Road Closures and Freight Diversion

2012 ◽  
Vol 2269 (1) ◽  
pp. 51-57 ◽  
Author(s):  
David Pierce ◽  
Jeffrey Short
Keyword(s):  
Performance Measures ◽  
The United States ◽  
Valuable Insight ◽  
Data Set ◽  
Sensing Technology ◽  
Global Positioning ◽  
Data Points ◽  
System Data ◽  
The Impact

The FHWA-sponsored Freight Performance Measures (FPM) program generates and monitors a series of performance measures related to the freight transportation system of the United States. The primary information analyzed by the FPM program is a data set consisting of billions of Global Positioning System data points from trucks. These data can be used to demonstrate empirically changes in truck travel patterns and freight performance independent of the availability of roadside sensing technology. A case study that was based on the flooding closure of Arkansas Interstate 40 in May 2011 was presented to show how FPM data can be used to analyze diversion behavior around road closures. This type of empirical analysis is in contrast to the majority of current diversion analyses, which rely on modeling to generate results. Not only do FPM data provide a viable alternative to modeling for studying past events, but the data may provide valuable insight into the underlying assumptions of future models designed to predict the impact of disaster scenarios. By understanding more fully how previous events unfolded, planners can prepare better for the next disaster.

State Medical Boards' Perceptions of a Minimum Data Set and Current Practices for Collecting Physician Information

2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen
Keyword(s):  
Media Coverage ◽  
The United States ◽  
Minimum Data Set ◽  
Direct Patient Care ◽  
Physician Workforce ◽  
Data Set ◽  
Minimum Data ◽  
State Medical Boards ◽  
The Impact ◽  
Current Practices

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.

Measuring Congestion and Reliability Impacts of Safety Projects

2021 ◽  
pp. 036119812110067
Author(s):  
Simona Babiceanu ◽  
Sanhita Lahiri ◽  
Mena Lockwood
Keyword(s):  
Performance Measures ◽  
Positive Impact ◽  
Operating Conditions ◽  
Vehicle Miles Traveled ◽  
Data Set ◽  
Data Points ◽  
Practical Recommendations

This study uses a suite of performance measures that was developed by taking into consideration various aspects of congestion and reliability, to assess impacts of safety projects on congestion. Safety projects are necessary to help move Virginia’s roadways toward safer operation, but can contribute to congestion and unreliability during execution, and can affect operations after execution. However, safety projects are assessed primarily for safety improvements, not for congestion. This study identifies an appropriate suite of measures, and quantifies and compares the congestion and reliability impacts of safety projects on roadways for the periods before, during, and after project execution. The paper presents the performance measures, examines their sensitivity based on operating conditions, defines thresholds for congestion and reliability, and demonstrates the measures using a set of Virginia safety projects. The data set consists of 10 projects totalling 92 mi and more than 1M data points. The study found that, overall, safety projects tended to have a positive impact on congestion and reliability after completion, and the congestion variability measures were sensitive to the threshold of reliability. The study concludes with practical recommendations for primary measures that may be used to measure overall impacts of safety projects: percent vehicle miles traveled (VMT) reliable with a customized threshold for Virginia; percent VMT delayed; and time to travel 10 mi. However, caution should be used when applying the results directly to other situations, because of the limited number of projects used in the study.

scholarly journals 910. A Comprehensive, One Year, Hospital-Wide Snapshot of All Serious Infectious Complications in People Who Inject Drugs

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S489-S490
Author(s):  
John T Henderson ◽  
Evelyn Villacorta Cari ◽  
Nicole Leedy ◽  
Alice Thornton ◽  
Donna R Burgess ◽  
...  
Keyword(s):  
Multivariable Analysis ◽  
Vertebral Osteomyelitis ◽  
The United States ◽  
Infectious Complications ◽  
Data Set ◽  
Cumulative Impact ◽  
Mortality And Morbidity ◽  
Icu Admission ◽  
Risk Of Death ◽  
The Impact

Abstract Background There has been a dramatic rise in IV drug use (IVDU) and its associated mortality and morbidity, however, the scope of this effect has not been described. Kentucky is at the epicenter of this epidemic and is an ideal place to better understand the health complications of IVDU in order to improve outcomes. Methods All adult in-patient admissions to University of Kentucky hospitals in 2018 with an Infectious Diseases (ID) consult and an ICD 9/10 code associated with IVDU underwent thorough retrospective chart review. Demographic, descriptive, and outcome data were collected and analyzed by standard statistical analysis. Results 390 patients (467 visits) met study criteria. The top illicit substances used were methamphetamine (37.2%), heroin (38.2%), and cocaine (10.3%). While only 4.1% of tested patients were HIV+, 74.2% were HCV antibody positive. Endocarditis (41.1%), vertebral osteomyelitis (20.8%), bacteremia without endocarditis (14.1%), abscess (12.4%), and septic arthritis (10.4%) were the most common infectious complications. The in-patient death rate was 3.0%, and 32.2% of patients were readmitted within the study period. The average length of stay was 26 days. In multivariable analysis, infectious endocarditis was associated with a statistically significant increase in risk of death, ICU admission, and hospital readmission. Although not statistically significant, trends toward mortality and ICU admission were identified for patients with prior endocarditis and methadone was correlated with decreased risk of readmission and ICU stay. FIGURE 1: Reported Substances Used FIGURE 2: Comorbidities FIGURE 3: Types of Severe Infectious Complications Conclusion We report on a novel, comprehensive perspective on the serious infectious complications of IVDU in an attempt to measure its cumulative impact in an unbiased way. This preliminary analysis of a much larger dataset (2008-2019) reveals some sobering statistics about the impact of IVDU in the United States. While it confirms the well accepted mortality and morbidity associated with infective endocarditis and bacteremia, there is a significant unrecognized impact of other infectious etiologies. Additional analysis of this data set will be aimed at identifying key predictive factors in poor outcomes in hopes of mitigating them. Disclosures All Authors: No reported disclosures

Eviction and Voter Turnout: The Political Consequences of Housing Instability

2021 ◽  
pp. 003232922110507
Author(s):  
Gillian Slee ◽  
Matthew Desmond
Keyword(s):  
Voter Turnout ◽  
Causal Effect ◽  
Additive Model ◽  
The United States ◽  
Data Set ◽  
Endogeneity Bias ◽  
Political Consequences ◽  
Housing Costs ◽  
Election Results ◽  
The Impact

In recent years, housing costs have outpaced incomes in the United States, resulting in millions of eviction filings each year. Yet no study has examined the link between eviction and voting. Drawing on a novel data set that combines tens of millions of eviction and voting records, this article finds that residential eviction rates negatively impacted voter turnout during the 2016 presidential election. Results from a generalized additive model show eviction’s effect on voter turnout to be strongest in neighborhoods with relatively low rates of displacement. To address endogeneity bias and estimate the causal effect of eviction on voting, the analysis treats commercial evictions as an instrument for residential evictions, finding that increases in neighborhood eviction rates led to substantial declines in voter turnout. This study demonstrates that the impact of eviction reverberates far beyond housing loss, affecting democratic participation.

Reliability-based covariate analysis for complex systems in heterogeneous environment: Case study of mining equipment

2018 ◽  
Vol 233 (4) ◽  
pp. 593-604
Author(s):  
Amin Moniri-Morad ◽  
Mohammad Pourgol-Mohammad ◽  
Hamid Aghababaei ◽  
Javad Sattarvand
Keyword(s):  
Complex Systems ◽  
Cox Regression ◽  
Reliability Evaluation ◽  
Distribution Functions ◽  
Heterogeneous Environment ◽  
Mining Equipment ◽  
Data Set ◽  
Explanatory Variables ◽  
The Impact

Operational heterogeneity and harsh environment lead to major variations in production system performance and safety. Traditional probabilistic model is dealt with time-to-event data analysis, which does not have the capability of quantifying and simulation of these types of complexities. This research proposes an integrated methodology for analyzing the impact of dominant explanatory variables on the complex system reliability. A flexible parametric proportional hazards model is developed by focusing on standard parametric Cox regression model for reliability evaluation in complex systems. To achieve this, natural cubic splines are utilized to create a smooth and flexible baseline hazards function where the standard parametric distribution functions do not fit into the failure data set. A real case study is considered to evaluate the reliability for multi-component mechanical systems such as mining equipment. Different operational and environmental explanatory variables are chosen for the analysis process. Research findings revealed that precise estimation of the baseline hazards function is a major part of the reliability evaluation in heterogeneous environment. It is concluded that an appropriate maintenance strategy potentially mitigate the equipment failure intensity.

Sanctioned to Survive: How Foreign Firms Perform when Economic Sanctions Affect their Business Relationships—A Study of Contemporary Economic Sanction Actions and their Impact

2017 ◽  
Vol 16 (5) ◽  
pp. 501-538
Author(s):  
Blaine Stout
Keyword(s):  
Single Case ◽  
Economic Sanctions ◽  
The United States ◽  
Study Strategies ◽  
Foreign Firms ◽  
Case Study Methodology ◽  
Exxon Mobil ◽  
Historical Accounts ◽  
The Impact

Abstract The intent of this study is to examine the effects of economic sanctions on companies with significant fdi operating in the sanctioned country. Using case study methodology, we consider the impact of sanctions imposed on the Russian Federation (rf) by the United States of America for its intrusion into the sovereign rights of Ukraine. Past sanction events in South Africa and pre-rf formation are reviewed. Two measurable frameworks are developed to study strategies based on ‘divestment and non-divestment’ (Malone and Goodin 1997) dimensions and coupled with variables related to ‘direct and indirect’ effects on financial performance, forgone potential, (Losman 1988) and foreign direct investment (Biglaiser and Lektzian 2011). This research also relies on the historical accounts of Hufbauer et al. (2007) for the compilation of facts related to economic sanctions. Through literature review, the study asks: 1) Strategically, how does a company respond to the economic sanctions imposed by its home country on the sanctioned country in which it has significant fdi? 2) Financially, how do economic sanctions affect the company’s performance and fdi? and 3) Organizationally, how do economic sanctions affect the relationships with those recipient companies of fdi? The study focus is on the energy industry in which the rf economy relies upon for 40 percent of its sustainability and the company of focus is Exxon Mobil (xom). The author readily acknowledges that a single case study may not provide the degree of conclusiveness found in a cross-case study format. However, the outcome of the study does provide a template for use in future case reviews.

scholarly journals Evacuation Data from a Hospital Outpatient Drill The Case Study of North Shore Hospital

2020 ◽  
Vol 5 ◽  
Author(s):  
Anass Rahouti ◽  
Ruggiero Lovreglio ◽  
Phil Jackson ◽  
Sélim Datoussaïd
Keyword(s):  
Built Environment ◽  
Fire Safety ◽  
Movement Time ◽  
Data Set ◽  
Healthcare Facilities ◽  
Staff Members ◽  
North Shore ◽  
The North ◽  
The Impact

Assessing the fire safety of buildings is fundamental to reduce the impact of this threat on their occupants. Such an assessment can be done by combining existing models and existing knowledge on how occupants behave during fires. Although many studies have been carried out for several types of built environment, only few of those investigate healthcare facilities and hospitals. In this study, we present a new behavioural data-set for hospital evacuations. The data was collected from the North Shore Hospital in Auckland (NZ) during an unannounced drill carried out in May 2017. This drill was recorded using CCTV and those videos are analysed to generate new evacuation model inputs for hospital scenarios. We collected pre-movement times, exit choices and total evacuation times for each evacuee. Moreover, we estimated pre-movement time distributions for both staff members and patients. Finally, we qualitatively investigated the evacuee actions of patients and staff members to study their interaction during the drill. The results show that participants were often independent from staff actions with a majority able to make their own decision.

scholarly journals Google Traffic sebagai Masukan Kebijakan Transportasi Perkotaan (Studi Kasus: Kota Bandar Lampung)

2020 ◽  
Vol 22 (3) ◽  
pp. 409-417
Author(s):  
Muhammad Zainal Ibad ◽  
Rahayu Sulistyorini ◽  
Chania Rahmah
Keyword(s):  
Urban Areas ◽  
Urban Transportation ◽  
Transportation Policy ◽  
Time Data ◽  
Global Positioning ◽  
Transportation Policies ◽  
Movement System ◽  
Using Data ◽  
The Impact

Congestion in urban areas is vulnerable because of the impact of the growth of activities and an increasingly specialized and complex economy. For this reason, it is necessary to formulate a good urban transportation policy to accommodate increased urban transportation needs. Google Traffic is a feature found on Google Maps to see the level of congestion in an area. Google Traffic can detect an area with red, yellow or green indications through the principle of Real Time Data using data from the Global Positioning System (GPS). This study wanted to see how the use of the Google Traffic Feature as input to urban transportation policies by looking at existing urban transportation policies, analyzing the movement system model on Google Traffic, and analyzing the development of Google Traffic model policies, which would be useful for the development of Urban Transportation Policies, especially Bandar Lampung City as a case study.

Income and healthcare financing system in the United States: an asymmetric analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehdi Barati ◽  
Hadiseh Fariditavana
Keyword(s):  
The United States ◽  
Set Covering ◽  
Healthcare Financing ◽  
Financing System ◽  
Data Set ◽  
Content Type ◽  
Funding Sources ◽  
Distributed Lag ◽  
The Impact ◽  
The Relationship

PurposeThe purpose of this study is to first assess how the US healthcare financing system is influenced by income variation. Then, it examines whether or not the impact of income variation is asymmetric.Design/methodology/approachFor the analyses of this paper, the autoregressive distributed lag (ARDL) model is implemented to a data set covering the period from 1960 to 2018.FindingsThe results provide evidence that major funding sources of aggregate healthcare expenditure (HCE) respond differently to changes in income. The results also imply that the effect of income is not always symmetric.Originality/valueMany studies have attempted to identify the relationship between income and HCE. A common feature of past studies is that they have only focused on aggregate HCE, while one might be interested in knowing how major funders of aggregate HCE would be affected by changes in income. Another common feature of past studies is that they have assumed that the relationship between income and HCE is symmetric.

Educating Students with Chronic Illness

2020 ◽  
pp. 578-597
Author(s):  
Margaret Tseng ◽  
Rebecca Magee Pluta
Keyword(s):  
United States ◽  
Middle School ◽  
Chronic Illness ◽  
Civil Rights ◽  
The United States ◽  
Middle School Student ◽  
Physical Location ◽  
Available Technology ◽  
The Impact

Students with chronic illness have historically received an education via home and hospital instruction during their absences. This instruction is significantly inferior in both quality and quantity when compared with the educational experience of students able to attend school. This case study details the experiences of a middle school student in the mid-Atlantic Region of the United States whose chronic illness presented unique and multifaceted challenges that could not be met by her district's inflexible policies and disconnected resources. This case illuminates the need for schools to break away from the traditional administrative special education mold when responding to the challenges of educating frequently absent students with chronic illness. The educational Civil Rights of these students can be preserved, however, by utilizing affordable, available technology to minimize the impact of frequently missed classes, provide continuity of instruction and allow educational access regardless of a student's physical location during their absences from school.

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