐scale development has necessitated active restoration across large tracts of disturbed habitats in the arid southwestern United States. In this context, programmatic directives such as the National Seed Strategy for Rehabilitation and Restoration have increasingly emphasized improved restoration practices that promote resilient, diverse plant communities, and enhance native seed reserves. While decision‐support tools have been implemented to support genetic diversity by guiding seed transfer decisions based on patterns in local adaptation, less emphasis has been placed on identifying priority seed mixes composed of native species assemblages. Well‐designed seed mixes can provide foundational ecosystem services including resilience to disturbance, resistance to invasive species, plant canopy structure to facilitate natural seedling recruitment, and habitat to support wildlife and pollinator communities. Drawing from a newly developed dataset of species distribution models for priority native plant taxa in the Mojave Desert, we created a novel decision support tool by pairing spatial predictions of species habitat with a database of key species traits including life history, flowering characteristics, pollinator relationships, and propagation methods. This publicly available web application, Mojave Seed Menus, helps restoration practitioners generate customized seed mixes for native plant restoration in the Mojave Desert based on project locations. Our application forms part of an integrated Mojave Desert restoration program designed to help practitioners identify species to include in local seed mixes and nursery stock development while accounting for local adaptation by identifying appropriate seed source locations from key restoration species.

Carbon Transfer Decision Model Based on LMDI Method.

Establishing a coordinated governance mechanism for regional carbon emissions is an essential way to achieve carbon peak and carbon neutrality, while the study of interprovincial carbon emissions transfer is one of the important foundations of regional carbon emissions coordinated governance research. Based on the multiregional input-output (MRIO) model, this study calculated the carbon emissions from both the producers' perspective and the consumers' perspective and analyzed the interprovincial net carbon emissions transfer decision. Furthermore, the logarithmic mean Divisia index (LMDI) method was adopted to decompose the factors that affect the province's net carbon emissions into technological effect, structural effect, input-output effect, and scale effect. It was revealed that the input-output effect was the primary influencing factor of the net carbon transfer at the provincial level.

Advances in numerical weather prediction, data science, and open‐source software herald a paradigm shift in catastrophe risk modeling and insurance underwriting

AbstractRecent advances in numerical weather prediction, combined with the new generation, high‐resolution climate simulations, and open‐source loss modeling frameworks, herald a move beyond the limited statistical representation of catastrophe risk based on past observations. In this new forward‐looking view of risk, an appreciation that our observed record of past natural catastrophes represents a limited sample of possible events, and that the statistics of weather and climate are changing as the planet warms, highlights a key limitation in traditional catastrophe modeling approaches that are built on defining statistical relationships using the observed record. Instead, ensembles of new spatially and dynamically consistent simulations of weather and climate provide physically plausible, but as‐yet‐unseen events at scales appropriate for making effective risk management and risk transfer decisions. This approach is especially useful in locations around the world where observational records are unobtainable or of short historical duration, such as in low‐income countries. We take a forward‐looking approach at the way that future catastrophe modeling and insurance underwriting could occur in response to these technological and scientific advances, using open‐source loss model frameworks.