Impacts of a Standing Disaster Payment Program on U.S. Crop Insurance

This research investigates the potential effects of the standing disaster assistance program proposed in the Senate version of the 2008 Farm Bill. Results suggest no significant impact on producer crop insurance purchase decisions. Payments under the program should be expected to differ considerably across geographic regions and levels of diversification, with the program providing the greatest benefit to undiversified producers in more risky production regions (e.g., the Southern Plains).

Impacts of the SURE Standing Disaster Assistance Program on Producer Risk Management and Crop Insurance Programs

This research investigates the potential effects of the row crop provisions of the standing disaster assistance program (SURE) in the 2008 Farm Bill. Results suggest little impact on producer crop insurance purchase decisions, though the program does seem to provide an incentive for mid-level coverage. Payments under the program should be expected to differ considerably across geographic regions and levels of diversification, with the program providing the greatest benefit to undiversified producers in more risky production regions.crop insurance, disaster assistance, Farm Bill, SURE, Agricultural and Food Policy, Farm Management, Risk and Uncertainty, Q12, Q18,

Which comorbid conditions should we be analyzing as risk factors for healthcare-associated infections?

OBJECTIVETo determine which comorbid conditions are considered causally related to central-line associated bloodstream infection (CLABSI) and surgical-site infection (SSI) based on expert consensus.DESIGNUsing the Delphi method, we administered an iterative, 2-round survey to 9 infectious disease and infection control experts from the United States.METHODSBased on our selection of components from the Charlson and Elixhauser comorbidity indices, 35 different comorbid conditions were rated from 1 (not at all related) to 5 (strongly related) by each expert separately for CLABSI and SSI, based on perceived relatedness to the outcome. To assign expert consensus on causal relatedness for each comorbid condition, all 3 of the following criteria had to be met at the end of the second round: (1) a majority (&gt;50%) of experts rating the condition at 3 (somewhat related) or higher, (2) interquartile range (IQR)≤1, and (3) standard deviation (SD)≤1.RESULTSFrom round 1 to round 2, the IQR and SD, respectively, decreased for ratings of 21 of 35 (60%) and 33 of 35 (94%) comorbid conditions for CLABSI, and for 17 of 35 (49%) and 32 of 35 (91%) comorbid conditions for SSI, suggesting improvement in consensus among this group of experts. At the end of round 2, 13 of 35 (37%) and 17 of 35 (49%) comorbid conditions were perceived as causally related to CLABSI and SSI, respectively.CONCLUSIONSOur results have produced a list of comorbid conditions that should be analyzed as risk factors for and further explored for risk adjustment of CLABSI and SSI.Infect Control Hosp Epidemiol 2017;38:449–454</jats:sec

AN INTERACTIVE ILLUSTRATION OF FARM PROGRAM PROVISIONS

Explaining the details and the impacts of government program provisions to agricultural producers can be a challenge for extension educators. This paper introduces a visual interactive tool that demonstrates the calculations of government payments established in the 2002 farm bill. Additionally, the paper explains how the tool is created in Microsoft® Excel and may be used in other areas.Agricultural and Food Policy,

The effect of adding comorbidities to current centers for disease control and prevention central-line–associated bloodstream infection risk-adjustment methodology

BACKGROUNDRisk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.METHODSUsing a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.RESULTSOverall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.CONCLUSIONSOur risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.Infect Control Hosp Epidemiol 2017;38:1019–1024</jats:sec

Representative Farms Economic Outlook for the November 2002 FAPRI/AFPC Baseline

The farm level economic impacts of the Farm Security and Rural Investment Act of 2002 on representative crop and livestock operations are projected in this report. The analysis was conducted over the 2001-2007 planning horizon using FLIPSIM, AFPC’s whole farm simulation model. Data to simulate farming operations in the nation’s major production regions came from two sources: - Producer panel cooperation to develop economic information to describe and simulate representative crop, livestock, and dairy farms. - Projected prices, policy variables, and input inflation rates from the Food and Agricultural Policy Research Institute (FAPRI) November 2002 Baseline. The FLIPSIM policy simulation model incorporates the historical risk faced by farmers for prices and production. This report presents the results of the November 2002 Baseline in a risk context using selected simulated probabilities and ranges for annual net cash farm income values. The probability of a farm experiencing annual cash flow deficits and the probability of a farm losing real net worth are included as indicators of the cash flow and equity risks facing farms through the year 2007.Agribusiness, Agricultural and Food Policy, Crop Production/Industries,

Preliminary - Representative Farm Analysis of House of Representatives Draft Concept Paper for 2002 Farm Bill

Agricultural and Food Policy,