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Journal Article
Review
Systematic review of using medical informatics in lung transplantation studies.
International Journal of Medical Informatics 2020 April
BACKGROUND: Lung transplantation is one of the advanced treatment options performed even in patients suffering from end-stage lung disease. Due to the positive results of medical informatics in other fields of medicine, lung transplant researchers have also conducted remarkable studies to improve transplant outcomes. The main objective of this article was to review the current studies of health information technology used in lung transplantation.
METHODS: A systematic search was performed in four scientific databases (Web of Science, Scopus, Science Direct, and PubMed) from January 2000 to December 2018. The criteria for inclusion were included in any study describing the use of health information technology or medical informatics in terms of lung transplantation, English papers, and original researchers. The retrieved articles were accordingly screened based on the inclusion and exclusion criteria to select relevant studies. The survey and synthesis of included articles were conducted based on predefined classification.
RESULTS: Out of 263 articles, 27 studies met our inclusion criteria. All included studies involved the application of health information technology in lung transplantation. The types of health information technology methods applied in reviewed articles included mhealth (11.1 %), DSS (7.4 %), decision aid tools (7.4 %), telemedicine (22.2 %), AI methods (11.1 %), data mining (37 %), and patient education (3.7 %). The majority of studies (88.9 %) showed the positive impact of health information technology to enhance lung transplantation outcomes. Finally, the main approaches in different phases of lung transplantation processes were interpreted and summarized in the visual model.
CONCLUSION: This systematic review provides new insights regarding the application of medical informatics in the lung transplantation domain. The missing areas of medical informatics in the lung transplantation domain were recognized through this study.
METHODS: A systematic search was performed in four scientific databases (Web of Science, Scopus, Science Direct, and PubMed) from January 2000 to December 2018. The criteria for inclusion were included in any study describing the use of health information technology or medical informatics in terms of lung transplantation, English papers, and original researchers. The retrieved articles were accordingly screened based on the inclusion and exclusion criteria to select relevant studies. The survey and synthesis of included articles were conducted based on predefined classification.
RESULTS: Out of 263 articles, 27 studies met our inclusion criteria. All included studies involved the application of health information technology in lung transplantation. The types of health information technology methods applied in reviewed articles included mhealth (11.1 %), DSS (7.4 %), decision aid tools (7.4 %), telemedicine (22.2 %), AI methods (11.1 %), data mining (37 %), and patient education (3.7 %). The majority of studies (88.9 %) showed the positive impact of health information technology to enhance lung transplantation outcomes. Finally, the main approaches in different phases of lung transplantation processes were interpreted and summarized in the visual model.
CONCLUSION: This systematic review provides new insights regarding the application of medical informatics in the lung transplantation domain. The missing areas of medical informatics in the lung transplantation domain were recognized through this study.
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