Análise de big data aplicada a serviços de saúde: uma revisão de literatura
DOI:
https://doi.org/10.5585/exactaep.2021.17297Palavras-chave:
Análise de big data, Serviços de saúde, Análise de saúde, Transferência de tecnologia.Resumo
O objetivo deste estudo é compreender os conceitos e a evolução da análise de big data aplicada aos serviços de saúde, considerando as atividades que envolvem o diagnóstico, tratamento e manejo do paciente. A revisão da literatura, consultando as bases de dados Science Direct, Scopus e Web of Science e empregando as palavras-chave health analytics e big data analytics sem restrições de tempo, encontrou trabalhos que abordam, especificamente, o uso de big data analytics no contexto da saúde, representados por exemplos e análises relacionadas. O tempo e a tomada de decisão aparecem como ações desenvolvidas tanto pela equipe de tecnologia da informação quanto pela equipe clínica, podendo considerar variáveis como custo, tempo, decisão e desempenho da estrutura funcional como os principais determinantes alinhados à estratégia corporativa. Este trabalho espera fomentar pesquisas sobre aspectos da saúde pública, além de considerar a preocupação com a sobrevivência das pessoas afetadas.Downloads
Referências
Alharthi, H. (2018). Healthcare predictive analytics: An overview with a focus on Saudi Arabia. Journal of infection and public health, 11(6), 749-756. https://doi.org/10.1016/j.jiph.2018.02.005.
Alkobaisi, S., Bae, W. D., Horak, M., Narayanappa, S., Lee, J., AbuKhousa, E., ... & Bae, D. J. (2019). Predictive and exposome analytics: A case study of asthma exacerbation management. Journal of Ambient Intelligence and Smart Environments, (Preprint), 1-26. https://doi.org/10.3233/AIS-190540
Abusharekh, A., Stewart, S. A., Hashemian, N., & Abidi, S. S. R. (2015, June). H-DRIVE: A Big Health Data Analytics Platform for Evidence-Informed Decision Making. In 2015 IEEE International Congress on Big Data (pp. 416-423). IEEE. https://doi.org/10.1109/BigDataCongress.2015.68
Balaji, S., Patil, M., & McGregor, C. (2017, June). A cloud based big data based online health analytics for rural nicus and picus in india: Opportunities and challenges. In 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 385-390). IEEE. https://doi.org/10.1109/CBMS.2017.112
Batarseh, F. A., & Latif, E. A. (2016). Assessing the quality of service using big data analytics: with application to healthcare. Big Data Research, 4, 13-24. https://doi.org/10.1016/j.bdr.2015.10.001
Balthazar, P., Harri, P., Prater, A., & Safdar, N. M. (2018). Protecting your patients’ interests in the era of big data, artificial intelligence, and predictive analytics. Journal of the American College of Radiology, 15(3), 580-586. https://doi.org/10.1016/j.jacr.2017.11.035
Blandford, A. (2019). HCI for health and wellbeing: Challenges and opportunities. International Journal of Human-Computer Studies, 131, 41-51. https://doi.org/10.1016/j.ijhcs.2019.06.007.
Cano, I., Tenyi, A., Vela, E., Miralles, F., & Roca, J. (2017). Perspectives on big data applications of health information. Current Opinion in Systems Biology, 3, 36-42. https://doi.org/10.1016/j.coisb.2017.04.012
Emani, C. K., Cullot, N., & Nicolle, C. (2015). Understandable big data: a survey. Computer science review, 17, 70-81. https://doi.org/10.1016/j.cosrev.2015.05.002
Galetsi, P., Katsaliaki, K., & Kumar, S. (2020). Big data analytics in health sector: Theoretical framework, techniques and prospects. International Journal of Information Management, 50, 206-216. https://doi.org/10.1016/j.ijinfomgt.2019.05.003
Galetsi, P., Katsaliaki, K., & Kumar, S. (2019). Values, challenges and future directions of big data analytics in healthcare: A systematic review. Social Science & Medicine, 241, 112533. https://doi.org/10.1016/j.socscimed.2019.112533
Galetsi, P., & Katsaliaki., & Kumar. (2019). Big Data Analytics in Health: an overview and bibliometric study of research activity. Health Information & Libraries Journal. https://doi.org/10.1111/hir.12286
Galetsi, P., & Katsaliaki., & Kumar. (2019). A review of the literature on big data analytics in healthcare. Journal of the Operational Research Society, 1-19. https://doi.org/10.1080/01605682.2019.1630328
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International journal of information management, 35(2), 137-144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
Gonzalez-Alonso, P., Vilar, R., & Lupiáñez-Villanueva, F. (2017, June). Meeting Technology and Methodology into Health Big Data Analytics Scenarios. In 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 284-285). IEEE. https://doi.org/10.1109/CBMS.2017.71
Harerimana, G., Jang, B., Kim, J. W., & Park, H. K. (2018). Health big data analytics: A technology survey. IEEE Access, 6, 65661-65678. https://doi.org/10.1109/ACCESS.2018.2878254
Kakhki, M. D., Singh, R., & Loyd, K. W. (2015). Developing Health Analytics Design Artifact for Improved Patient Activation: An On-going Case Study. In New Contributions in Information Systems and Technologies (pp. 733-739). Springer, Cham. https://doi.org/ 10.1007/978-3-319-16486-1_72
Kan, H., Nagar, S., Patel, J., Wallace, D. J., Molta, C., & Chang, D. J. (2016). Longitudinal treatment patterns and associated outcomes in patients with newly diagnosed systemic lupus erythematosus. Clinical Therapeutics, 38(3), 610-624. https://doi.org/10.1016/j.clinthera.2016.01.016
kBioAssist, S. (2017). CrowdHEALTH: Holistic Health Records and Big Data Analytics for Health Policy Making and Personalized Health. Informatics Empowers Healthcare Transformation, 238, 19. http://dx.doi.org/10.3233/978-1-61499-781-8-19
Khennou, F., Khamlichi, Y. I., & Chaoui, N. E. H. (2018). Improving the Use of Big Data Analytics within Electronic Health Records: A Case Study based OpenEHR. Procedia Computer Science, 127, 60-68. https://doi.org/10.1016/j.procs.2018.01.098
Manyika, J. (2011). Big data: The next frontier for innovation, competition, and productivity. http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation
McGregor, C., & Majola, P. X. (2019, June). Opportunities for a Cloud Based Health Analytics as a Service for Eastern Cape Initiation Schools in South Africa. In 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 531-534). IEEE. https://doi.org/10.1109/CBMS.2019.00108
Moutselos, K., Kyriazis, D., & Maglogiannis, I. (2018, July). A Web Based Modular Environment for Assisting Health Policy Making Utilizing Big Data Analytics. In 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA) (pp. 1-5). IEEE. https://doi.org/10.1109/IISA.2018.8633625
Moutselos, K., Kyriazis, D., Diamantopoulou, V., & Maglogiannis, I. (2018, December). Trustworthy data processing for health analytics tasks. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 3774-3779). IEEE. https://doi.org/10.1109/BigData.2018.8622449
Nambiar, R., Bhardwaj, R., Sethi, A., & Vargheese, R. (2013, October). A look at challenges and opportunities of big data analytics in healthcare. In 2013 IEEE international conference on Big Data (pp. 17-22). IEEE. https://doi.org/10.1109/BigData.2013.6691753
Nguyen, T., Larsen, M., O’Dea, B., Nguyen, H., Nguyen, D. T., Yearwood, J., ... & Christensen, H. (2018). Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2018.01.014
Oussous, A., Benjelloun, F. Z., Lahcen, A. A., & Belfkih, S. (2018). Big Data technologies: A survey. Journal of King Saud University-Computer and Information Sciences, 30(4), 431-448. https://doi.org/10.1016/j.jksuci.2017.06.001
Pagani, R. N., Kovaleski, J. L., & Resende, L. M. (2015). Methodi Ordinatio: a proposed methodology to select and rank relevant scientific papers encompassing the impact factor, number of citation, and year of publication. Scientometrics, 105(3), 2109-2135. https://doi.org/10.1007/s11192-015-1744-x
Pashazadeh, A., & Navimipour, N. J. (2018). Big data handling mechanisms in the healthcare applications: A comprehensive and systematic literature review. Journal of biomedical informatics, 82, 47-62. https://doi.org/10.1016/j.jbi.2018.03.014
Poornima, S., & Pushpalatha, M. (2020). A survey on various applications of prescriptive analytics. International Journal of Intelligent Networks, 1, 76-84. https://doi.org/10.1016/j.ijin.2020.07.001
Sabra, S., Malik, K. M., & Alobaidi, M. (2018). Prediction of venous thromboembolism using semantic and sentiment analyses of clinical narratives. Computers in biology and medicine, 94, 1-10. https://doi.org/10.1016/j.compbiomed.2017.12.026
Saggi, M. K., & Jain, S. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing & Management, 54(5), 758-790. https://doi.org/10.1016/j.ipm.2018.01.010
Stephanie, L., & Sharma, R. S. (2020). Digital health eco-systems: An epochal review of practice-oriented research. International Journal of Information Management, 53, 102032. https://doi.org/10.1016/j.ijinfomgt.2019.10.017
Shafqat, S., Kishwer, S., Rasool, R. U., Qadir, J., Amjad, T., & Ahmad, H. F. (2020). Big data analytics enhanced healthcare systems: a review. The Journal of Supercomputing, 76(3), 1754-1799. https://doi.org/10.1007/s11227-017-2222-4
Suresh, S. (2016). Big data and predictive analytics: applications in the care of children. Pediatric Clinics, 63(2), 357-366. https://doi.org/10.1016/j.pcl.2015.12.007
Xu, Z. (2019). An empirical study of patients' privacy concerns for health informatics as a service. Technological Forecasting and Social Change, 143, 297-306. https://doi.org/10.1016/j.techfore.2019.01.018
Zhou, Y., Zhao, L., Zhou, N., Zhao, Y., Marino, S., Wang, T., ... & Dinov, I. D. (2019). Predictive Big Data Analytics using the UK Biobank Data. Scientific reports, 9(1), 6012. https://doi.org/10.1038/s41598-019-41634-y
Wlodarczak, P., Soar, P., & Ally, M. (2015). Behavioural health analytics using mobile phones. EAI Endorsed Trans. Scalable Information Systems, 2(5), e6. https://doi.org/10.4108/sis.2.5.e6
Wlodarczak, P., Soar, J., & Ally, M. (2015, May). Reality mining in eHealth. In International Conference on Health Information Science (pp. 1-6). Springer, Cham. https://doi.org/ 10.1007/978-3-319-19156-0_1
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2021 Exacta
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.