An Evaluation of Current Government Reinsurance Program and Its Improvement Strategies for Crop Insuranc

2017 ◽  
Vol 58 (2) ◽  
pp. 21-48
Author(s):  
Sujin Kang ◽  
Wonho Chung
2019 ◽  
Vol 62 (0) ◽  
pp. 56-63
Author(s):  
Laura Silvia Hernández Gutiérrez ◽  
Angélica García-Gómez ◽  
Argimira Vianey Barona Nuñez ◽  
Erick López Léon

The education based on simulation is an educationalstrategy where students learn from their errors, developing skills, knowledge, competences,etc. in a controlled environment. During the process of teaching by simulation, it is necessaryto execute various types of assessments (diagnostic, summative, formative) in order tomake adjustments or changes in the educational process of the students, therefore identifying areas of opportunity for improvement. With the simulation, different processes can be taught, like interprofessionalism and collaborative work. Nowadays, there is a major concern for added safety and the quality of care for the patients and their families. Therefore, a WHO study group determined the basic interprofessional competences, and has been given the task of disseminating and promoting interprofessional education. Some educational institutions in the US, Canada and Europe have integrated interprofessional and collaborative work in simulation practices. All the activity by simulation must be evaluated in order to provide feedback to the participants and establish improvement strategies. The assessment of the interprofessional work focuses on the evaluation of common skills and competencies among various health professionals.


2020 ◽  
pp. archdischild-2020-319130
Author(s):  
Yincent Tse ◽  
David Tuthill

ObjectivesTo estimate the incidence, characteristics and outcomes of 10-fold or greater or a tenth or less medication errors in children aged <16 years in Wales.DesignPopulation-based surveillance study July 2017 to June 2019. Cases were identified by paediatricians and hospital pharmacists using monthly electronic Welsh Paediatric Surveillance Unit (WPSU) reporting system.Patients‘Definite’ incident occurred when children received all or any of the incorrect dose of medication. ‘Near miss’ was where the prescribed, prepared or dispensed medication was not administered to the child.Main outcome measuresIncidence, patient characteristics, setting, drug characteristics, outcome, harm and enabling or preventive factors.ResultsIn total, 50 10-fold errors were reported; 20 definite and 30 near miss cases. This yields a minimum annual incidence of 1 per 3797 admissions, or 4.6/100 000 children. Of these, 43 were overdoses and 7 underdoses. 33 incidents occurred in children <5 years of age. Overall, 37 different medications were involved with the majority, 31 cases, being administered enterally. Of these 31 enteral medication errors, all definite cases (10) had received liquid preparations. Temporary harm occurred in 5/20 (25%) definite cases with one requiring intensive care; all fully recovered.ConclusionsIn this first ever population surveillance study in a high-resource healthcare system, 10-fold errors in children were rare, sometimes prevented and uncommonly caused harm. We recommend country-wide improvements be made to reduce iatrogenic harm. Understanding the enabling and preventive factors may help national improvement strategies to reduce these errors.


Author(s):  
Mark Cooper ◽  
Kai P. Voss-Fels ◽  
Carlos D. Messina ◽  
Tom Tang ◽  
Graeme L. Hammer

Abstract Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.


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