Performance of NAIS

This working paper confines its scope to performance of National Agricultural Insurance Scheme (NAIS). It examines the progress of NAIS in India and in one selected state, Gujarat. The two dimensions considered are coverage over time and across the states. It is further disaggregated for different seasons. The performance was studied with respect to number of performance indicators, namely, farmers covered, area covered, sum insured, premium collected, subsidy to small farmers, claims made and farmers benefited. The state-wise performance gives the comparative picture of NAIS among the states. Detailed performance was studied for Gujarat. Again the progress was examined over time and among the districts. Though the data shows impressive growth over time it cannot be termed as satisfactory. The coverage of area as well as loanee farmers has been disappointing. The scheme has many flaws. The mandatory aspect has not been appreciated by farmers.

Crop Insurance in India

This working paper discusses the dependence of Indian agriculture on uncertain rains. In addition the farmers experience other production risks as well as marketing risks related to different crop enterprises and for different agro-climatic regions and areas. It then argues on the need for crop insurance as an alternative to manage production risk. It then takes up the historical overview of crop insurance products and their performance. It is followed by the discussion on the currently available crop insurance products for specific crops and regions. It discusses at length the two important products, namely, National Agricultural Insurance Scheme and Weather Based Insurance Scheme. It also reflects on some deficiencies in these products.

Misinformation in Healthcare Social Networks: Contributing Factors

There has been a steady increase in the amount of information published on the internet in the past ten years. In the healthcaredomain, patients are increasingly exchanging medical information on online social networks and engaging in self care as aresult. This trend has concerned many researchers who have studied and confirmed the existence of misinformation on theinternet. This research is a work in progress investigating how online social networks affect patient safety. The researchquestion is: What are the factors contributing to the amount of misinformation in healthcare social networks? In particular,this research explores the critical factors that influence the extent of misinformation about diabetes on a diabetes socialnetwork. A total of 100 discussion threads will be collected and regression techniques will be used to analyze the data

EHR Adoption and Patient Safety: The Role of EHR and Health Care Provider Characteristics

Health care providers are increasingly adopting EHR and expecting EHR to reduce medical errors and improve patient safety. However, the findings on the effect of EHR on patient safety have been mixed. In this paper, we investigate the factors moderating the relationship between EHR and patient safety. More specifically, we propose that EHR characteristics, including EHR certification, usability and privacy protection mechanism, and health care provider characteristics, including IT experience, stage of adoption, length of usage, and organization size, could influence the actual impact of EHR on patient safety

A quantitative study of colloidal fouling in membrane processes

Ph.DDOCTOR OF PHILOSOPH

A concept for a visual computer interface to make error taxonomies useful at the point of primary care

Evidence suggests that the quality of care delivered by the healthcare industry currently falls far short of its capabilities. Whilst most patient safety and quality improvement work to date has focused on inpatient settings, some estimates suggest that outpatient settings are equally important, with up to 200 000 avoidable deaths annually in the United States of America (USA) alone. There is currently a need for improved error reporting and taxonomy systems that are useful at the point of care. This provides an opportunity to harness the benefits of computer visualisation to help structure and illustrate the 'stories' behind errors. In this paper we present a concept for a visual taxonomy of errors, based on visual models of the healthcare system at both macrosystem and microsystem levels (previously published in this journal), and describe how this could be used to create a visual database of errors. In an alphatest in a US context, we were able to code a sample of 20 errors from an existing error database using the visual taxonomy. The approach is designed to capture and disseminate patient safety information in an unambiguous format that is useful to all members of the healthcare team (including the patient) at the point of care as well as at the policy-making level