Development of a magnetic particle immunoassay for polybrominated diphenyl ethers and application to environmental and food matrices.

A sensitive magnetic particle enzyme-linked immunoassay (ELISA) was developed to analyze polybrominated diphenyl ethers (PBDEs) in water, milk, fish, and soil samples. The assay was rapid and can be used to analyze fifty samples in about 1h after sample cleanup. The assay has a limit of detection (LOD) below 0.1 ppb towards the following brominated diphenyl ether (BDE) congeners: BDE-47, BDE-99, BDE-28, BDE-100, and BDE-153, with the LOD approximately the same as GC-NCI-MS. The congeners most readily recognized in the ELISA were BDE-47 and BDE-99 with the cross-reactivities of BDE-28, BDE-100, and BDE-153 being less than 15% relative to BDE-47. As anticipated, the sensitivities are proportional to the similarities between the hapten structure and the BDE congener structure. Some oxygenated congeners with structural similarity to the hapten showed high to moderate cross-reactivities. Very low cross-reactivity was observed for other PBDEs or chlorinated environmental contaminants. The assay gave good recoveries of PBDEs from spiked water samples and a very small within and between day variance. Comparison with GC-NCI-MS demonstrated the ELISA method showed equivalent precision and sensitivity, with better recovery. The lower recovery of the GC-NCI-MS method could be caused by the use of an internal standard other than an isotopically substituted material that could not be used because of the fragmentation pattern observed by this method. The cleanup methods prior to ELISA were matrix dependent, no pretreatment was needed for environmental water samples, while fish, milk, and soil samples required various degrees of cleanup. Analysis of this wide variety of environmental samples by both ELISA and GC-MS demonstrated ELISA provides a timely and cost-effective method to screen for PBDEs in a variety of samples.

Does patient activation predict the course of type 2 diabetes? A longitudinal study.

OBJECTIVE: To examine whether patient activation is predictive of the course of diabetes over a three year period among patients with and without diabetes. METHODS: Longitudinal analyses utilized electronic health record data from 2011 to 2014. We examined how the patient activation measure (PAM) was predictive of 2014 diabetes-related outcomes among patients with diabetes (n=10,071); pre-diabetes (n=1804); and neither diabetes nor pre-diabetes (n=46,402). Outcomes were clinical indicators (blood pressure, cholesterol, and trigylcerides), costly utilization, and progression from no diabetes to pre-diabetes or diabetes. RESULTS: Higher PAM level predicted better clinical indicator control in patients with diabetes. In patients with pre-diabetes, PAM level predicted better clinical indicator control, and those in the highest level of PAM in 2011 had lower odds of having a hospitalization compared to those in the lowest level. In patients without diabetes or pre-diabetes in 2011, higher PAM level was associated with lower odds of developing pre-diabetes. CONCLUSIONS: More activated patients with diabetes and pre-diabetes had better outcomes than less activated patients. More activated patients without diabetes or pre-diabetes were less likely to develop pre-diabetes over a three year period. PRACTICE IMPLICATIONS: Strategies to improve patient activation may be useful to help curb the diabetes epidemic.

Adding A Measure Of Patient Self-Management Capability To Risk Assessment Can Improve Prediction Of High Costs.

We explored whether supplementing a clinical risk score with a behavioral measure could improve targeting of the patients most in need of supports that reduce their risk of costly service utilization. Using data from a large health system that determines patient self-management capability using the Patient Activation Measure, we examined utilization of hospital and emergency department care by the 15 percent of patients with the highest clinical risk scores. After controlling for risk scores and placing patients within segments based on their level of activation in 2011, we found that the lower the activation level, the higher the utilization and cost of hospital services in each of the following three years. These findings demonstrate that adding a measure of patient self-management capability to a risk assessment can improve prediction of high care costs and inform actions to better meet patient needs.

When patient activation levels change, health outcomes and costs change, too.

Patient engagement has become a major focus of health reform. However, there is limited evidence showing that increases in patient engagement are associated with improved health outcomes or lower costs. We examined the extent to which a single assessment of engagement, the Patient Activation Measure, was associated with health outcomes and costs over time, and whether changes in assessed activation were related to expected changes in outcomes and costs. We used data on adult primary care patients from a single large health care system where the Patient Activation Measure is routinely used. We found that results indicating higher activation in 2010 were associated with nine out of thirteen better health outcomes-including better clinical indicators, more healthy behaviors, and greater use of women's preventive screening tests-as well as with lower costs two years later. Changes in activation level were associated with changes in over half of the health outcomes examined, as well as costs, in the expected directions. These findings suggest that efforts to increase patient activation may help achieve key goals of health reform and that further research is warranted to examine whether the observed associations are causal.

Tax levy financing for local public health: fiscal allocation, effort, and capacity.

BACKGROUND: Local health departments (LHDs) rely on a wide variety of funding sources, and the level of financing is associated with both LHD performance in essential public health services and population health outcomes. Although it has been shown that funding sources vary across LHDs, there is no evidence regarding the relationship between fiscal allocation (local tax levy); fiscal effort (tax capacity); and fiscal capacity (community wealth). PURPOSE: The purpose of this study is to analyze local tax levy support for LHD funding. Three research questions are addressed: (1) What are tax levy trends in LHD fiscal allocation? (2) What is the role of tax levy in overall LHD financing? and (3) How do local community fiscal capacity and fiscal effort relate to LHD tax levy fiscal allocation? METHODS: This study focuses on 74 LHDs eligible for local tax levy funding in Minnesota. Funding and expenditure data for 5 years (2006 to 2010) were compiled from four governmental databases, including the Minnesota Department of Health, the State Auditor, the State Demographer, and the Metropolitan Council. Trends in various funding sources and expenditures are described for the time frame of interest. Data were analyzed in 2012. RESULTS: During the 2006-2010 time period, total average LHD per capita expenditures increased 13%, from $50.98 to $57.63. Although the overall tax levy increase in Minnesota was 25%, the local tax levy for public health increased 5.6% during the same period. There is a direct relationship between fiscal effort and LHD expenditures. CONCLUSIONS: Local funding reflects LHD community priorities and the relative importance in comparison to funding other local programs with tax dollars. In Minnesota, local tax levy support for local public health services is not keeping pace with local tax support for other local government services. These results raise important questions about the relationship between tax levy resource effort, resource allocation, and fiscal capacity as they relate to public health spending in local communities.