Provenance Data Management in Health Information Systems: A Systematic Literature Review
Aims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/13/6/991 |
| _version_ | 1797593915874869248 |
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| author | Márcio José Sembay Douglas Dyllon Jeronimo de Macedo Laércio Pioli Júnior Regina Maria Maciel Braga Antonio Sarasa-Cabezuelo |
| author_facet | Márcio José Sembay Douglas Dyllon Jeronimo de Macedo Laércio Pioli Júnior Regina Maria Maciel Braga Antonio Sarasa-Cabezuelo |
| author_sort | Márcio José Sembay |
| collection | DOAJ |
| description | Aims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. Method: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. Results: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. Conclusion: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs. |
| first_indexed | 2024-03-11T02:15:18Z |
| format | Article |
| id | doaj.art-46df62d256b7481ab51f5f6590188d36 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-11T02:15:18Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-46df62d256b7481ab51f5f6590188d362023-11-18T11:11:35ZengMDPI AGJournal of Personalized Medicine2075-44262023-06-0113699110.3390/jpm13060991Provenance Data Management in Health Information Systems: A Systematic Literature ReviewMárcio José Sembay0Douglas Dyllon Jeronimo de Macedo1Laércio Pioli Júnior2Regina Maria Maciel Braga3Antonio Sarasa-Cabezuelo4Department of Information Science, Federal University of Santa Catarina, Florianópolis 88040-900, BrazilDepartment of Information Science, Federal University of Santa Catarina, Florianópolis 88040-900, BrazilDepartment of Computer Science, Federal University of Santa Catarina, Florianópolis 88040-370, BrazilDepartment of Computer Science, Federal University of Juiz of Fora, Juiz de Fora 36036-330, BrazilDepartment of Computer Science, Complutense University of Madrid (UCM), 28040 Madrid, SpainAims: This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results. Method: An SLR was performed on six databases using a search string. The backward and forward snowballing technique was also used. Eligible studies were all articles in English that presented on the use of different methods, techniques, models, methodologies, and technologies related to provenance data management in HISs. The quality of the included articles was assessed to obtain a better connection to the topic studied. Results: Of the 239 studies retrieved, 14 met the inclusion criteria described in this SLR. In order to complement the retrieved studies, 3 studies were included using the backward and forward snowballing technique, totaling 17 studies dedicated to the construction of this research. Most of the selected studies were published as conference papers, which is common when involving computer science in HISs. There was a more frequent use of data provenance models from the PROV family in different HISs combined with different technologies, among which blockchain and middleware stand out. Despite the advantages found, the lack of technological structure, data interoperability problems, and the technical unpreparedness of working professionals are still challenges encountered in the management of provenance data in HISs. Conclusion: It was possible to conclude the existence of different methods, techniques, models, and combined technologies, which are presented in the proposal of a taxonomy that provides researchers with a new understanding about the management of provenance data in HISs.https://www.mdpi.com/2075-4426/13/6/991provenance data managementdata provenanceprovenance datahealth information systemshealth datahealth data management |
| spellingShingle | Márcio José Sembay Douglas Dyllon Jeronimo de Macedo Laércio Pioli Júnior Regina Maria Maciel Braga Antonio Sarasa-Cabezuelo Provenance Data Management in Health Information Systems: A Systematic Literature Review Journal of Personalized Medicine provenance data management data provenance provenance data health information systems health data health data management |
| title | Provenance Data Management in Health Information Systems: A Systematic Literature Review |
| title_full | Provenance Data Management in Health Information Systems: A Systematic Literature Review |
| title_fullStr | Provenance Data Management in Health Information Systems: A Systematic Literature Review |
| title_full_unstemmed | Provenance Data Management in Health Information Systems: A Systematic Literature Review |
| title_short | Provenance Data Management in Health Information Systems: A Systematic Literature Review |
| title_sort | provenance data management in health information systems a systematic literature review |
| topic | provenance data management data provenance provenance data health information systems health data health data management |
| url | https://www.mdpi.com/2075-4426/13/6/991 |
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