Tracking Spending Among Commercially Insured Beneficiaries Using a Distributed Data Model

T imely, local data are important to policy-makers, providers, patients, payers, and employers working to slow the growth of healthcare spending, which is a major focus of federal, state, and local healthcare reform initiatives. Community-based multistakeholder coalitions have formed across the country in an effort to influence their local healthcare markets and reduce costs. More than 40 percent of people in the United States live in a community with a multistakeholder coalition aimed at improving health and healthcare, including collaboratives focused on improving the exchange of health information, accelerating engagement by key local opinion leaders and stakeholders, or promoting quality improvement. 1 All of these entities, however, lack the local data needed to determine if their efforts are making a difference. The factors contributing to rising healthcare spending differ across communities and depend on local context; understanding the drivers of local spending growth is complicated by the variety of inputs. Provider culture and supply, various market segments (outpatient, inpatient, long-term care), payer mix, regulation, and the competitiveness of hospital and physician markets all affect pricing, utilization, and ultimately, the total cost of care. Research has shown that the relative contribution of these factors varies across markets and that drivers of commercial spending are not necessarily the same as drivers of Medicare spending. Chernew et al found that commercial spending was not correlated with Medicare spending across hospital referral regions. ABSTRACT Objectives To explore the feasibility of using a distributed data model for ongoing reporting of local healthcare spending, specifically to investigate the contribution of utilization and pricing to geographic variation and trends in reimbursements for commercially insured beneficiaries younger than 65 years. Study Design Retrospective descriptive analysis. Methods Commercial claims were obtained for beneficiaries in 5 states for the years 2008 to 2010 using a distributed data model. Claims were aggregated to the hospital service area (HSA) level and healthcare utilization was quantified using a novel, National Quality Forum-endorsed measure that is independent of price and allows for the calculation of resource use across all services in standardized units. We examined trends in utilization, prices, and reimbursements over time. To examine geographic variation, we mapped resource use by HSA in the 3 states from which we had data from multiple insurers. We calculated the correlation between commercial and Medicare reimbursements and utilization. Medicare claims were obtained from the Dartmouth Atlas

Shortfalls and Solutions for Meeting National and Global Conservation Area Targets

Governments have committed to conserving 17% of terrestrial and 10% of marine environments globally, especially “areas of particular importance for biodiversity” through “ecologically representative” Protected Area (PA) systems or other “area-based conservation measures”, while individual countries have committed to conserve 3–50% of their land area. We estimate that PAs currently cover 14.6% of terrestrial and 2.8% of marine extent, but 59–68% of ecoregions, 77–78% of important sites for biodiversity, and 57% of 25,380 species have inadequate coverage. The existing 19.7 million km2 terrestrial PA network needs only 3.3 million km2 to be added to achieve 17% terrestrial coverage. However, it would require nearly doubling to achieve, costefficiently, coverage targets for all countries, ecoregions, important sites, and species. Poorer countries have the largest relative shortfalls. Such extensive and rapid expansion of formal PAs is unlikely to be achievable. Greater focus is therefore needed on alternative approaches, including community- and privately managed sites and other effective area-based conservation measures.We are grateful to the many individuals and organizations who contribute to the IUCN Red List of Threatened Species,WDPA, or to identification of IBAs or AZEs. We thank A. Bennett for help with data collation and N. Dulvy, W. Laurance, and D. Faith for helpful comments on an earlier draft. This work was supported by the Cambridge Conservation Initiative Collaborative Fund and Arcadia.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/conl.1215

Investigating locally relevant risk factors for Campylobacter infection in Australia: Protocol for a case-control study and genomic analysis

Introduction The CampySource project aims to identify risk factors for human Campylobacter infection in Australia. We will investigate locally relevant risk factors and those significant in international studies in a case-control study. Case isolates and contemporaneous isolates from food and animal sources will be sequenced to conduct source attribution modelling, and findings will be combined with the case-control study in a source-assigned analysis. Methods and analysis The case-control study will include 1200 participants (600 cases and 600 controls) across three regions in Australia. Cases will be recruited from campylobacteriosis notifications to health departments. Only those with a pure and viable Campylobacter isolate will be eligible for selection to allow for whole genome sequencing of isolates. Controls will be recruited from notified cases of influenza, frequency matched by sex, age group and geographical area of residence. All participants will be interviewed by trained telephone interviewers using a piloted questionnaire. We will collect Campylobacter isolates from retail meats and companion animals (specifically dogs), and all food, animal and human isolates will undergo whole genome sequencing. We will use sequence data to estimate the proportion of human infections that can be attributed to animal and food reservoirs (source attribution modelling), and to identify spatial clusters and temporal trends. Source-assigned analysis of the case-control study data will also be conducted where cases are grouped according to attributed sources. Ethics and dissemination Human and animal ethics have been approved. Genomic data will be published in online archives accompanied by basic metadata. We anticipate several publications to come from this study

First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ

Parrots Eat Nutritious Foods despite Toxins

Generalist herbivores are challenged not only by the low nitrogen and high indigestibility of their plant foods, but also by physical and chemical defenses of plants. This study investigated the foods of wild parrots in the Peruvian Amazon and asked whether these foods contain dietary components that are limiting for generalist herbivores (protein, lipids, minerals) and in what quantity; whether parrots chose foods based on nutrient content; and whether parrots avoid plants that are chemically defended.We made 224 field observations of free-ranging parrots of 17 species in 8 genera foraging on 102 species of trees in an undisturbed tropical rainforest, in two dry seasons (July-August 1992-1993) and one wet season (January-February1994). We performed laboratory analyses of parts of plants eaten and not eaten by parrots and brine shrimp assays of toxicity as a proxy for vertebrates. Parrots ate seeds, fruits, flowers, leaves, bark, and insect larvae, but up to 70% of their diet comprised seeds of many species of tropical trees, in various stages of ripeness. Plant parts eaten by parrots were rich in protein, lipid, and essential minerals, as well as potentially toxic chemicals. Seeds were higher than other plant materials in protein and lipid and lower in fiber. Large macaws of three species ate foods higher in protein and lipids and lower in fiber compared to plant parts available but not eaten. Macaws ate foods that were lower in phenolic compounds than foods they avoided. Nevertheless, foods eaten by macaws contained measurable levels of toxicity. Macaws did not appear to make dietary selections based on mineral content.Parrots represent a remarkable example of a generalist herbivore that consumes seeds destructively despite plant chemical defenses. With the ability to eat toxic foods, rainforest-dwelling parrots exploited a diversity of nutritious foods, even in the dry season when food was scarce for other frugivores and granivores

Equine penile squamous cell carcinoma: expression of biomarker proteins and EcPV2

Equine penile squamous cell carcinoma (EpSCC) is a relatively common cutaneous neoplasm with a poor prognosis. In this study, we aimed to determine the protein expression and colocalisation of FRA1, c-Myc, Cyclin D1, and MMP7 in normal (NT), tumour (T), hyperplastic epidermis and/or squamous papilloma (Hyp/Pap), poorly-differentiated (PDSCC), or well-differentiated (WDSCC) EpSCC using a tissue array approach. Further objectives were to correlate protein expression to (i) levels of inflammation, using a convolutional neural network (ii) equine papillomavirus 2 (EcPV2) infection, detected using PCR amplification. We found an increase in expression of FRA1 in EpSCC compared to NT samples. c-Myc expression was higher in Hyp/Pap and WDSCC but not PDSCC whereas MMP7 was reduced in WDSCC compared with NT. There was a significant increase in the global intersection coefficient (GIC) of FRA1 with MMP7, c-Myc, and Cyclin D1 in EpSCC. Conversely, GIC for MMP7 with c-Myc was reduced in EpSCC tissue. Inflammation was positively associated with EcPV2 infection in both NT and EpSCC but not Hyp/Pap. Changes in protein expression could be correlated with EcPV2 for Cyclin D1 and c-Myc. Our results evaluate novel biomarkers of EpSCC and a putative correlation between the expression of biomarkers, EcPV2 infection and inflammation

A laboratory study of anisotropic geomaterials incorporating recent micromechanical understanding

This paper presents an experimental investigation revisiting the anisotropic stress–strain–strength behaviour of geomaterials in drained monotonic shear using hollow cylinder apparatus. The test programme has been designed to cover the effect of material anisotropy, preshearing, material density and intermediate principal stress on the behaviour of Leighton Buzzard sand. Experiments have also been performed on glass beads to understand the effect of particle shape. This paper explains phenomenological observations based on recently acquired understanding in micromechanics, with attention focused on strength anisotropy and deformation non-coaxiality, i.e. non-coincidence between the principal stress direction and the principal strain rate direction. The test results demonstrate that the effects of initial anisotropy produced during sample preparation are significant. The stress–strain–strength behaviour of the specimen shows strong dependence on the principal stress direction. Preloading history, material density and particle shape are also found to be influential. In particular, it was found that non-coaxiality is more significant in presheared specimens. The observations on the strength anisotropy and deformation non-coaxiality were explained based on the stress–force–fabric relationship. It was observed that intermediate principal stress parameter b(b = (σ2 − σ3)/(σ1 − σ3)) has a significant effect on the non-coaxiality of sand. The lower the b-value, the higher the degree of non-coaxiality is induced. Visual inspection of shear band formed at the end of HCA testing has also been presented. The inclinations of the shear bands at different loading directions can be predicted well by taking account of the relative direction of the mobilized planes to the bedding plane

Quantitative Analysis of BTF3, HINT1, NDRG1 and ODC1 Protein Over-Expression in Human Prostate Cancer Tissue

Prostate carcinoma is the most common cancer in men with few, quantifiable, biomarkers. Prostate cancer biomarker discovery has been hampered due to subjective analysis of protein expression in tissue sections. An unbiased, quantitative immunohistochemical approach provided here, for the diagnosis and stratification of prostate cancer could overcome this problem. Antibodies against four proteins BTF3, HINT1, NDRG1 and ODC1 were used in a prostate tissue array (> 500 individual tissue cores from 82 patients, 41 case pairs matched with one patient in each pair had biochemical recurrence). Protein expression, quantified in an unbiased manner using an automated analysis protocol in ImageJ software, was increased in malignant vs non-malignant prostate (by 2-2.5 fold, p<0.0001). Operating characteristics indicate sensitivity in the range of 0.68 to 0.74; combination of markers in a logistic regression model demonstrates further improvement in diagnostic power. Triple-labeled immunofluorescence (BTF3, HINT1 and NDRG1) in tissue array showed a significant (p<0.02) change in co-localization coefficients for BTF3 and NDRG1 co-expression in biochemical relapse vs non-relapse cancer epithelium. BTF3, HINT1, NDRG1 and ODC1 could be developed as epithelial specific biomarkers for tissue based diagnosis and stratification of prostate cancer