The analysis of a cardiological network in a regulated setting: a spatial interaction approach

Bruni, Matteo Lippi; Nobilio, Lucia; Ugolini, Cristina

doi:10.1002/hec.1255

Cited by 17 publications

(12 citation statements)

References 26 publications

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“…In countries like the United States and Italy, the number of Reference Interventional Cardiology Center per capita is higher than in Brazil, allowing patients to be referred to specialized services closer to their place of residence, increasing survival rates and decreasing the patients’ hospitalization duration due to early admission [52], [60], [61].…”

Section: Discussionmentioning

confidence: 99%

Regional Disparities in Mortality after Ischemic Heart Disease in a Brazilian State from 2006 to 2010

Andrade

Zanini²,

Batilana

et al. 2013

PLoS ONE

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BackgroundHigh technology in the field of interventional cardiology applied in tertiary hospitals has brought enormous benefits in the treatment of ischemic heart disease (IHD). However, IHD mortality rates remain high. We analyzed the relationship between IHD mortality rate and the socioeconomic, demographic, and geographic conditions in 399 cities in Parana state, Brazil, from 2006 to 2010.Methods and ResultsData were obtained from the Mortality Information System and the Brazilian Institute of Geography and Statistics and evaluated through Exploratory Spatial Data Analysis. GeoDa™ was used to analyze 29.351 deaths across 399 cities. We found a positive spatial autocorrelation regarding IHD mortality (I = 0.5913, p = 0.001). There was a significant positive association between each of three socioeconomic and demographic indicators and IHD mortality rate: Population Elderly Index (I = 0.3436), Illiteracy Rate (I = 0.1873) and City Development Index (I = 0.0900). In addition, two indicators presented significant negative association with IHD mortality rate: Adjusted Population Size (I = −0.1216) and Gross Domestic Product (I = −0.0864). We also found a positive association between IHD mortality rates and the geographic distances between patients’ city of residence and their corresponding regional referral centers in interventional cardiology (I = 0.3368). Cities located within Regional Health Units with Reference Interventional Cardiology Center presented a significantly lower average specific mortality rate by IHD. The high mortality rate by IHD within the Regional Health Units was not restricted to socioeconomic and demographic variables, but dependent on the distance between each city and their reference interventional cardiology center.ConclusionsWe conclude that geographic factors play a significant role in IHD mortality within cities. These findings have important policy implications regarding the geographic distribution of cardiac health care networks in Latin America and in other emerging countries.

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Section: Discussionmentioning

confidence: 99%

Regional Disparities in Mortality after Ischemic Heart Disease in a Brazilian State from 2006 to 2010

Andrade

Zanini²,

Batilana

et al. 2013

PLoS ONE

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“…On the other hand, as we mentioned in the first section, correlation between patient mobility and health-care service parameters (e.g., quality, efficiency, infrastructure, location) have previously been confirmed in many studies [6, 7, 10, 11, 15]. Therefore, we consider the changes in patient mobility parameters (attract/escape) as proxies for availability and accessibility of health-care services.…”

Section: Resultsmentioning

confidence: 78%

“…International mobility, cross-border mobility, or health tourism are some of the terms used for country-to-country health travel [3, 8, 9]. This study covers the range of interregional patient mobility previously studied in Spain and Italy to improve the understanding of health economics [6, 7, 10–15]. In these countries, as in Turkey, local health departments have gained more autonomy in the past few decades, while central governments still maintain regulatory roles.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, using panel data analysis Mafrolla and D’Amico [15] found a strong correlation between patient mobility behavior and health-care efficiency. In addition, certain studies have been conducted on specific issues, such as pediatric diseases [6], aortic valve substitution [7], percutaneous transluminal coronary angioplasty (PTCA) [10], or cardiac surgeries stratified according to severity levels [11], using patient-mobility parameters.…”

Section: Introductionmentioning

confidence: 99%

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Clustering patient mobility patterns to assess effectiveness of health-service delivery

Delil

Çeli̇k

San

et al. 2017

BMC Health Serv Res

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BackgroundAnalysis of patient mobility in a country not only gives an idea of how the health-care system works, but also can be a guideline to determine the quality of health care and health disparity among regions. Even though determination of patient movement is important, it is not often realized that patient mobility could have a unique pattern beyond health-related endowments (e.g., facilities, medical staff). This study therefore addresses the following research question: Is there a way to identify regions with similar patterns using spatio-temporal distribution of patient mobility? The aim of the paper is to answer this question and improve a classification method that is useful for populous countries like Turkey that have many administrative areas.MethodsThe data used in the study consist of spatio-temporal information on patient mobility for the period between 2009 and 2013. Patient mobility patterns based on the number of patients attracted/escaping across 81 provinces of Turkey are illustrated graphically. The hierarchical clustering method is used to group provinces in terms of the mobility characteristics revealed by the patterns. Clustered groups of provinces are analyzed using non-parametric statistical tests to identify potential correlations between clustered groups and the selected basic health indicators.ResultsIneffective health-care delivery in certain regions of Turkey was determined through identifying patient mobility patterns. High escape values obtained for a large number of provinces suggest poor health-care accessibility. On the other hand, over the period of time studied, visualization of temporal mobility revealed a considerable decrease in the escape ratio for inadequately equipped provinces. Among four of twelve clusters created using the hierarchical clustering method, which include 64 of 81 Turkish provinces, there was a statistically significant relationship between the patterns and the selected basic health indicators of the clusters. The remaining eight clusters included 17 provinces and showed anomalies.ConclusionsThe most important contribution of this study is the development of a way to identify patient mobility patterns by analyzing patient movements across the clusters. These results are strong evidence that patient mobility patterns provide a useful tool for decisions concerning the distribution of health-care services and the provision of health care equipment to the provinces.

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“…This model has been implemented in various themes to distinguish the presence of agglomeration or competition forces among alternative destinations . Using this methodology, Lippi Bruni, Nobilio, and Ugolini’s () analysis of hospital choice by patients undergoing percutaneous transluminal coronary angioplasty in Emilia Romagna (Italy), found that information on destinations is processed hierarchically and that agglomeration (instead of competition) forces are dominant. In another framework, Bernasco’s () analysis of crimes committed by location found that an area located in close proximity of many other residential units is less likely to be targeted than an area that is relatively isolated, thus suggesting the presence of competition forces.…”

Section: Methodsmentioning

confidence: 99%

Universities’ attractiveness to students: The Darwinism effect

Cattaneo

Horta

Malighetti

et al. 2018

Higher Education Quarterly

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Due to significant government cuts to Higher Education funding in Southern European systems, their already underfunded universities were forced to increasingly compete for students as sources of additional revenue. Concurrently, families and students that continued to afford participation in Higher Education became more selective when choosing a university, realising the riskier investment that Higher Education participation had become. Through a competing destinations model and relying on all Italian private and public universities, this study finds that the competition forces characterising universities’ attractiveness over the last decade have changed since the financial crisis of 2008. In a context of lower demand for Higher Education, the competition for students grew and universities in close proximity were better prepared to face the new challenges, leading to the growth of Higher Education clusters.

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The analysis of a cardiological network in a regulated setting: a spatial interaction approach

Cited by 17 publications

References 26 publications

Regional Disparities in Mortality after Ischemic Heart Disease in a Brazilian State from 2006 to 2010

Regional Disparities in Mortality after Ischemic Heart Disease in a Brazilian State from 2006 to 2010

Clustering patient mobility patterns to assess effectiveness of health-service delivery

Universities’ attractiveness to students: The Darwinism effect

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