709 research outputs found

    Input-Output Analysis with Public Policy Objectives: A Case Study of the Georgia Cotton Industry

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    Farm bill legislation directed at agricultural commodities contributes to economies of rural areas. This research quantifies the economic impacts of the Georgia cotton industry for the U.S. economy. A cotton industry model with cotton and peanut acreage is utilized with IMPLAN to estimate impacts. The Georgia cotton industry creates 4% more tax revenues for federal, state, and local governments than it receives in commodity support payments. Stochastic simulation analysis indicates that the Georgia cotton industry is not likely to remain viable without government payments.economic impact, FSRI, IMPLAN, industry model, multivariate empirical distribution, Simetar, social welfare analysis, stochastic simulation, Agribusiness, Research and Development/Tech Change/Emerging Technologies,

    Government Payments: Economic Impact on Southeastern Peanut Farms

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    Southeastern peanut farms with diversified field crops utilize government payments to supplement market receipts. Production in 2002 represented growing conditions under adverse weather, while 2003 represented optimal conditions. Representative farm analysis provides insight into allocation of market receipts and government payments for meeting variable costs and fixed costs.Crop Production/Industries,

    Siblings by Choice: Race, Gender and Violence (St. Louis, MO: Chalice Press, 2004)

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    Reviewed by Laurie Garrett-Cobbina

    Crop Rotations and Dynamic Analysis of Southeastern Peanut Farms

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    Agricultural policy objectives provide green payment incentives for farmers to initiate practices with environmental benefits. Velvet beans planted as a cover crop offer an alternative for southeastern peanut farmers to control nematodes without chemicals, while increasing soil fertility. Commodity programs provide government payments that are essential to rural economies of the southeast.Environmental Economics and Policy,

    Major inpatient surgeries and in-hospital mortality in New South Wales public hospitals in Australia: A state-wide retrospective cohort study

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    BACKGROUND Surgical interventions save lives and are important focus for health services research worldwide. Investigating variation in postoperative mortality may improve understanding of unwarranted variations and promote safety and quality in surgical care. We aimed to evaluate trends of in-hospital mortality rates among adult inpatients receiving major elective surgeries and determine the variation in mortality among New South Wales (NSW) public hospitals. MATERIALS AND METHODS In this study, we used the all-inclusive population-based NSW Admitted Patient Data from July 2001 to June 2014. We retrospectively included adult patients aged 18 + years receiving Abdominal Aortic Aneurysm (AAA) repair, Peripheral bypass, Colorectal surgeries, Joint replacement, Spinal surgeries, or Cardiac surgeries. The primary outcome was in-hospital mortality for selected surgeries. Changes in mortality rates over time and hospital standardised mortality rates were modelled using multivariate logistic regression models adjusting for case-mix factors. RESULTS Over 13-year study period, the in-hospital mortality rates declined annually by 6.4% (95% Confidence Interval (CI): 4.3, 8.4) for Colorectal surgery by 5.7% (95%CI: 2.0, 9.3) for Joint replacement and by 4.2% (95%CI: 1.9, 6.4) for Cardiac surgery. After controlling for patient-level factors, little variation was observed among hospitals for in-hospital mortality. There was a greater variability for cardiac surgery compared with the other surgical groups but no outlier hospital was consistently associated with significantly higher than expected mortality rate. CONCLUSIONS Mortality has declined for major surgeries in the past 15 years. There was some variation among hospitals regarding in-hospital mortality that was mostly explained by patients demographic and admission characteristics. Our findings are reassuring for patients and contribute to knowledge that can help further improve surgical care

    Hospital effect on infections after four major surgeries: Outlier and volume-outcome analysis using all-inclusive state data

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    Hospital volume is known to have a direct impact on outcomes of major surgeries. However, it is unclear if the evidence applies specifically to surgical site infections. To determine if there are procedure-specific hospital outliers (with higher surgical site infection rates [SSIR]) for four major surgical procedures, and to examine if hospital volume is associated with SSIR in the context of outlier performance in New South Wales (NSW), Australia. Adults who underwent one of four surgical procedures (colorectal, joint replacement, spinal and cardiac procedures) at a NSW healthcare facility from 2002 through 2013 were included. The hospital volume for each of the four surgical procedures was categorised into tertiles (low, medium and high). Multivariable logistic regression models were built to estimate the expected SSIR for each procedure. The expected SSIR were used to compute an indirect standardised SSIR which was then plotted in funnel plots to identify hospital outliers. One hospital was identified to be an overall outlier (higher SSIR for 3 out of the 4 procedures performed in its facilities); whereas two hospitals were outliers for one specific procedure throughout the entire study period. Low-volume facilities performed the best for colorectal surgery and worst for joint replacement and cardiac surgery. One high-volume facility was an outlier for spinal surgery. Surgical site infections seem to be mostly a procedure-specific as opposed to a hospital-specific phenomenon in NSW. The association between hospital volume and SSIRs differs for different surgical procedures.ACAC is funded by an Australian National Health and Medical Research Council Senior Research Fellowship (#1058878)
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