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Leveraging intrinsic resources for the protection of health information assets
Author(s) -
Kevin Tatenda Kativu,
Dalenca Pottas
Publication year - 2019
Publication title -
south african computer journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 6
eISSN - 2313-7835
pISSN - 1015-7999
DOI - 10.18489/sacj.v31i2.536
Subject(s) - business , leverage (statistics) , unavailability , health care , asset (computer security) , context (archaeology) , risk analysis (engineering) , resource (disambiguation) , knowledge management , computer science , computer security , economic growth , economics , paleontology , computer network , machine learning , engineering , reliability engineering , biology
The prevailing state of rural economies continues to constrain the use of digital applications for improved healthcare. These constraints are attributed to the unavailability of key infrastructure and financial resources. Moreover, a prevailing shortage of skilled health workers highlights the critical role digital solutions have to play in alleviating health service delivery challenges. Resource-constrained settings need secure low cost and long shelf-life solutions that leverage existing resources to provide adequate and secure health services. The objective of this paper is to identify the existing resources that can be engaged in the protection of the broader health information assets (including digital applications). To meet the objective, a single case study was conducted. Questionnaires were distributed to twenty-five Community Health Workers to identify existing stressors and resources in the context. The paper leads with a description of resource-constrained settings, highlights the challenges facing healthcare systems in these contexts and emphasizes the need for health information asset protection. The findings, recommendations and conclusions are subsequently presented. The contribution of this paper is a set of recommendations for improving health information asset protection in resource-constrained settings as informed by stressors and resources identified in the case study.

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