Abstract
Data in the healthcare industry is overwhelming, not only because of its volume but also because of its variety. In order to use such data, it needs to be pre-processed and integrated first. An additional problem is the visualization of such big data and making it valuable, readable and easier to come to the conclusions. This paper presents a system that uses interactive maps for presenting data and services for integrating healthcare data and combining it with other external sources. The purpose of this system is to show a presence of some disease in the country, how many patients with that diagnosis had to travel to some other location in order to get the medical examination and how far they had to go. Such information can be valuable in process of organizing and optimizing healthcare resources and creating models for cheaper and more optimal healthcare both from system’s and patient’s perspective.
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Notes
- 1.
Tableau - https://www.tableau.com/.
- 2.
Qlik - http://www.qlik.com/us/.
- 3.
Silk - https://www.silk.co/.
- 4.
Google Maps API - https://developers.google.com/maps/.
- 5.
Leaflet - http://leafletjs.com/.
- 6.
D3.js - https://d3js.org/.
- 7.
OpenLayers - https://openlayers.org/.
- 8.
.NET Compiler Platform - https://github.com/dotnet/roslyn.
- 9.
Hypertable - http://www.hypertable.org/.
- 10.
IDC10 code API - https://www.hipaaspace.com/.
- 11.
OpenStreetMap - https://www.openstreetmap.org/.
- 12.
MapQuest Geocoding API - https://developer.mapquest.com/documentation/geocoding-api/.
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Frtunić Gligorijević, M., Puflović, D., Stevanoska, E., Jevtović Stoimenov, T., Velinov, G., Stoimenov, L. (2017). Interactive Map Visualization System Based on Integrated Semi-structured and Structured Healthcare Data. In: Da Silveira, M., Pruski, C., Schneider, R. (eds) Data Integration in the Life Sciences. DILS 2017. Lecture Notes in Computer Science(), vol 10649. Springer, Cham. https://doi.org/10.1007/978-3-319-69751-2_10
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