This article provides a thorough examination of healthcare data analytics and identifies various unresolved questions that necessitate further investigation. The implementation of healthcare analytics has the potential to generate two supplementary advantages for healthcare providers, specifically heightened patient contentment and ameliorated health consequences. The field of data analytics has been propelled forward by the facilitation of healthcare data acquisition through technological and software advancements. The lack of a predetermined framework in the data, along with the constraints imposed by privacy considerations in data gathering and dissemination methods, have presented significant obstacles to the progression of the field. The expeditious handling and comprehension of data requires prompt decision-making in the presence of substantial information quantities. In specific situations, the retrieval and analysis of data may necessitate the utilisation of more advanced techniques owing to the intricacy of the data. The emergence of data collection technologies that facilitate analytics has presented new obstacles, despite their effectiveness in accumulating vast quantities of data. The healthcare industry employs a wide array of methodologies, which can be attributed to the inherent distinctions in the fundamental data types.
Keywords
Healthcare Data Analytics, Electronic Health Records, Clinical Text Mining, Clinic-Genomic Data Integration, Temporal Data Mining.
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June Huh Eddie
June Huh Eddie
Department of Biomedical Engineering, Bauman Moscow State Technical University, Moscow, Russia, 105005.
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Cite this article
June Huh Eddie, “A Review of Medical Data Sources, and Advanced Data Analytics in the Medical Sector”, Journal of Biomedical and Sustainable Healthcare Applications, vol.3, no.2, pp. 106-117, July 2023. doi: 10.53759/0088/JBSHA202303011.
