Dashboarding the maternal and child health profiles for health supporting system

International Conference on Information Technology and Digital Applications 2018

计算机科学;无线电电子学

Iswari, Lizda^1 ; Fudholi, Dhomas Hatta^1 ; Aditya, Silfa Kurnia^1

Department of Informatics Yogyakarta, Indonesia Universitas, Islam, Indonesia^1

关键词: Current situation;    Extract , transform and loads;    Health parameters;    Healthcare services;    On-line analytical processing;    Statistical datas;    Supporting factors;    Supporting systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/482/1/012013/pdf
DOI  :  10.1088/1757-899X/482/1/012013

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Various types of health data are routinely collected and published as national health profiles. However, these vast amounts of data are not always used effectively since they are presented in raw tabular data sets, fragmented, and are not well-equipped with the statistical data inferences and the trend of changes which are essential to explore some unknown previous information. In this paper, we propose how to manage the national open health data sets as a dashboard application to support the decision making for maternal and child health-care services in Indonesia. The research was conducted in four steps. First, we described what maternal and child health parameters are involved in relation to the availability of open and accessible data set. Second, we designed the dashboard application based on Kimball's four step dimensional modelling. Third, we implemented the schema modelling as data warehouse by executing ETL (extract, transform and load) and OLAP (On Line Analytical Processing) cubes. Fourth, we analyzed the results with the business intelligence approach. We explored the open data sets in four consecutive years (2014-2017) and determined seven types of business process, i.e. analysis of health profile on neonates, infants, and children, analysis of maternal health profile before, during and after pregnancy period, and analysis of health supporting factors. By applying data warehouse and business intelligence, our proposed system has the ability to integrate and extract a number of tabular and fragmented data sets into an easy and quickly inferred information about the current situation of maternal and children health care services.