Establishing spatially-enabled health registry systems using implicit spatial data pools: Case study-Uganda

Augustus Aturinde, Nakasi Rose, Mahdi Farnaghi, Gilbert Maiga, Petter Pilesjö, Ali Mansourian*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Downloads (Pure)


Background: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.

Methods: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.

Results: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.

Conclusion: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.

Original languageEnglish
Article number215
Pages (from-to)1-9
Number of pages9
JournalBMC medical informatics and decision making
Publication statusPublished - 8 Nov 2019
Externally publishedYes


  • Mobile-GIS
  • RESTful web services
  • SDI
  • Spatial epidemiology
  • Spatially-enabled health registry
  • Uganda
  • ITC-CV


Dive into the research topics of 'Establishing spatially-enabled health registry systems using implicit spatial data pools: Case study-Uganda'. Together they form a unique fingerprint.

Cite this