It was possible to detect the main cause of the existing high infant mortality rate in the state of Indiana, USA, through the use of big data.
The State of Indiana (USA) improved its public policies based on the use of the data flow generated by public institutions and citizens themselves ('open data’), and which was previously scattered. By crossing all these public ‘big data’, and with the help of the multinational SAP data analysts, Chris Atkins and his team generated an algorithm which succeeded in drawing very valuable conclusions.
The main such conclusion was that the better prenatal care the mother received, the more she preserved her health during pregnancy, so the government boosted this practice and managed to reduce infant mortality, after two decades of trying unsuccessfully by other means.
With the study, the possibility of working in other current problems through big data, a tool with great potential, was analysed. Now, using the same algorithm, Indiana is fighting against crime recurrence.
Source of information:
Atkins, C. Cómo EE.UU. rebajó la mortalidad infantil drásticamente solo cruzando datos. El Observatorio Vodafone de la Empresa [Internet]. February 22, 2018 [query performed on September 12, 2018]; Public Administrations [approx. 2 screens]. Available at: https://www.observatorio-empresas.vodafone.es/articulos/administraciones-publicas/open-data-mortalidad-infantil-indiana-chris-atkins/
▪ To reduce high infant mortality in Indiana.
▪ To have a database integrating all the information.
▪ To create an algorithm which could detect the causes in order to provide a solution to the different problems.
Greater security. La tasa de mortalidad infantil pasó de un 7,7 el 2013 al 7,2 el 2017 (muertes por cada 1.000 nacimientos).
Make the most of creativity and innovation.
To use all of the available sources of information: to contribute to the good analysis of the data.
Published on*** 8 Sep 2018
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