Visual analytics: tackling data related challenges in healthcare process mining

2018 Conference paper presented at Strathmore University. Thematic area(Health, Healthcare Management and Research Ethics)Data-science approaches such as Visual analytics tend to be process blind whereas process-science approaches such as process mining tend to be model-driven without considering the “evidence” hidden in the data. Use of either approach separately faces limitations in analysis of healthcare data. Visual analytics allows humans to exploit their perceptual and cognitive capabilities in processing data, while process mining represents the data in terms of activities and resources thereby giving a complete process picture. We use a literature survey of research that has deployed either or both Visual analytics and process mining in the healthcare environments to discover strengths that can help solve open problems and challenges in healthcare data when using process mining. We present a visual analytics (data science) approach in solving data challenges in healthcare process mining (process science). Historical data (event logs) obtained from organizational archives are used to generate accurate and evidence-based activity sequences that are manipulated and analysed to answer questions that could not be tackled by process mining. The approach can help hospital management and clinicians among others, audit their business processes in addition to providing important operational information. Other beneficiaries are those organizations interested in forensic information regarding individuals and groups of patients.1.Institute of Computing and Informatics, Technical University of Mombasa; 2.Faculty of information Technology, Strathmore University 3.School of Computing and Information technology, Muranga University of technology; 4.School of Computing and Informatics, Masinde Muliro University of Science and Technolog

Challenges in achieving interoperability in distributed systems: a survey of literature

As need for collaboration and distributed systems among organizations increase, there is the challenge of different standards in almost all communication issues. This calls for scrutiny of systems used by different organizations or units of the same organization in an effort to achieve distributed systems. Available literature on this topic is limited and there is lack of an assessment framework to determine which system has attained what level of interoperability. We discuses four strategies or approaches used in achieving some degree of interoperability, as well as issues in distributed systems interoperability. This paper conducts a detailed literature review on interoperability in distributed systems and then proposes a ranking framework to assess interoperability. Currently XML is widely used implementing systems that need to communicate with others. However technical challenges such as semantics, security and legacy databases, together with many managerial issues remain a hindrance to achieving complete interoperability. Keywords: Interoperability, Distributed systems, Legacy Systems, XML