RT Journal Article
T1 Provenance Data Management in Health Information Systems: A Systematic Literature Review
A1 Sembay, Márcio José
A1 Jeronimo de Macedo, Douglas Dyllon
A1 Pioli Júnior, Laércio
A1 Maciel Braga, Regina Maria
A1 Sarasa Cabezuelo, Antonio
AB 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.
PB MDPI
SN 2075-4426
YR 2023
FD 2023-06-13
LK https://hdl.handle.net/20.500.14352/103617
UL https://hdl.handle.net/20.500.14352/103617
LA eng
NO Ministerio de Ciencia e Innovación (España)
DS Docta Complutense
RD 27 sept 2024