117 research outputs found

    Still Searching: How People Use Health Care Price Information in the United States, New York State, Florida, Texas and New Hampshire

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    Americans bear a large and growing share of their health care costs in the form of high deductibles and insurance premiums, as well as copayments and, sometimes, coinsurance for physician office visits and hospitalizations. Historically, the health care system has not made it easy for people to find out how much their care will cost them out of pocket. But, in recent years, insurers, state governments, employers and other entities have been trying to make price information more easily available to individuals and families. Are Americans trying to find out about health care prices today? Do they want more information? What sources would they trust to deliver it?This nationally representative research finds 50 percent of Americans have tried to find health care price information before getting care, including 20 percent who have tried to compare prices across multiple providers. Representative surveys in four states— New York, Texas, Florida and New Hampshire—show higher percentages of residents in Texas, Florida and New Hampshire have tried to find price information and have compared prices than New York residents and Americans overall. This variation suggests factors at the state level might be influencing how many people try to find out about health care costs. Nationally and in those four states, more than half of people who compared prices report saving money. Most Americans overall think it is important for their state governments to provide comparative price information. But we found limited awareness that doctors' prices vary and limited awareness that hospitals' prices vary.Public Agenda conducted this research with support from the Robert Wood Johnson Foundation and the New York State Health Foundation. The findings are based on a nationally representative survey of 2,062 adults, ages 18 and older, and a set of representative surveys in four states: one survey of 802 adults in New York, one of 808 adults in Texas, one of 819 adults in Florida and one of 826 adults in New Hampshire. The surveys were conducted from July through September 2016 by telephone, including cell phones, and online

    Why Let the People Decide? Elected Officials on Participatory Budgeting

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    This report documents findings from interviews with U.S. elected officials regarding their experience with participatory budgeting (PB). It also includes recommendations for policymakers, PB advocates and funders looking to improve and expand PB

    Public Spending, By The People: Participatory Budgeting in the United States and Canada in 2014-15

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    From 2014 to 2015, more than 70,000 residents across the United States and Canada directly decided how their cities and districts should spend nearly $50 million in public funds through a process known as participatory budgeting (PB). PB is among the fastest growing forms of public engagement in local governance, having expanded to 46 communities in the U.S. and Canada in just 6 years.PB is a young practice in the U.S. and Canada. Until now, there's been no way for people to get a general understanding of how communities across the U.S. implement PB, who participates, and what sorts of projects get funded. Our report, "Public Spending, By the People" offers the first-ever comprehensive analysis of PB in the U.S. and Canada.Here's a summary of what we found:Overall, communities using PB have invested substantially in the process and have seen diverse participation. But cities and districts vary widely in how they implemented their processes, who participated and what projects voters decided to fund. Officials vary in how much money they allocate to PB and some communities lag far behind in their representation of lower-income and less educated residents.The data in this report came from 46 different PB processes across the U.S. and Canada. The report is a collaboration with local PB evaluators and practitioners. The work was funded by the Democracy Fund and the Rita Allen Foundation, and completed through a research partnership with the Kettering Foundation

    Potential misinterpretations caused by collapsing upper categories of comorbidity indices: An illustration from a cohort of older breast cancer survivors

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    BACKGROUND: Comorbidity indices summarize complex medical histories into concise ordinal scales, facilitating stratification and regression in epidemiologic analyses. Low subject prevalence in the highest strata of a comorbidity index often prompts combination of upper categories into a single stratum (\u27collapsing\u27). OBJECTIVE: We use data from a breast cancer cohort to illustrate potential inferential errors resulting from collapsing a comorbidity index. METHODS: Starting from a full index (0, 1, 2, 3, and \u3e/=4 comorbidities), we sequentially collapsed upper categories to yield three collapsed categorizations. The full and collapsed categorizations were applied to analyses of (1) the association between comorbidity and all-cause mortality, wherein comorbidity was the exposure; (2) the association between older age and all-cause mortality, wherein comorbidity was a candidate confounder or effect modifier. RESULTS: Collapsing the index attenuated the association between comorbidity and mortality (risk ratio, full versus dichotomized categorization: 4.6 vs 2.1), reduced the apparent magnitude of confounding by comorbidity of the age/mortality association (relative risk due to confounding, full versus dichotomized categorization: 1.14 vs 1.09), and obscured modification of the association between age and mortality on both the absolute and relative scales. CONCLUSIONS: Collapsing categories of a comorbidity index can alter inferences concerning comorbidity as an exposure, confounder and effect modifier

    Motivation and mortality in older women with early stage breast cancer: A longitudinal study with ten years of follow-up.

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    OBJECTIVES The Getting Out of Bed Scale (GOB) was validated as a health-related quality of life (HRQoL) variable in older women with early stage breast cancer, suggesting its potential as a concise yet powerful measure of motivation. The aim of our project was to assess the association between GOB and mortality over 10years of follow-up. MATERIALS AND METHODS We studied 660 women ≥65-years old diagnosed with stage I-IIIA primary breast cancer. Data were collected over 10years of follow-up from interviews, medical records, and death indexes. RESULTS Compared to women with lower GOB scores, women with higher GOB had an unadjusted hazard ratio (HR) of all-cause mortality of 0.78 at 5years, 95% confidence interval (CI) (0.52, 1.19) and 0.77 at 10years, 95%CI (0.59, 1.00). These associations diminished after adjusting for age and stage of breast cancer, and further after adjusting for other HRQoL variables including physical function, mental health, emotional health, psychosocial function, and social support. Unadjusted HRs of breast cancer-specific mortality were 0.92, 95%CI (0.49, 1.74), at 5years, and 0.82, 95%CI (0.52, 1.32), at 10years. These associations also decreased in adjusted models. CONCLUSION Women with higher GOB scores had a lower hazard of all-cause mortality in unadjusted analysis. This effect diminished after adjusting for confounding clinical and HRQoL variables. GOB is a measure of motivation that may not be independently associated with cancer mortality, but reflects other HRQoL variables making it a potential outcome to monitor in older patients with cancer

    Comparison of Different Approaches to Confounding Adjustment in a Study on the Association of Antipsychotic Medication With Mortality in Older Nursing Home Patients

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    Selective prescribing of conventional antipsychotic medication (APM) to frailer patients is thought to have led to overestimation of the association with mortality in pharmacoepidemiologic studies relying on claims data. The authors assessed the validity of different analytic techniques to address such confounding. The cohort included 82,012 persons initiating APM use after admission to a nursing home in 45 states with 2001–2005 Medicaid/Medicare data, linked to clinical data (Minimum Data Set) and institutional characteristics. The authors compared the association between APM class and 180-day mortality with multivariate outcome modeling, propensity score (PS) adjustment, and instrumental variables. The unadjusted risk difference (per 100 patients) of 10.6 (95% confidence interval (CI): 9.4, 11.7) comparing use of conventional medication with atypical APM was reduced to 7.8 (95% CI: 6.6, 9.0) and 7.0 (95% CI: 5.8, 8.2) after PS adjustment and high-dimensional PS (hdPS) adjustment, respectively. Results were similar in analyses limited to claims-based Medicaid /Medicare variables (risk difference = 8.2 for PS, 7.1 for hdPS). Instrumental-variable estimates were imprecise (risk difference = 8.8, 95% CI: −1.3, 19.0) because of the weak instrument. These results suggest that residual confounding has a relatively small impact on the effect estimate and that hdPS methods based on claims alone provide estimates at least as good as those from conventional analyses using claims enriched with clinical information

    Automated inter-rater reliability assessment and electronic data collection in a multi-center breast cancer study

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    <p>Abstract</p> <p>Background</p> <p>The choice between paper data collection methods and electronic data collection (EDC) methods has become a key question for clinical researchers. There remains a need to examine potential benefits, efficiencies, and innovations associated with an EDC system in a multi-center medical record review study.</p> <p>Methods</p> <p>A computer-based automated menu-driven system with 658 data fields was developed for a cohort study of women aged 65 years or older, diagnosed with invasive histologically confirmed primary breast cancer (N = 1859), at 6 Cancer Research Network sites. Medical record review with direct data entry into the EDC system was implemented. An inter-rater and intra-rater reliability (IRR) system was developed using a modified version of the EDC.</p> <p>Results</p> <p>Automation of EDC accelerated the flow of study information and resulted in an efficient data collection process. Data collection time was reduced by approximately four months compared to the project schedule and funded time available for manuscript preparation increased by 12 months. In addition, an innovative modified version of the EDC permitted an automated evaluation of inter-rater and intra-rater reliability across six data collection sites.</p> <p>Conclusion</p> <p>Automated EDC is a powerful tool for research efficiency and innovation, especially when multiple data collection sites are involved.</p

    Risk of venous thromboembolism after total hip and knee replacement in older adults with comorbidity and co-occurring comorbidities in the Nationwide Inpatient Sample (2003-2006)

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    <p>Abstract</p> <p>Background</p> <p>Venous thromboembolism is a common, fatal, and costly injury which complicates major surgery in older adults. The American College of Chest Physicians recommends high potency prophylaxis regimens for individuals undergoing total hip or knee replacement (THR or TKR), but surgeons are reluctant to prescribe them due to fear of excess bleeding. Identifying a high risk cohort such as older adults with comorbidities and co-occurring comorbidities who might benefit most from high potency prophylaxis would improve how we currently perform preoperative assessment.</p> <p>Methods</p> <p>Using the Nationwide Inpatient Sample, we identified older adults who underwent THR or TKR in the U.S. between 2003 and 2006. Our outcome was VTE, including any pulmonary embolus or deep venous thrombosis. We performed multivariate logistic regression analyses to assess the effects of comorbidities on VTE occurrence. Comorbidities under consideration included coronary artery disease, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), diabetes, and cerebrovascular disease. We also examined the impact of co-occurring comorbidities on VTE rates.</p> <p>Results</p> <p>CHF increased odds of VTE in both the THR cohort (OR = 3.08 95% CI 2.05-4.65) and TKR cohort (OR = 2.47 95% CI 1.95-3.14). COPD led to a 50% increase in odds in the TKR cohort (OR = 1.49 95% CI 1.31-1.70). The data did not support synergistic effect of co-occurring comorbidities with respect to VTE occurrence.</p> <p>Conclusions</p> <p>Older adults with CHF undergoing THR or TKR and with COPD undergoing TKR are at increased risk of VTE. If confirmed in other datasets, these older adults may benefit from higher potency prophylaxis.</p

    Can fisheries-induced evolution shift reference points for fisheries management?

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    Biological reference points are important tools for fisheries management. Reference points are not static, butmay change when a population's environment or the population itself changes. Fisheries-induced evolution is one mechanism that can alter population characteristics, leading to "shifting" reference points by modifying the underlying biological processes or by changing the perception of a fishery system. The former causes changes in "true" reference points, whereas the latter is caused by changes in the yardsticks used to quantify a system's status. Unaccounted shifts of either kind imply that reference points gradually lose their intended meaning. This can lead to increased precaution, which is safe, but potentially costly. Shifts can also occur in more perilous directions, such that actual risks are greater than anticipated. Our qualitative analysis suggests that all commonly used reference points are susceptible to shifting through fisheries-induced evolution, including the limit and "precautionary" reference points for spawning-stock biomass, B-lim and B-pa, and the target reference point for fishing mortality, F-0.1. Our findings call for increased awareness of fisheries-induced changes and highlight the value of always basing reference points on adequately updated information, to capture all changes in the biological processes that drive fish population dynamics
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