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A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.

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Title: A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.
Authors: Baghapour, Mohammad Ali1 baghapour@sums.ac.ir, Shooshtarian, Mohammad Reza2,3 mrshooshtarian@yahoo.com, Javaheri, Mohammad Reza1 m_reza_jh@yahoo.com, Dehghanifard, Sina1 s_i_n_a_h@yahoo.com, Sefidkar, Razieh1 rozisefidkar@yahoo.com, Nobandegani, Amir Fadaei1 amirfadaei66@gmail.com
Source: International Journal of Medical Informatics. Oct2018, Vol. 118, p5-15. 11p.
Subjects: Medical wastes, Hospital care, Medical decision making, Data mining, Medical economics, Comparative studies, Computer software, Consensus (Social sciences), Decision making, Health facility administration, Logic, Research methodology, Medical cooperation, Waste management, Research, Evaluation research, Medical waste disposal
Abstract: Background: Proper Health-Care Waste Management (HCWM) and integrated documentation in this sector of hospitals require analyzing massive data collected by hospital's health experts. This study presented a quantitative software-based index to assess the HCWM process performance by integrating ontology-based Multi-Criteria Group Decision-Making techniques and fuzzy modeling that were coupled with data mining. This framework represented the Complex Event Processing (CEP) and Corporate Performance Management (CPM) types of Process Mining in which a user-friendly software namely Group Fuzzy Decision-Making (GFDM) was employed for index calculation.Findings: Assessing the governmental hospitals of Shiraz, Iran in 2016 showed that the proposed index was able to determine the waste management condition and clarify the blind spots of HCWM in the hospitals. The index values under 50 were found in some of the hospitals showing poor process performance that should be at the priority of optimization and improvement.Conclusion: The proposed framework has distinctive features such as modeling the uncertainties (risks) in hospitals' process assessment and flexibility enabling users to define the intended criteria, stakeholders, and number of hospitals. Having computer-aided approach for decision process also accelerates the index calculation as well as its accuracy which would contribute to more willingness of hospitals' experts and other end-users to use the index in practice. The methodology could efficiently be employed as a tool for managing hospitals' event logs and digital documentation in big data environment not only for the health-care waste management, but also in other administrative wards of hospitals. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Medical Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Baghapour%2C+Mohammad+Ali%22">Baghapour, Mohammad Ali</searchLink><relatesTo>1</relatesTo><i> baghapour@sums.ac.ir</i><br /><searchLink fieldCode="AR" term="%22Shooshtarian%2C+Mohammad+Reza%22">Shooshtarian, Mohammad Reza</searchLink><relatesTo>2,3</relatesTo><i> mrshooshtarian@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Javaheri%2C+Mohammad+Reza%22">Javaheri, Mohammad Reza</searchLink><relatesTo>1</relatesTo><i> m_reza_jh@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Dehghanifard%2C+Sina%22">Dehghanifard, Sina</searchLink><relatesTo>1</relatesTo><i> s_i_n_a_h@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Sefidkar%2C+Razieh%22">Sefidkar, Razieh</searchLink><relatesTo>1</relatesTo><i> rozisefidkar@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Nobandegani%2C+Amir+Fadaei%22">Nobandegani, Amir Fadaei</searchLink><relatesTo>1</relatesTo><i> amirfadaei66@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Medical+Informatics%22">International Journal of Medical Informatics</searchLink>. Oct2018, Vol. 118, p5-15. 11p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Medical+wastes%22">Medical wastes</searchLink><br /><searchLink fieldCode="DE" term="%22Hospital+care%22">Hospital care</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+decision+making%22">Medical decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+economics%22">Medical economics</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Consensus+%28Social+sciences%29%22">Consensus (Social sciences)</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Health+facility+administration%22">Health facility administration</searchLink><br /><searchLink fieldCode="DE" term="%22Logic%22">Logic</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+cooperation%22">Medical cooperation</searchLink><br /><searchLink fieldCode="DE" term="%22Waste+management%22">Waste management</searchLink><br /><searchLink fieldCode="DE" term="%22Research%22">Research</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+research%22">Evaluation research</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+waste+disposal%22">Medical waste disposal</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: <bold>Background: </bold>Proper Health-Care Waste Management (HCWM) and integrated documentation in this sector of hospitals require analyzing massive data collected by hospital's health experts. This study presented a quantitative software-based index to assess the HCWM process performance by integrating ontology-based Multi-Criteria Group Decision-Making techniques and fuzzy modeling that were coupled with data mining. This framework represented the Complex Event Processing (CEP) and Corporate Performance Management (CPM) types of Process Mining in which a user-friendly software namely Group Fuzzy Decision-Making (GFDM) was employed for index calculation.<bold>Findings: </bold>Assessing the governmental hospitals of Shiraz, Iran in 2016 showed that the proposed index was able to determine the waste management condition and clarify the blind spots of HCWM in the hospitals. The index values under 50 were found in some of the hospitals showing poor process performance that should be at the priority of optimization and improvement.<bold>Conclusion: </bold>The proposed framework has distinctive features such as modeling the uncertainties (risks) in hospitals' process assessment and flexibility enabling users to define the intended criteria, stakeholders, and number of hospitals. Having computer-aided approach for decision process also accelerates the index calculation as well as its accuracy which would contribute to more willingness of hospitals' experts and other end-users to use the index in practice. The methodology could efficiently be employed as a tool for managing hospitals' event logs and digital documentation in big data environment not only for the health-care waste management, but also in other administrative wards of hospitals. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Medical Informatics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ijmedinf.2018.07.001
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 5
    Subjects:
      – SubjectFull: Medical wastes
        Type: general
      – SubjectFull: Hospital care
        Type: general
      – SubjectFull: Medical decision making
        Type: general
      – SubjectFull: Data mining
        Type: general
      – SubjectFull: Medical economics
        Type: general
      – SubjectFull: Comparative studies
        Type: general
      – SubjectFull: Computer software
        Type: general
      – SubjectFull: Consensus (Social sciences)
        Type: general
      – SubjectFull: Decision making
        Type: general
      – SubjectFull: Health facility administration
        Type: general
      – SubjectFull: Logic
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Medical cooperation
        Type: general
      – SubjectFull: Waste management
        Type: general
      – SubjectFull: Research
        Type: general
      – SubjectFull: Evaluation research
        Type: general
      – SubjectFull: Medical waste disposal
        Type: general
    Titles:
      – TitleFull: A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.
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            NameFull: Baghapour, Mohammad Ali
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            NameFull: Shooshtarian, Mohammad Reza
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            NameFull: Nobandegani, Amir Fadaei
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            – D: 01
              M: 10
              Text: Oct2018
              Type: published
              Y: 2018
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              Value: 118
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            – TitleFull: International Journal of Medical Informatics
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