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dc.contributor.authorGonzalez Aleu, Flores, F.F., Perez, J., Gonzalez, R., Garza-Reyes, J.A.
dc.identifier.citationGonzalez Aleu, Flores, F.F., Perez, J., Gonzalez, R., Garza-Reyes, J.A. (2020). 'Assessing Systematic Literature Review Bias: Kaizen Events in Hospitals Case Study'. Proceedings of the 10th Conference on Industrial Engineering and Operations Management (IEOM), Dubai, UAE, 10-12 March. US: IEOM Society International, pp. 1-8.en_US
dc.description.abstractA systematic literature review (SLR) is a protocol used to identify publications, select relevant publications, collect data, conduct scientometric analyses, and report research results (SLR outcomes or findings). Despite the increasing use of SLR to assess the maturity or evolution of a research field, as Engineering Management, there are a limit number of publications focused to test SLR biases. Therefore, the purposes of this investigation are to test search field bias (precise SLR vs. sensitive SLR) and to identify statistically significant differences between SLR outcomes. In order to achieve these goals, a three steps methodology was used in three platforms/databases. First, a precise SLR in ProQuest (search terms only in abstract) was conducted to identify publications describing a single Kaizen event in a hospital. From these publications, five metrics were assessed: new authors per year, number of authors per paper, number of publications per year, Kaizen event duration (days), and number of tools used during the Kaizen event per paper. Second, a sensitive SLR in ProQuest (search term in full text) was conducted using the same search terms, exclusion criteria, and metrics from the first step. Third, t-test hypotheses were conducted in SPSS version 20 to identify statistically significant difference for each metric between precise SLR vs. sensitive SLR. The same three steps were used in two more platforms/databases: EBSCOhost and Scopus. Initial results from this ongoing investigation show statistically significant differences between precise SLR and sensitive SLR for some of the five metrics assessed, such as the number of publications per year. Final results will be available in November 2018.en_US
dc.publisherIEOM Societyen_US
dc.rightsCC0 1.0 Universal*
dc.subjectSystematic literature review, kaizen event, rapid improvement event, hospital, biasen_US
dc.titleAssessing systematic literature review bias: kaizen events in hospitals case studyen_US
dc.typeMeetings and Proceedingsen_US
dc.contributor.departmentUniversity of Derbyen_US
dc.identifier.journalProceedings of the 10th International Conference on Industrial Engineering and Operations Management (IEOM)en_US

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