ReviewJournal of multidisciplinary healthcare2024
Informing the State of Process Modeling and Automation of Blood Banking and Transfusion Services Through a Systematic Mapping Study.
Review in Journal of multidisciplinary healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Purpose: The current state of the art in process modeling of blood banking and transfusion services is not well grounded; methodological reviews are lacking to bridge the gap between such blood banking and transfusion processes (and their models) and their automation. This research aims to fill this gap with a methodological review. Methods: A systematic mapping study was adopted, driven by five key research questions. Identified research studies were accepted based on fulfilling the following inclusion criteria: 1) research studies should focus on blood banking and transfusion process modeling since the late 1970s; and 2) research studies should focus on process automation in relation to workflow-based systems, with papers classified into categories in line with the analysis undertaken to answer each of the research questions. Results: The search identified 22 papers related to modeling and automation of blood banking and transfusion, published in the period 1979-2022. The findings revealed that only four process modeling languages were reported to visualize process workflows. The preparation of blood components, serologic testing, blood distribution, apheresis, preparation for emergencies, maintaining blood banking and transfusion safety, and documentation have not been reported to have been modeled in the literature. This review revealed the lack of use of Business Process Modeling Notation (BPMN) as the industry standard process modeling language in the domain. The review also indicated a deficiency in modeling specialized processes in blood banking and transfusion, with the majority of reported processes being described as high level, but lacking elaboration. Automation was reported to improve transfusion safety, and to reduce cost, time cycle, and human errors. Conclusion: The work highlights the non-existence of a developed process architectural framework for blood banking and transfusion processes, which is needed to lay the groundwork for identifying and modeling strategic, managerial, and operational processes to bridge the gap with their enactment in healthcare systems. This paves the way for the development of a data-harvesting platform for blood banking and transfusion services.
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