Keywords

markov models, emergency hospital admissions forecasting, pollution control policies, healthcare management

Start Date

1-7-2012 12:00 AM

Description

Perceived need of big cities is focused on policies limiting pollution fromcars exhaust, energy production, industrial manufacture, with the aim to reducethe impact on both environment and citizens health/living. Decision support ismandatory, aiming at monitoring the city's status, evaluating policies effectivenessand estimating/predicting impacts of environment on health in order to plan morerationale resources allocation and care provision.We present a multi-period analysis performed through Markov-based approachesand prove how these methods may support decisions in the management of bigcities, by integrating environment and health related issues. The study hasconsidered historical pollutants data (2002 to 2011) for assessing air quality inMilan, according to the most updated European Directive; approaches have beenused to evaluate the effectiveness of a traffic limitation policy brought into force inthe 2007 (the Ecopass).Although several epidemiological studies have provided evidence of a relationshipbetween air quality and mortality/morbidity due to cardiovascular and respiratorydiseases, the prediction of emergency hospital admissions in the short term is yetdifficult to achieve, even if crucial for a rational healthcare management. In thispaper we propose to use Markov-based techniques in order to obtain a model toforecast hospital admissions, in the short term, according to pollution level.This work has been performed within the European project Lenvis (LocalENVIronmental Services), a collaborative network of services able to retrieve andanalyze heterogeneous and geographically dispersed data sources in order todeliver environment and health information (www.lenvis.eu). The Markov-basedmodels, trained and validated on real data, have been deployed into the Lenvis'Health Impact Decision Support System (HIDSS) and made accessible, asservices, to decision makers and users accounted. The system has showed itsusefulness both for environment authorities and healthcare stakeholders.

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Jul 1st, 12:00 AM

Markov-based approaches to support policies makers in environment and healthcare

Perceived need of big cities is focused on policies limiting pollution fromcars exhaust, energy production, industrial manufacture, with the aim to reducethe impact on both environment and citizens health/living. Decision support ismandatory, aiming at monitoring the city's status, evaluating policies effectivenessand estimating/predicting impacts of environment on health in order to plan morerationale resources allocation and care provision.We present a multi-period analysis performed through Markov-based approachesand prove how these methods may support decisions in the management of bigcities, by integrating environment and health related issues. The study hasconsidered historical pollutants data (2002 to 2011) for assessing air quality inMilan, according to the most updated European Directive; approaches have beenused to evaluate the effectiveness of a traffic limitation policy brought into force inthe 2007 (the Ecopass).Although several epidemiological studies have provided evidence of a relationshipbetween air quality and mortality/morbidity due to cardiovascular and respiratorydiseases, the prediction of emergency hospital admissions in the short term is yetdifficult to achieve, even if crucial for a rational healthcare management. In thispaper we propose to use Markov-based techniques in order to obtain a model toforecast hospital admissions, in the short term, according to pollution level.This work has been performed within the European project Lenvis (LocalENVIronmental Services), a collaborative network of services able to retrieve andanalyze heterogeneous and geographically dispersed data sources in order todeliver environment and health information (www.lenvis.eu). The Markov-basedmodels, trained and validated on real data, have been deployed into the Lenvis'Health Impact Decision Support System (HIDSS) and made accessible, asservices, to decision makers and users accounted. The system has showed itsusefulness both for environment authorities and healthcare stakeholders.