scholarly journals The impact of acute stroke service centralisation: a time series evaluation

2018 ◽  
Vol 5 (3) ◽  
pp. 181-187 ◽  
Author(s):  
Mat Elameer ◽  
Chris Price ◽  
Darren Flynn ◽  
Helen Rodgers
Keyword(s):  
Time Series ◽  
Acute Stroke ◽  
Stroke Service ◽  
Series Evaluation ◽  
The Impact

The impact of an Advanced Nurse Practitioner training programme in an acute stroke service

2018 ◽  
Vol 14 (3) ◽  
pp. 130-134 ◽  
Author(s):  
Christopher Sanders ◽  
Graham Ashman
Keyword(s):  
Acute Stroke ◽  
Nurse Practitioner ◽  
Training Programme ◽  
Stroke Service ◽  
Practitioner Training ◽  
The Impact

Highs and Lows: An Interrupted Time-Series Evaluation of the Impact of North America’s Only Supervised Injection Facility on Crime

2017 ◽  
Vol 48 (1) ◽  
pp. 36-49 ◽  
Author(s):  
Andrew J. Myer ◽  
Linsey Belisle
Keyword(s):  
Time Series ◽  
Drug Users ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Supervised Injection Facility ◽  
Series Evaluation ◽  
Supervised Injection ◽  
Supervised Injection Facilities ◽  
The Impact ◽  
Combat Problems

North America is currently experiencing an opioid crisis. One proposed solution to combat problems associated with injection drug use is the use of supervised injection facilities. These facilities provide drug users a space to inject pre-obtained drugs without any legal repercussions. Research on these facilities has focused on public health outcomes, and generally found positive results. Far fewer studies have investigated the impact supervised injection facilities have on crime. The current study provides an interrupted time-series analysis on the impact of North America’s only supervised injection facility on crime. Analyses of city wide crime data evidence no impact of the supervised injection facility on crime. Disaggregated analyses indicate a significant decrease in crimes in the district where the supervised injection facility is located. Implications of the findings are discussed.

River-Basin Planning for Control of Nitrate Pollution

1982 ◽  
Vol 14 (4-5) ◽  
pp. 245-252 ◽  
Author(s):  
C S Sinnott ◽  
D G Jamieson
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
River Basin ◽  
Water Resource ◽  
Potable Water ◽  
Potential Problem ◽  
Nitrate Pollution ◽  
Optimal Mix ◽  
Regional Basis ◽  
The Impact

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

EFFECTS OF TREND AND PERIODICITY ON THE CORRELATION DIMENSION AND THE LYAPUNOV EXPONENTS

2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Time Series Data ◽  
Logistic Map ◽  
Model Identification ◽  
Series Data ◽  
Largest Lyapunov Exponent ◽  
The Impact

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.

scholarly journals Correction to: Measuring the impact of the Afordable Care Act Medicaid expansion on access to primary care using an interrupted time series approach

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Elizabeth A. Brown ◽  
Brandi M. White ◽  
Walter J. Jones ◽  
Mulugeta Gebregziabher ◽  
Kit N. Simpson
Keyword(s):  
Primary Care ◽  
Time Series ◽  
Interrupted Time Series ◽  
Medicaid Expansion ◽  
Time Series Approach ◽  
Access To Primary Care ◽  
The Impact

An amendment to this paper has been published and can be accessed via the original article.

scholarly journals Bottlenecks in the Acute Stroke Care System during the COVID-19 Pandemic in Catalonia

2021 ◽  
pp. 1-9
Author(s):  
Anna Ramos-Pachón ◽  
Álvaro García-Tornel ◽  
Mònica Millán ◽  
Marc Ribó ◽  
Sergi Amaro ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Functional Outcome ◽  
Stroke Care ◽  
Care Quality ◽  
Point Of View ◽  
Stroke Severity ◽  
Acute Stroke Care ◽  
Vessel Occlusion ◽  
Prehospital Delays ◽  
The Impact

<b><i>Introduction:</i></b> The COVID-19 pandemic resulted in significant healthcare reorganizations, potentially striking standard medical care. We investigated the impact of the COVID-19 pandemic on acute stroke care quality and clinical outcomes to detect healthcare system’s bottlenecks from a territorial point of view. <b><i>Methods:</i></b> Crossed-data analysis between a prospective nation-based mandatory registry of acute stroke, Emergency Medical System (EMS) records, and daily incidence of COVID-19 in Catalonia (Spain). We included all stroke code activations during the pandemic (March 15–May 2, 2020) and an immediate prepandemic period (January 26–March 14, 2020). Primary outcomes were stroke code activations and reperfusion therapies in both periods. Secondary outcomes included clinical characteristics, workflow metrics, differences across types of stroke centers, correlation analysis between weekly EMS alerts, COVID-19 cases, and workflow metrics, and impact on mortality and clinical outcome at 90 days. <b><i>Results:</i></b> Stroke code activations decreased by 22% and reperfusion therapies dropped by 29% during the pandemic period, with no differences in age, stroke severity, or large vessel occlusion. Calls to EMS were handled 42 min later, and time from onset to hospital arrival increased by 53 min, with significant correlations between weekly COVID-19 cases and more EMS calls (rho = 0.81), less stroke code activations (rho = −0.37), and longer prehospital delays (rho = 0.25). Telestroke centers were afflicted with higher reductions in stroke code activations, reperfusion treatments, referrals to endovascular centers, and increased delays to thrombolytics. The independent odds of death increased (OR 1.6 [1.05–2.4], <i>p</i> 0.03) and good functional outcome decreased (mRS ≤2 at 90 days: OR 0.6 [0.4–0.9], <i>p</i> 0.015) during the pandemic period. <b><i>Conclusion:</i></b> During the COVID-19 pandemic, Catalonia’s stroke system’s weakest points were the delay to EMS alert and a decline of stroke code activations, reperfusion treatments, and interhospital transfers, mostly at local centers. Patients suffering an acute stroke during the pandemic period had higher odds of poor functional outcome and death. The complete stroke care system’s analysis is crucial to allocate resources appropriately.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

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