Assessment of extreme heat and hospitalizations to inform early warning systems.

Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat-health early warning systems. We used a two-stage analysis to estimate heat-health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003-2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat-health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure-response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat-health early warning systems

Declining mortality following acute myocardial infarction in the Department of Veterans Affairs Health Care System

<p>Abstract</p> <p>Background</p> <p>Mortality from acute myocardial infarction (AMI) is declining worldwide. We sought to determine if mortality in the Veterans Health Administration (VHA) has also been declining.</p> <p>Methods</p> <p>We calculated 30-day mortality rates between 2004 and 2006 using data from the VHA External Peer Review Program (EPRP), which entails detailed abstraction of records of all patients with AMI. To compare trends within VHA with other systems of care, we estimated relative mortality rates between 2000 and 2005 for all males 65 years and older with a primary diagnosis of AMI using administrative data from the VHA Patient Treatment File and the Medicare Provider Analysis and Review (MedPAR) files.</p> <p>Results</p> <p>Using EPRP data on 11,609 patients, we observed a statistically significant decline in adjusted 30-day mortality following AMI in VHA from 16.3% in 2004 to 13.9% in 2006, a relative decrease of 15% and a decrease in the odds of dying of 10% per year (p = .011). Similar declines were found for in-hospital and 90-day mortality.</p> <p>Based on administrative data on 27,494 VHA patients age 65 years and older and 789,400 Medicare patients, 30-day mortality following AMI declined from 16.0% during 2000-2001 to 15.7% during 2004-June 2005 in VHA and from 16.7% to 15.5% in private sector hospitals. After adjusting for patient characteristics and hospital effects, the overall relative odds of death were similar for VHA and Medicare (odds ratio 1.02, 95% C.I. 0.96-1.08).</p> <p>Conclusion</p> <p>Mortality following AMI within VHA has declined significantly since 2003 at a rate that parallels that in Medicare-funded hospitals.</p

Costly Hospital Readmissions and Complex Chronic Illness

People with multiple chronic conditions account for a large and disproportionate share of total health care costs. One aspect of the high cost for such patients is a relatively high number of hospital admissions per year. This study aims to clarify how the rate of hospital readmissions and hospital cost per person in a year depend on a patient's number of different chronic conditions (“complexity”), severity of illness, principal diagnosis at discharge, payer group, and other variables. We use a database of all hospital discharges for adults in six states. The number of different chronic conditions has a smoothly increasing effect on readmissions and cost per year, and there are notable differences by payer group. We offer illustrations of the potential savings from reducing total inpatient cost and readmissions in narrowly targeted populations with the most complex problems. The study's methods and descriptive data potentially could be useful for health plans and their sponsors (employers, government) when they design strategies to address the high cost of complex chronic illness

Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza‐related hospitalizations in the United States

Please cite this paper as: Charland et al.(2012) Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza‐related hospitalizations in the United States. Influenza and Other Respiratory Viruses DOI: 10.1111/irv.12019. Background Findings from studies examining the association between obesity and acute respiratory infection are inconsistent. Few studies have assessed the relationship between obesity‐related behavioral factors, such as diet and exercise, and risk of acute respiratory infection. Objective To determine whether community prevalence of obesity, low fruit/vegetable consumption, and physical inactivity are associated with influenza‐related hospitalization rates. Methods Using data from 274 US counties, from 2002 to 2008, we regressed county influenza‐related hospitalization rates on county prevalence of obesity (BMI ≥ 30), low fruit/vegetable consumption (<5 servings/day), and physical inactivity (<30 minutes/month recreational exercise), while adjusting for community‐level confounders such as insurance coverage and the number of primary care physicians per 100 000 population. Results A 5% increase in obesity prevalence was associated with a 12% increase in influenza‐related hospitalization rates [adjusted rate ratio (ARR) 1·12, 95% confidence interval (CI) 1·07, 1·17]. Similarly, a 5% increase in the prevalence of low fruit/vegetable consumption and physical inactivity was associated with an increase of 12% (ARR 1·12, 95% CI 1·08, 1·17) and 11% (ARR 1·11, 95% CI 1·07, 1·16), respectively. When all three variables were included in the same model, a 5% increase in prevalence of obesity, low fruit/vegetable consumption, and physical inactivity was associated with 6%, 8%, and 7% increases in influenza‐related hospitalization rates, respectively. Conclusions Communities with a greater prevalence of obesity were more likely to have high influenza‐related hospitalization rates. Similarly, less physically active populations, with lower fruit/vegetable consumption, tended to have higher influenza‐related hospitalization rates, even after accounting for obesity