Towards Paperless Hospitals: Lessons Learned from 15 Health Facilities in Uganda

  • Benjamin KanagwaEmail author
  • Jenard Ntacyo
  • Sam Orach
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 445)


This paper presents action research results on critical features that impact the implementation and acceptance of Electronic Patient Records Management Systems (EPRMS) by health facilities. The paper also discusses automation approaches as well as initial benefits reported by health facilities. The EPRMS is in use by over 15 health facilities in Uganda. The goal is to create a paperless environment for a group of health facilities in a resource constrained environment. The EPRMS incorporates features for Electronic Patient Records (EPR), Electronic Medical Records (EMR) and Hospital Management. A phased-roll out approach was used as a way to ease challenges of insufficient resources such as computers, unstable local area network, frequent power outages and skills-gap among others. The first phase covered Outpatient Departments (OPD) for production deployment while Inpatients, Maternal and Child Health(MCH), HIV/AIDS care centres are setup in training mode awaiting the next phase of roll out. After a year of use, we administered a questionnaire to understand the impact and challenges of EPRMS. The respondents were hospital administrators and managers. In addition to the questionnaire, the Uganda Catholic Medical Bureau (UCMB) has its internal annual reporting process. The results reported are from the questionnaire, UCMB internal reporting, our observations and interactions with key stakeholders during implementation. Our finding indicate EMR and EPR functionality are not highly rated by hospital managers while Hospital Management features are considered important.


Health Facility Electronic Medical Record Electronic Health Record Local Area Network Electronic Patient Record 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Computing and Informatics Technology Makerere UniversityKampalaUganda
  2. 2.Uganda Catholic Medical BureauKampalaUganda

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