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Background: COVID-19 was declared pandemic by WHO on 30th January 2020 and to cure it, No specific antiviral treatment has been developed yet, therefore only preventive measures such as; facemask, regular hand washing, social as well as physical distancing, respiratory etiquettes and vaccination against Covid-19, are proven methods of its control and prevention. Objectives: To study the knowledge, Attitude and Practices among people about COVID-19 vaccine and find out various socio-demographic factors for its decision making. Material &Methods: A descriptive cross sectional study was conducted among the persons attended the tertiary care center to get vaccine against COVID-19 at Government Medical College, Badaun, UP. Results: Out of all respondents, majority (77.2%) of them accepted to get the vaccine as soon as available. 81.5% of respondents were male and more than half (60%) of them were unmarried. More than three fourth (77.5%) of respondents were unemployed and nearly one third (32%) belonged to BPL category. As per study, majority of respondents (86%) and (71.8%) said that vaccine is safe and effective way to control and prevent COVID-19, respectively.(77.2%)respondents who accepted that vaccine should be taken as soon as available, more than half (57%) of them said that doctor's recommendation is an important factor in vaccination decision-making.Conclusion: The most important factor for vaccine hesitancy is the occurrence of mild to moderate adverse effects following immunization, and this may be the biggest challenge in the global response against the Covid-19 pandemic.
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Background: Rajiv Aarogyasri has covered 86.53% of the families across the state. Majority of its people are living in rural areas. Hence, our study will explore gaps in accessibility of urban centric health services by rural policyholder’s under the scheme. To find out the current status of Aarogyasri coverage, awareness, utilization and experiences of rural policyholders in Chittoor district of Andhra Pradesh during the year 2014-15.Methods: This is a cross-sectional quantitative study and a total of 200 households were surveyed by using multi-stage random sampling technique to obtain primary data, and for background & discussion secondary data was reviewed. SPSS software was used for data analysisResults: In the past one year, 6.77% of the families have received benefits under the scheme. Amongst the ones who have utilized RAS services, 2/3rd of the families were protected from catastrophic illnesses and the mean average of 91.70% of the total costs was covered by RAS. Another 19.21% of the families were in need of healthcare but did not utilize the services due to lack of RAS card, lack of awareness, non-listed therapies, procedural difficulty, non-availability of caretaker, loss of wage and low quality of services.Conclusions: Overall, 66.66% of the beneficiaries expressed their satisfaction, 16.66% opinionated fair while 16.66% were dissatisfied with the RAS services. Beneficiaries experienced shortage of supportive services in Government hospitals under the scheme. Further, IEC activities, alternatives for excluded conditions, strengthening of public facilities will improve the utilization of RAS and reduce the OOPE.
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Background: RSBY, a health insurance scheme, was launched by the Indian government to protect BPL families from incurring financial liabilities which are likely to occur due to hospitalization. Objectives was to compare over all OOPE among RSBY beneficiaries and non-beneficiaries and to estimate its extent during hospitalization in different domains among RSBY beneficiaries and non-beneficiaries.Methods: It was a cross-sectional study conducted for 2 months (January-February 2018) among BPL families residing in Ganjam district, Odisha. Multistage random sampling was done. Total sample size was 256, the number of beneficiaries and non beneficiaries taken was 128 each.Results: Non beneficiaries incurred higher overall OOPE higher i.e. 95.3% than the Beneficiaries and it was found to be statistically significant with x²=74.8 and P-value <0.001. Among beneficiaries out of pocket expenditure was found in 46.1% of the study population. 45.3% of beneficiaries had to borrow partially from friends and relatives to fulfil their hospital related expenses followed by 32% borrowing fully for their treatment. Among beneficiaries, most out of pocket expenditure was for life support services as they sought treatment mostly for surgical conditions.Conclusions: Health insurance coverage should be improved by increasing enrolment. People should be made aware about the services covered under the schemes.
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PURPOSE: Recently, a new Bayesian Penalized Likelihood (BPL) Reconstruction Algorithm was introduced by GE Healthcare, Q.Clear; it promises to provide better PET image resolution compared to the widely used Ordered Subset Expectation Maximization (OSEM). The aimof this study is to compare the performance of these two algorithms on several types of findings, in terms of image quality, lesion detectability, sensitivity, and specificity.METHODS: Between September 6th 2017 and July 31st 2018, 663 whole body 18F-FDG PET/CT scans were performed at the Nuclear Medicine Department of S. Martino Hospital (Belluno, Italy). Based on the availability of clinical/radiological follow-up data, 240 scans were retrospectively reviewed. For each scan, a hypermetabolic finding was selected, reporting both for OSEM and Q.Clear: SUVmax and SUVmean values of the finding, the liver and the background close to the finding; size of the finding; percentage variations of SUVmax and SUVmean. Each finding was subsequently correlated with clinical and radiological follow-up, to define its benign/malignant nature.RESULTS: Overall, Q.Clear improved the SUVvalues in each scan, especially in small findings (< 10mm), high SUVmax values (≥ 10), and medium/low backgrounds. Furthermore, Q.Clear amplifies the signal of hypermetabolic findings without modifying the background signal, which leads to an increase in signal-to-noise ratio, improving overall image quality. Finally, Q.Clear did not affect PET sensitivity or specificity, in terms of number of reported findings and characterization of their nature.CONCLUSIONS: Q.Clear is an iterative algorithm that improves significantly the quality of PET images compared to OSEM, increasing the SUVmax of findings (in particular for small findings) and the signal-to-noise ratio. However, due to the intrinsic characteristics of this algorithm, it will be necessary to adapt and/or modify the current interpretative criteria based of quantitative evaluation, to avoid an overestimation of the disease burden.
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Delivery of Health Care , Evaluation Studies as Topic , Fluorodeoxyglucose F18 , Follow-Up Studies , Liver , Nuclear Medicine , Positron Emission Tomography Computed Tomography , Retrospective Studies , Sensitivity and Specificity , Signal-To-Noise RatioABSTRACT
Background: Government -year pilot project in December 2005 in five backward districts (Banaskantha, Dahod, Kutch, Panchmahals, and Sabarkantha). The scheme has now been extended to the entire state. Aims & Objective: ; (2) Reasons for not utilizing the ; (3) Problems faced in the utilization as perceived by the beneficiaries. Material and Methods: A total of 116 BPL families selected by Simple random sampling (SRS) method were included in the present study. All females of 15-49 years of age group and one male person who is the Head of Family were taken from each of the family. Results: Out of total 268 subjects, only 88 ( 32.84%) subjects were aware about Out of them 56 were females and 32 were head of the family males. A total of 46 out of 152 (30.26%) females utilized the benefits of is a significant association between education and knowledge regarding ‘Yojana’. The reasons for non-utilization was unawareness about the procedural aspects of registration and availing the benefits, the types of services covered under the yojana and the misconception that they have to pay additional charges also. Conclusion: Most of the participants who were actually the beneficiaries of the scheme were unaware of ‘Chiranjeevi Scheme’. IEC activities with emphasis on Government programs focusing on maternal and child health should be strengthened.
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Background & objectives: In 2008, India’s Labour Ministry launched a hospital insurance scheme called Rashtriya Swasthya Bima Yojana (RSBY) covering ‘Below Poverty Line’ (BPL) households. RSBY is implemented through insurance companies; premiums are subsidized by Union and States governments (75 : 25%). We examined RSBY’s enrolment of BPL, costs vs. budgets and policy ramifications. Methods: Numbers of BPL are obtained by following criteria of two committees appointed for this task. District-specific premiums are weighted to obtain national average premiums. Using the BPL estimates and national premiums, we calculated overall expected costs of full roll-out of the RSBY per annum, and compared it to Union government budget allocations. Results: By March 31, 2011, RSBY enrolled about 27.8 per cent of the number of BPL households following the Tendulkar Committee estimates (37.6% following the Lakdawala Committee criteria). The average national weighted premium was ` 530 per household per year in 2011. The expected cost of premium to the union government of enrolling the entire BPL population in financial year (FY) 2010-11 would be ` 33.5 billion using Tendulkar count of BPL (or ` 24.6 billion following Lakdawala count), representing about 0.3 per cent (or 0.2%, respectively) of the total union budget. The RSBY budget allocation for FY 2010-11 was only about 0.037 per cent of the total union budget, sufficient to pay premiums of only 34 per cent of the BPL households enrolled by March 31, 2011. Interpretation & conclusions: RSBY could be the platform for universal health insurance when (i) the budget allocation will match the required funds for maintenance and expansion of the scheme; (ii) the scheme would ensure that beneficiaries’ rights are legally anchored; and (iii) RSBY would attract large numbers of premiumpaying (non-BPL) households.