BIG DATA IN HEALTHCARE: OPPORTUNITIES FOR IMPROVED PATIENT CARE AND SECURITY CONCERNS
Main Article Content
Keywords
Big Data, Healthcare, Patient Care, Security Risks, Predictive Analytics, Personalized Medicine, Data Protection, Encryption, Compliance
Abstract
This literature review explores the impact of big data in healthcare, focusing on its potential to improve patient care and the associated security risks. The study examines various big data applications, including predictive analytics, personalized medicine, and enhanced operational efficiencies, contributing to better diagnostics, treatment protocols, and patient outcomes. It also addresses significant security challenges such as data breaches, encryption practices, and compliance with data protection regulations. Through an analysis of articles from databases like PubMed and PsycINFO, the review identifies key themes and demonstrates how big data can revolutionize healthcare while presenting risks to privacy and system integrity. The findings highlight the need for collaboration among healthcare providers, policymakers, and technologists to leverage big data benefits in healthcare delivery securely.
References
[1] A. Alyass, M. Turcotte, and D. Meyre, “From big data analysis to personalized medicine for all: challenges and opportunities,” BMC Med. Genomics, vol. 8, no. 1, p. 33, Dec. 2015, doi: 10.1186/s12920-015-0108-y.
[2] M. Hassan et al., “Innovations in genomics and big data analytics for personalized medicine and health care: A review,” Int. J. Mol. Sci., vol. 23, no. 9, p. 4645, 2022.
[3] A. Alhur, “Exploring Saudi Arabia Individuals’ Attitudes toward Electronic Personal Health Records,” J. Comput. Sci. Technol. Stud., vol. 4, no. 1, pp. 80–87, 2022.
[4] K. Adnan, R. Akbar, S. W. Khor, and A. B. A. Ali, “Role and Challenges of Unstructured Big Data in Healthcare,” in Data Management, Analytics and Innovation, vol. 1042, N. Sharma, A. Chakrabarti, and V. E. Balas, Eds., in Advances in Intelligent Systems and Computing, vol. 1042. , Singapore: Springer Singapore, 2020, pp. 301–323. doi: 10.1007/978-981-32-9949-8_22.
[5] M. Adibuzzaman, P. DeLaurentis, J. Hill, and B. D. Benneyworth, “Big data in healthcare–the promises, challenges and opportunities from a research perspective: A case study with a model database,” in AMIA Annual Symposium Proceedings, American Medical Informatics Association, 2017, p. 384. Accessed: Apr. 21, 2024. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977694/
[6] A. L. Beam and I. S. Kohane, “Big data and machine learning in health care,” Jama, vol. 319, no. 13, pp. 1317–1318, 2018.
[7] P. K. D. Pramanik, S. Pal, and M. Mukhopadhyay, “Healthcare big data: A comprehensive overview,” Res. Anthol. Big Data Anal. Archit. Appl., pp. 119–147, 2022.
[8] A. A. Alhur, “The Effectiveness of E-learning in Saudi Arabia During the Spread of COVID-19,” Int. J. Adv. Res. Educ. Soc., vol. 3, no. 4, pp. 156–165, 2021.
[9] S. Dash, S. K. Shakyawar, M. Sharma, and S. Kaushik, “Big data in healthcare: management, analysis and future prospects,” J. Big Data, vol. 6, no. 1, p. 54, Dec. 2019, doi: 10.1186/s40537-019-0217-0.
[10] I. D. Dinov, “Volume and value of big healthcare data,” J. Med. Stat. Inform., vol. 4, 2016, Accessed: Apr. 21, 2024. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795481/
[11] A. Khanan, S. Abdullah, A. H. H. M. Mohamed, A. Mehmood, and K. A. Z. Ariffin, “Big Data Security and Privacy Concerns: A Review,” in Smart Technologies and Innovation for a Sustainable Future, A. Al-Masri and K. Curran, Eds., in Advances in Science, Technology & Innovation. , Cham: Springer International Publishing, 2019, pp. 55–61. doi: 10.1007/978-3-030-01659-3_8.
[12] D. S. Terzi, R. Terzi, and S. Sagiroglu, “A survey on security and privacy issues in big data,” in 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), IEEE, 2015, pp. 202–207. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7412089/
[13] Y. Gahi, M. Guennoun, and H. T. Mouftah, “Big data analytics: Security and privacy challenges,” in 2016 IEEE Symposium on Computers and Communication (ISCC), IEEE, 2016, pp. 952–957. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7543859/
[14] E. Bertino and E. Ferrari, “Big Data Security and Privacy,” in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, vol. 31, S. Flesca, S. Greco, E. Masciari, and D. Saccà, Eds., in Studies in Big Data, vol. 31. , Cham: Springer International Publishing, 2018, pp. 425–439. doi: 10.1007/978-3-319-61893-7_25.
[15] A. Alhur, “Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot,” Cureus, vol. 16, no. 4, 2024, Accessed: Apr. 13, 2024. [Online]. Available: https://www.cureus.com/articles/243466-redefining-healthcare-with-artificial-intelligence-ai-the-contributions-of-chatgpt-gemini-and-co-pilot.pdf
[16] H. Alharthi, “Healthcare predictive analytics: An overview with a focus on Saudi Arabia,” J. Infect. Public Health, vol. 11, no. 6, pp. 749–756, 2018.
[17] B. Boukenze, H. Mousannif, and A. Haqiq, “Predictive analytics in healthcare system using data mining techniques,” Comput Sci Inf Technol, vol. 1, pp. 1–9, 2016.
[18] V. X. Liu, D. W. Bates, J. Wiens, and N. H. Shah, “The number needed to benefit: estimating the value of predictive analytics in healthcare,” J. Am. Med. Inform. Assoc., vol. 26, no. 12, pp. 1655–1659, 2019.
[19] A. Muniasamy, S. Tabassam, M. A. Hussain, H. Sultana, V. Muniasamy, and R. Bhatnagar, “Deep Learning for Predictive Analytics in Healthcare,” in The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019), vol. 921, A. E. Hassanien, A. T. Azar, T. Gaber, R. Bhatnagar, and M. F. Tolba, Eds., in Advances in Intelligent Systems and Computing, vol. 921. , Cham: Springer International Publishing, 2020, pp. 32–42. doi: 10.1007/978-3-030-14118-9_4.
[20] V.-K. Lakshmanan, S. Ojha, and Y. Do Jung, “A modern era of personalized medicine in the diagnosis, prognosis, and treatment of prostate cancer,” Comput. Biol. Med., vol. 126, p. 104020, 2020.
[21] N. Jain, U. Nagaich, M. Pandey, D. K. Chellappan, and K. Dua, “Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements,” EPMA J., vol. 13, no. 4, pp. 561–580, Nov. 2022, doi: 10.1007/s13167-022-00304-2.
[22] S. Chintala, “AI-Driven Personalised Treatment Plans: The Future of Precision Medicine,” Mach. Intell. Res., vol. 17, no. 02, pp. 9718–9728, 2023.
[23] B. Y. Kasula, “Advancements in AI-driven Healthcare: A Comprehensive Review of Diagnostics, Treatment, and Patient Care Integration,” Int. J. Mach. Learn. Sustain. Dev., vol. 1, no. 1, pp. 1–5, 2024.
[24] A. Pulumati, A. Pulumati, B. S. Dwarakanath, A. Verma, and R. V. L. Papineni, “Technological advancements in cancer diagnostics: Improvements and limitations,” Cancer Rep., vol. 6, no. 2, p. e1764, Feb. 2023, doi: 10.1002/cnr2.1764.
[25] S. Abdallah et al., “The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders,” Cureus, vol. 15, no. 10, 2023, Accessed: Apr. 21, 2024. [Online]. Available: https://www.cureus.com/articles/195184-the-impact-of-artificial-intelligence-on-optimizing-diagnosis-and-treatment-plans-for-rare-genetic-disorders.pdf
[26] E. D. Esplin, L. Oei, and M. P. Snyder, “Personalized sequencing and the future of medicine: discovery, diagnosis and defeat of disease,” Pharmacogenomics, vol. 15, no. 14, pp. 1771–1790, Nov. 2014, doi: 10.2217/pgs.14.117.
[27] S. S. Kamble and A. Gunasekaran, “Big data-driven supply chain performance measurement system: a review and framework for implementation,” Int. J. Prod. Res., vol. 58, no. 1, pp. 65–86, Jan. 2020, doi: 10.1080/00207543.2019.1630770.
[28] K. L. Keung, C. K. Lee, and P. Ji, “Data-driven order correlation pattern and storage location assignment in robotic mobile fulfillment and process automation system,” Adv. Eng. Inform., vol. 50, p. 101369, 2021.
[29] P. Ghimire, M. Zadeh, J. Thorstensen, and E. Pedersen, “Data-driven efficiency modeling and analysis of all-electric ship powertrain: A comparison of power system architectures,” IEEE Trans. Transp. Electrification, vol. 8, no. 2, pp. 1930–1943, 2021.
[30] R. K. Singh, S. Agrawal, A. Sahu, and Y. Kazancoglu, “Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda,” TQM J., vol. 35, no. 1, pp. 262–291, 2023.
[31] Y. Wang, L. Kung, and T. A. Byrd, “Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations,” Technol. Forecast. Soc. Change, vol. 126, pp. 3–13, 2018.
[32] D. W. Bates, S. Saria, L. Ohno-Machado, A. Shah, and G. Escobar, “Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients,” Health Aff. (Millwood), vol. 33, no. 7, pp. 1123–1131, Jul. 2014, doi: 10.1377/hlthaff.2014.0041.
[33] Y. Wang, L. Kung, W. Y. C. Wang, and C. G. Cegielski, “An integrated big data analytics-enabled transformation model: Application to health care,” Inf. Manage., vol. 55, no. 1, pp. 64–79, 2018.
[34] K. Pendry, “The use of big data in transfusion medicine,” Transfus. Med., vol. 25, no. 3, pp. 129–137, Jun. 2015, doi: 10.1111/tme.12223.
[35] M. I. Fernández, P. Chanfreut, I. Jurado, and J. M. Maestre, “A data-based model predictive decision support system for inventory management in hospitals,” IEEE J. Biomed. Health Inform., vol. 25, no. 6, pp. 2227–2236, 2020.
[36] L. Galli, T. Levato, F. Schoen, and L. Tigli, “Prescriptive analytics for inventory management in health care,” J. Oper. Res. Soc., vol. 72, no. 10, pp. 2211–2224, Oct. 2021, doi: 10.1080/01605682.2020.1776167.
[37] S. Guha and S. Kumar, “Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap,” Prod. Oper. Manag., vol. 27, no. 9, pp. 1724–1735, Sep. 2018, doi: 10.1111/poms.12833.
[38] M. I. Pramanik, R. Y. Lau, H. Demirkan, and M. A. K. Azad, “Smart health: Big data enabled health paradigm within smart cities,” Expert Syst. Appl., vol. 87, pp. 370–383, 2017.
[39] M. Adams, “Big data and individual privacy in the age of the internet of things,” Technol. Innov. Manag. Rev., vol. 7, no. 4, 2017, Accessed: Apr. 21, 2024. [Online]. Available: https://timreview.ca/sites/default/files/article_PDF/Adams_TIMReview_April2017.pdf
[40] H. K. Patil and R. Seshadri, “Big data security and privacy issues in healthcare,” in 2014 IEEE international congress on big data, IEEE, 2014, pp. 762–765. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/6906856/
[41] C. Schmitt, M. Shoffner, P. Owen, X. Wang, and B. Lamm, “Security and privacy in the era of big data,” SMW Technol. Solut. Chall. Data Leakage, vol. 1, no. 2, 2013, Accessed: Apr. 21, 2024. [Online]. Available: https://www.renci.org/wp-content/uploads/2014/02/0313WhitePaper-iRODS.pdf
[42] H. Tao et al., “Economic perspective analysis of protecting big data security and privacy,” Future Gener. Comput. Syst., vol. 98, pp. 660–671, 2019.
[43] N. Menachemi and T. H. Collum, “Benefits and drawbacks of electronic health record systems,” Risk Manag. Healthc. Policy, pp. 47–55, 2011.
[44] A. Mehmood, I. Natgunanathan, Y. Xiang, G. Hua, and S. Guo, “Protection of big data privacy,” IEEE Access, vol. 4, pp. 1821–1834, 2016.
[45] K. A. Salleh and L. Janczewski, “Technological, organizational and environmental security and privacy issues of big data: A literature review,” Procedia Comput. Sci., vol. 100, pp. 19–28, 2016.
[46] D. S. Terzi, R. Terzi, and S. Sagiroglu, “A survey on security and privacy issues in big data,” in 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), IEEE, 2015, pp. 202–207. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7412089/
[47] H. S. Fhom, “Big Data: Opportunities and Privacy Challenges.” arXiv, Feb. 03, 2015. Accessed: Apr. 21, 2024. [Online]. Available: http://arxiv.org/abs/1502.00823
[48] S. Varshney, D. Munjal, O. Bhattacharya, S. Saboo, and N. Aggarwal, “Big data privacy breach prevention strategies,” in 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), IEEE, 2020, pp. 1–6. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9358878/
[49] P. Sharma and S. Barua, “From data breach to data shield: the crucial role of big data analytics in modern cybersecurity strategies,” Int. J. Inf. Cybersecurity, vol. 7, no. 9, pp. 31–59, 2023.
[50] T. van den Broek and A. F. van Veenstra, “Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation,” Technol. Forecast. Soc. Change, vol. 129, pp. 330–338, 2018.
[51] T. Duchamp, “Big Data is the Cornerstone of Regulatory Compliance Systems,” in The FinTech Book, 1st ed., S. Chishti and J. Barberis, Eds., Wiley, 2016, pp. 100–105. doi: 10.1002/9781119218906.ch26.
[52] A. Gupta, A. Verma, P. Kalra, and L. Kumar, “Big Data: A security compliance model,” in 2014 Conference on IT in Business, Industry and Government (CSIBIG), IEEE, 2014, pp. 1–5. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7056963/
[53] P. Jain, M. Gyanchandani, and N. Khare, “Big data privacy: a technological perspective and review,” J. Big Data, vol. 3, no. 1, p. 25, Dec. 2016, doi: 10.1186/s40537-016-0059-y.
[54] Z. Wan, J. W. Hazel, E. W. Clayton, Y. Vorobeychik, M. Kantarcioglu, and B. A. Malin, “Sociotechnical safeguards for genomic data privacy,” Nat. Rev. Genet., vol. 23, no. 7, pp. 429–445, 2022.
[55] U. Pagallo, “The legal challenges of big data: putting secondary rules first in the field of EU data protection,” Eur Data Prot Rev, vol. 3, p. 36, 2017.
[56] L. A. Shihab, “Technological tools for data security in the treatment of data reliability in big data environments,” Int. Trans. J. Eng. Manag. Appl. Sci. Technol., vol. 11, no. 9, pp. 1–13, 2020.
[57] R. Cumbley and P. Church, “Is ‘big data’ creepy?,” Comput. Law Secur. Rev., vol. 29, no. 5, pp. 601–609, 2013.
[58] A. Alhur et al., “ASSESSING SAUDI ARABIAN INDIVIDUALS’ATTITUDES AND PERCEPTIONS ON THE CONFIDENTIALITY AND PRIVACY OF ELECTRONIC HEALTH AND MEDICAL INFORMATION,” J. Popul. Ther. Clin. Pharmacol., vol. 30, no. 16, pp. 742–752, 2023.
[59] A. A. ALHUR, “Public Health Informatics: The Importance of Covid-19 Dashboard in KSA for Sharing and Visualizing Health Information,” J. Inf. Syst. Digit. Technol., vol. 5, no. 1, pp. 43–59, 2023.
[60] A. A. Alhur, “Public Health Informatics: The Importance of COVID-19 Dashboard in KSA: Health Information Sharing and Visualization,” J. Health Sci. Med. Dev., vol. 2, no. 02, pp. 64–79, 2023.
[61] D. B. Rawat, R. Doku, and M. Garuba, “Cybersecurity in big data era: From securing big data to data-driven security,” IEEE Trans. Serv. Comput., vol. 14, no. 6, pp. 2055–2072, 2019.
[62] A. Nassar and M. Kamal, “Machine Learning and Big Data analytics for Cybersecurity Threat Detection: A Holistic review of techniques and case studies,” J. Artif. Intell. Mach. Learn. Manag., vol. 5, no. 1, pp. 51–63, 2021.
[63] A. Alhur and A. A. Alhur, “The Acceptance of Digital Health: What about Telepsychology and Telepsychiatry?,” J. Sist. Inf., vol. 18, no. 2, pp. 18–35, 2022.
[64] M. L. Montagnani and M. A. Cavallo, “Cybersecurity and Liability in a Big Data World,” Mkt Compet. Rev, vol. 2, p. 71, 2018.
[65] J. Gao, H. Aziz, P. Maropoulos, and W. Cheung, “Application of product data management technologies for enterprise integration,” Int. J. Comput. Integr. Manuf., vol. 16, no. 7–8, pp. 491–500, Jan. 2003, doi: 10.1080/0951192031000115813.
[66] V. Bianchi et al., “Integrated systems for NGS data management and analysis: open issues and available solutions,” Front. Genet., vol. 7, p. 75, 2016.
[67] J. Chen, L. Ramanathan, and M. Alazab, “Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management of smart cities,” Microprocess. Microsyst., vol. 81, p. 103722, 2021.
[68] A. A. Alhur et al., “Telemental health and artificial intelligence: knowledge and attitudes of Saudi Arabian individuals towards ai-integrated telemental health,” J. Popul. Ther. Clin. Pharmacol., vol. 30, no. 17, pp. 1993–2009, 2023.
[69] Y. Ye, J. Shi, D. Zhu, L. Su, J. Huang, and Y. Huang, “Management of medical and health big data based on integrated learning-based health care system: a review and comparative analysis,” Comput. Methods Programs Biomed., vol. 209, p. 106293, 2021.
[70] M. Jayaratne et al., “A data integration platform for patient-centered e-healthcare and clinical decision support,” Future Gener. Comput. Syst., vol. 92, pp. 996–1008, 2019.
[71] S. Nazir et al., “A comprehensive analysis of healthcare big data management, analytics and scientific programming,” IEEE Access, vol. 8, pp. 95714–95733, 2020.
[72] V. Kilintzis, I. Chouvarda, N. Beredimas, P. Natsiavas, and N. Maglaveras, “Supporting integrated care with a flexible data management framework built upon Linked Data, HL7 FHIR and ontologies,” J. Biomed. Inform., vol. 94, p. 103179, 2019.
[73] A. Alhur, “An Exploration of Nurses’ Perceptions of the Usefulness and Easiness of Using EMRs,” J. Public Health Sci., vol. 2, no. 01, pp. 20–31, 2023.
[74] A. Alhur, “An Investigation of Nurses’ Perceptions of the Usefulness and Easiness of Using Electronic Medical Records in Saudi Arabia: A Technology Acceptance Model: Technology Acceptance Model,” Indones. J. Inf. Syst., vol. 5, no. 2, pp. 30–42, 2023.
[75] F. Prasser, O. Kohlbacher, U. Mansmann, B. Bauer, and K. Kuhn, “Data Integration for Future Medicine (DIFUTURE): An Architectural and Methodological Overview,” Methods Inf. Med., vol. 57, no. S 01, pp. e57–e65, Jul. 2018, doi: 10.3414/ME17-02-0022.
[2] M. Hassan et al., “Innovations in genomics and big data analytics for personalized medicine and health care: A review,” Int. J. Mol. Sci., vol. 23, no. 9, p. 4645, 2022.
[3] A. Alhur, “Exploring Saudi Arabia Individuals’ Attitudes toward Electronic Personal Health Records,” J. Comput. Sci. Technol. Stud., vol. 4, no. 1, pp. 80–87, 2022.
[4] K. Adnan, R. Akbar, S. W. Khor, and A. B. A. Ali, “Role and Challenges of Unstructured Big Data in Healthcare,” in Data Management, Analytics and Innovation, vol. 1042, N. Sharma, A. Chakrabarti, and V. E. Balas, Eds., in Advances in Intelligent Systems and Computing, vol. 1042. , Singapore: Springer Singapore, 2020, pp. 301–323. doi: 10.1007/978-981-32-9949-8_22.
[5] M. Adibuzzaman, P. DeLaurentis, J. Hill, and B. D. Benneyworth, “Big data in healthcare–the promises, challenges and opportunities from a research perspective: A case study with a model database,” in AMIA Annual Symposium Proceedings, American Medical Informatics Association, 2017, p. 384. Accessed: Apr. 21, 2024. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977694/
[6] A. L. Beam and I. S. Kohane, “Big data and machine learning in health care,” Jama, vol. 319, no. 13, pp. 1317–1318, 2018.
[7] P. K. D. Pramanik, S. Pal, and M. Mukhopadhyay, “Healthcare big data: A comprehensive overview,” Res. Anthol. Big Data Anal. Archit. Appl., pp. 119–147, 2022.
[8] A. A. Alhur, “The Effectiveness of E-learning in Saudi Arabia During the Spread of COVID-19,” Int. J. Adv. Res. Educ. Soc., vol. 3, no. 4, pp. 156–165, 2021.
[9] S. Dash, S. K. Shakyawar, M. Sharma, and S. Kaushik, “Big data in healthcare: management, analysis and future prospects,” J. Big Data, vol. 6, no. 1, p. 54, Dec. 2019, doi: 10.1186/s40537-019-0217-0.
[10] I. D. Dinov, “Volume and value of big healthcare data,” J. Med. Stat. Inform., vol. 4, 2016, Accessed: Apr. 21, 2024. [Online]. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795481/
[11] A. Khanan, S. Abdullah, A. H. H. M. Mohamed, A. Mehmood, and K. A. Z. Ariffin, “Big Data Security and Privacy Concerns: A Review,” in Smart Technologies and Innovation for a Sustainable Future, A. Al-Masri and K. Curran, Eds., in Advances in Science, Technology & Innovation. , Cham: Springer International Publishing, 2019, pp. 55–61. doi: 10.1007/978-3-030-01659-3_8.
[12] D. S. Terzi, R. Terzi, and S. Sagiroglu, “A survey on security and privacy issues in big data,” in 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), IEEE, 2015, pp. 202–207. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7412089/
[13] Y. Gahi, M. Guennoun, and H. T. Mouftah, “Big data analytics: Security and privacy challenges,” in 2016 IEEE Symposium on Computers and Communication (ISCC), IEEE, 2016, pp. 952–957. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7543859/
[14] E. Bertino and E. Ferrari, “Big Data Security and Privacy,” in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, vol. 31, S. Flesca, S. Greco, E. Masciari, and D. Saccà, Eds., in Studies in Big Data, vol. 31. , Cham: Springer International Publishing, 2018, pp. 425–439. doi: 10.1007/978-3-319-61893-7_25.
[15] A. Alhur, “Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot,” Cureus, vol. 16, no. 4, 2024, Accessed: Apr. 13, 2024. [Online]. Available: https://www.cureus.com/articles/243466-redefining-healthcare-with-artificial-intelligence-ai-the-contributions-of-chatgpt-gemini-and-co-pilot.pdf
[16] H. Alharthi, “Healthcare predictive analytics: An overview with a focus on Saudi Arabia,” J. Infect. Public Health, vol. 11, no. 6, pp. 749–756, 2018.
[17] B. Boukenze, H. Mousannif, and A. Haqiq, “Predictive analytics in healthcare system using data mining techniques,” Comput Sci Inf Technol, vol. 1, pp. 1–9, 2016.
[18] V. X. Liu, D. W. Bates, J. Wiens, and N. H. Shah, “The number needed to benefit: estimating the value of predictive analytics in healthcare,” J. Am. Med. Inform. Assoc., vol. 26, no. 12, pp. 1655–1659, 2019.
[19] A. Muniasamy, S. Tabassam, M. A. Hussain, H. Sultana, V. Muniasamy, and R. Bhatnagar, “Deep Learning for Predictive Analytics in Healthcare,” in The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019), vol. 921, A. E. Hassanien, A. T. Azar, T. Gaber, R. Bhatnagar, and M. F. Tolba, Eds., in Advances in Intelligent Systems and Computing, vol. 921. , Cham: Springer International Publishing, 2020, pp. 32–42. doi: 10.1007/978-3-030-14118-9_4.
[20] V.-K. Lakshmanan, S. Ojha, and Y. Do Jung, “A modern era of personalized medicine in the diagnosis, prognosis, and treatment of prostate cancer,” Comput. Biol. Med., vol. 126, p. 104020, 2020.
[21] N. Jain, U. Nagaich, M. Pandey, D. K. Chellappan, and K. Dua, “Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements,” EPMA J., vol. 13, no. 4, pp. 561–580, Nov. 2022, doi: 10.1007/s13167-022-00304-2.
[22] S. Chintala, “AI-Driven Personalised Treatment Plans: The Future of Precision Medicine,” Mach. Intell. Res., vol. 17, no. 02, pp. 9718–9728, 2023.
[23] B. Y. Kasula, “Advancements in AI-driven Healthcare: A Comprehensive Review of Diagnostics, Treatment, and Patient Care Integration,” Int. J. Mach. Learn. Sustain. Dev., vol. 1, no. 1, pp. 1–5, 2024.
[24] A. Pulumati, A. Pulumati, B. S. Dwarakanath, A. Verma, and R. V. L. Papineni, “Technological advancements in cancer diagnostics: Improvements and limitations,” Cancer Rep., vol. 6, no. 2, p. e1764, Feb. 2023, doi: 10.1002/cnr2.1764.
[25] S. Abdallah et al., “The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders,” Cureus, vol. 15, no. 10, 2023, Accessed: Apr. 21, 2024. [Online]. Available: https://www.cureus.com/articles/195184-the-impact-of-artificial-intelligence-on-optimizing-diagnosis-and-treatment-plans-for-rare-genetic-disorders.pdf
[26] E. D. Esplin, L. Oei, and M. P. Snyder, “Personalized sequencing and the future of medicine: discovery, diagnosis and defeat of disease,” Pharmacogenomics, vol. 15, no. 14, pp. 1771–1790, Nov. 2014, doi: 10.2217/pgs.14.117.
[27] S. S. Kamble and A. Gunasekaran, “Big data-driven supply chain performance measurement system: a review and framework for implementation,” Int. J. Prod. Res., vol. 58, no. 1, pp. 65–86, Jan. 2020, doi: 10.1080/00207543.2019.1630770.
[28] K. L. Keung, C. K. Lee, and P. Ji, “Data-driven order correlation pattern and storage location assignment in robotic mobile fulfillment and process automation system,” Adv. Eng. Inform., vol. 50, p. 101369, 2021.
[29] P. Ghimire, M. Zadeh, J. Thorstensen, and E. Pedersen, “Data-driven efficiency modeling and analysis of all-electric ship powertrain: A comparison of power system architectures,” IEEE Trans. Transp. Electrification, vol. 8, no. 2, pp. 1930–1943, 2021.
[30] R. K. Singh, S. Agrawal, A. Sahu, and Y. Kazancoglu, “Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda,” TQM J., vol. 35, no. 1, pp. 262–291, 2023.
[31] Y. Wang, L. Kung, and T. A. Byrd, “Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations,” Technol. Forecast. Soc. Change, vol. 126, pp. 3–13, 2018.
[32] D. W. Bates, S. Saria, L. Ohno-Machado, A. Shah, and G. Escobar, “Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients,” Health Aff. (Millwood), vol. 33, no. 7, pp. 1123–1131, Jul. 2014, doi: 10.1377/hlthaff.2014.0041.
[33] Y. Wang, L. Kung, W. Y. C. Wang, and C. G. Cegielski, “An integrated big data analytics-enabled transformation model: Application to health care,” Inf. Manage., vol. 55, no. 1, pp. 64–79, 2018.
[34] K. Pendry, “The use of big data in transfusion medicine,” Transfus. Med., vol. 25, no. 3, pp. 129–137, Jun. 2015, doi: 10.1111/tme.12223.
[35] M. I. Fernández, P. Chanfreut, I. Jurado, and J. M. Maestre, “A data-based model predictive decision support system for inventory management in hospitals,” IEEE J. Biomed. Health Inform., vol. 25, no. 6, pp. 2227–2236, 2020.
[36] L. Galli, T. Levato, F. Schoen, and L. Tigli, “Prescriptive analytics for inventory management in health care,” J. Oper. Res. Soc., vol. 72, no. 10, pp. 2211–2224, Oct. 2021, doi: 10.1080/01605682.2020.1776167.
[37] S. Guha and S. Kumar, “Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap,” Prod. Oper. Manag., vol. 27, no. 9, pp. 1724–1735, Sep. 2018, doi: 10.1111/poms.12833.
[38] M. I. Pramanik, R. Y. Lau, H. Demirkan, and M. A. K. Azad, “Smart health: Big data enabled health paradigm within smart cities,” Expert Syst. Appl., vol. 87, pp. 370–383, 2017.
[39] M. Adams, “Big data and individual privacy in the age of the internet of things,” Technol. Innov. Manag. Rev., vol. 7, no. 4, 2017, Accessed: Apr. 21, 2024. [Online]. Available: https://timreview.ca/sites/default/files/article_PDF/Adams_TIMReview_April2017.pdf
[40] H. K. Patil and R. Seshadri, “Big data security and privacy issues in healthcare,” in 2014 IEEE international congress on big data, IEEE, 2014, pp. 762–765. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/6906856/
[41] C. Schmitt, M. Shoffner, P. Owen, X. Wang, and B. Lamm, “Security and privacy in the era of big data,” SMW Technol. Solut. Chall. Data Leakage, vol. 1, no. 2, 2013, Accessed: Apr. 21, 2024. [Online]. Available: https://www.renci.org/wp-content/uploads/2014/02/0313WhitePaper-iRODS.pdf
[42] H. Tao et al., “Economic perspective analysis of protecting big data security and privacy,” Future Gener. Comput. Syst., vol. 98, pp. 660–671, 2019.
[43] N. Menachemi and T. H. Collum, “Benefits and drawbacks of electronic health record systems,” Risk Manag. Healthc. Policy, pp. 47–55, 2011.
[44] A. Mehmood, I. Natgunanathan, Y. Xiang, G. Hua, and S. Guo, “Protection of big data privacy,” IEEE Access, vol. 4, pp. 1821–1834, 2016.
[45] K. A. Salleh and L. Janczewski, “Technological, organizational and environmental security and privacy issues of big data: A literature review,” Procedia Comput. Sci., vol. 100, pp. 19–28, 2016.
[46] D. S. Terzi, R. Terzi, and S. Sagiroglu, “A survey on security and privacy issues in big data,” in 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), IEEE, 2015, pp. 202–207. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7412089/
[47] H. S. Fhom, “Big Data: Opportunities and Privacy Challenges.” arXiv, Feb. 03, 2015. Accessed: Apr. 21, 2024. [Online]. Available: http://arxiv.org/abs/1502.00823
[48] S. Varshney, D. Munjal, O. Bhattacharya, S. Saboo, and N. Aggarwal, “Big data privacy breach prevention strategies,” in 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), IEEE, 2020, pp. 1–6. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9358878/
[49] P. Sharma and S. Barua, “From data breach to data shield: the crucial role of big data analytics in modern cybersecurity strategies,” Int. J. Inf. Cybersecurity, vol. 7, no. 9, pp. 31–59, 2023.
[50] T. van den Broek and A. F. van Veenstra, “Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation,” Technol. Forecast. Soc. Change, vol. 129, pp. 330–338, 2018.
[51] T. Duchamp, “Big Data is the Cornerstone of Regulatory Compliance Systems,” in The FinTech Book, 1st ed., S. Chishti and J. Barberis, Eds., Wiley, 2016, pp. 100–105. doi: 10.1002/9781119218906.ch26.
[52] A. Gupta, A. Verma, P. Kalra, and L. Kumar, “Big Data: A security compliance model,” in 2014 Conference on IT in Business, Industry and Government (CSIBIG), IEEE, 2014, pp. 1–5. Accessed: Apr. 21, 2024. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/7056963/
[53] P. Jain, M. Gyanchandani, and N. Khare, “Big data privacy: a technological perspective and review,” J. Big Data, vol. 3, no. 1, p. 25, Dec. 2016, doi: 10.1186/s40537-016-0059-y.
[54] Z. Wan, J. W. Hazel, E. W. Clayton, Y. Vorobeychik, M. Kantarcioglu, and B. A. Malin, “Sociotechnical safeguards for genomic data privacy,” Nat. Rev. Genet., vol. 23, no. 7, pp. 429–445, 2022.
[55] U. Pagallo, “The legal challenges of big data: putting secondary rules first in the field of EU data protection,” Eur Data Prot Rev, vol. 3, p. 36, 2017.
[56] L. A. Shihab, “Technological tools for data security in the treatment of data reliability in big data environments,” Int. Trans. J. Eng. Manag. Appl. Sci. Technol., vol. 11, no. 9, pp. 1–13, 2020.
[57] R. Cumbley and P. Church, “Is ‘big data’ creepy?,” Comput. Law Secur. Rev., vol. 29, no. 5, pp. 601–609, 2013.
[58] A. Alhur et al., “ASSESSING SAUDI ARABIAN INDIVIDUALS’ATTITUDES AND PERCEPTIONS ON THE CONFIDENTIALITY AND PRIVACY OF ELECTRONIC HEALTH AND MEDICAL INFORMATION,” J. Popul. Ther. Clin. Pharmacol., vol. 30, no. 16, pp. 742–752, 2023.
[59] A. A. ALHUR, “Public Health Informatics: The Importance of Covid-19 Dashboard in KSA for Sharing and Visualizing Health Information,” J. Inf. Syst. Digit. Technol., vol. 5, no. 1, pp. 43–59, 2023.
[60] A. A. Alhur, “Public Health Informatics: The Importance of COVID-19 Dashboard in KSA: Health Information Sharing and Visualization,” J. Health Sci. Med. Dev., vol. 2, no. 02, pp. 64–79, 2023.
[61] D. B. Rawat, R. Doku, and M. Garuba, “Cybersecurity in big data era: From securing big data to data-driven security,” IEEE Trans. Serv. Comput., vol. 14, no. 6, pp. 2055–2072, 2019.
[62] A. Nassar and M. Kamal, “Machine Learning and Big Data analytics for Cybersecurity Threat Detection: A Holistic review of techniques and case studies,” J. Artif. Intell. Mach. Learn. Manag., vol. 5, no. 1, pp. 51–63, 2021.
[63] A. Alhur and A. A. Alhur, “The Acceptance of Digital Health: What about Telepsychology and Telepsychiatry?,” J. Sist. Inf., vol. 18, no. 2, pp. 18–35, 2022.
[64] M. L. Montagnani and M. A. Cavallo, “Cybersecurity and Liability in a Big Data World,” Mkt Compet. Rev, vol. 2, p. 71, 2018.
[65] J. Gao, H. Aziz, P. Maropoulos, and W. Cheung, “Application of product data management technologies for enterprise integration,” Int. J. Comput. Integr. Manuf., vol. 16, no. 7–8, pp. 491–500, Jan. 2003, doi: 10.1080/0951192031000115813.
[66] V. Bianchi et al., “Integrated systems for NGS data management and analysis: open issues and available solutions,” Front. Genet., vol. 7, p. 75, 2016.
[67] J. Chen, L. Ramanathan, and M. Alazab, “Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management of smart cities,” Microprocess. Microsyst., vol. 81, p. 103722, 2021.
[68] A. A. Alhur et al., “Telemental health and artificial intelligence: knowledge and attitudes of Saudi Arabian individuals towards ai-integrated telemental health,” J. Popul. Ther. Clin. Pharmacol., vol. 30, no. 17, pp. 1993–2009, 2023.
[69] Y. Ye, J. Shi, D. Zhu, L. Su, J. Huang, and Y. Huang, “Management of medical and health big data based on integrated learning-based health care system: a review and comparative analysis,” Comput. Methods Programs Biomed., vol. 209, p. 106293, 2021.
[70] M. Jayaratne et al., “A data integration platform for patient-centered e-healthcare and clinical decision support,” Future Gener. Comput. Syst., vol. 92, pp. 996–1008, 2019.
[71] S. Nazir et al., “A comprehensive analysis of healthcare big data management, analytics and scientific programming,” IEEE Access, vol. 8, pp. 95714–95733, 2020.
[72] V. Kilintzis, I. Chouvarda, N. Beredimas, P. Natsiavas, and N. Maglaveras, “Supporting integrated care with a flexible data management framework built upon Linked Data, HL7 FHIR and ontologies,” J. Biomed. Inform., vol. 94, p. 103179, 2019.
[73] A. Alhur, “An Exploration of Nurses’ Perceptions of the Usefulness and Easiness of Using EMRs,” J. Public Health Sci., vol. 2, no. 01, pp. 20–31, 2023.
[74] A. Alhur, “An Investigation of Nurses’ Perceptions of the Usefulness and Easiness of Using Electronic Medical Records in Saudi Arabia: A Technology Acceptance Model: Technology Acceptance Model,” Indones. J. Inf. Syst., vol. 5, no. 2, pp. 30–42, 2023.
[75] F. Prasser, O. Kohlbacher, U. Mansmann, B. Bauer, and K. Kuhn, “Data Integration for Future Medicine (DIFUTURE): An Architectural and Methodological Overview,” Methods Inf. Med., vol. 57, no. S 01, pp. e57–e65, Jul. 2018, doi: 10.3414/ME17-02-0022.
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Oct 10, 2022
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Anas Alhur, Abdulaziz Alahmari, Aeshah alshowaiman, Dalal Alrowely, Faiz Alahmari, abdulkarim alahmari, Hamed alshamrani, Mohammed Alahmari, Ahmed Alahmari, Ali alshehri, Hadeel sanyour, Hassan asiri, Ahmad Asiri, Ahmed Aljohani, & Ibtihal Alqahtani. (2022). BIG DATA IN HEALTHCARE: OPPORTUNITIES FOR IMPROVED PATIENT CARE AND SECURITY CONCERNS. Journal of Population Therapeutics and Clinical Pharmacology, 29(04), 3313-3322. https://doi.org/10.53555/jptcp.v29i04.5873
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Author Biographies
Anas Alhur
College of Public Health and Health Informatics, University of Hail, KSA
Abdulaziz Alahmari
Ministry of Health
Aeshah alshowaiman
Alshifa hospital
Dalal Alrowely
Qara Health care center
Faiz Alahmari
Ministry of Health
abdulkarim alahmari
Ministry of Health
Hamed alshamrani
Health cluster in Taif
Mohammed Alahmari
Ballahmar General Hospital
Ahmed Alahmari
Ministry of Health
Ali alshehri
Tanomah general hospital
Hadeel sanyour
Ministry of Health
Hassan asiri
Asir Central Blood Bank
Ahmad Asiri
King Khalid university
Ahmed Aljohani
Alazizyah Children Hospital
Ibtihal Alqahtani
Jazan Health Cluster
How to Cite
Anas Alhur, Abdulaziz Alahmari, Aeshah alshowaiman, Dalal Alrowely, Faiz Alahmari, abdulkarim alahmari, Hamed alshamrani, Mohammed Alahmari, Ahmed Alahmari, Ali alshehri, Hadeel sanyour, Hassan asiri, Ahmad Asiri, Ahmed Aljohani, & Ibtihal Alqahtani. (2022). BIG DATA IN HEALTHCARE: OPPORTUNITIES FOR IMPROVED PATIENT CARE AND SECURITY CONCERNS. Journal of Population Therapeutics and Clinical Pharmacology, 29(04), 3313-3322. https://doi.org/10.53555/jptcp.v29i04.5873