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Integrated Risk Management and Artificial Intelligence in Hospital

Year 2023, Volume: 7 Issue: 1, 63 - 80, 31.12.2023
https://doi.org/10.61969/jai.1329224

Abstract

The topic revolves around the integration of Artificial Intelligence (AI) in Hospital Integrated Risk Management (IRM). AI offers significant advantages in enhancing risk identification, assessment, and mitigation across various areas of hospital operations. It can contribute to patient safety by enabling early detection of critical conditions, improving clinical risk management, and enhancing decisionmaking processes. AI also plays a vital role in information security and privacy, operational risk management, regulatory compliance, and human resources in hospitals. However, the use of AI in Hospital IRM comes with certain disadvantages and risks that need to be mitigated. These include data quality and bias, interpretability and transparency challenges, privacy and security concerns, reduced human oversight, ethical considerations, and implementation challenges. Mitigating these risks requires robust data governance, addressing bias in AI algorithms, ensuring transparency and accountability, implementing strong cybersecurity measures, and upholding ethical guidelines. To achieve successful implementation, hospitals should prioritize employee competencies, such as domain knowledge, data literacy, AI and data science skills, critical thinking, collaboration, adaptability, and ethical awareness. By developing these competencies and adhering to best practices, hospitals can optimize the use of AI in IRM, improve patient outcomes, enhance operational efficiency, and mitigate risks effectively.

References

  • Mun, J., Housel, T., Jones, R., Carlton, B., & Skots, V. (2020). Acquiring artificial intelligence systems: Development challenges, implementation risks, and cost/benefits opportunities. Naval Engineers Journal, 132(2), 79-94.
  • Rodrigues, A. R. D., Ferreira, F. A., Teixeira, F. J., & Zopounidis, C. (2022). Artificial intelligence, digital transformation and cybersecurity in the banking sector: A multi-stakeholder cognitiondriven framework. Research in International Business and Finance, 60, 101616.
  • Oboni, F., Angelino, C., & Moreno, J. (2007, May). Using artificial intelligence in an integrated risk management programme for a large alpine landslide. In Landslides and Climate Change: Challenges and Solutions: Proceedings of the International Conference on Landslides and Climate Change, Ventnor, Isle of Wight, UK, 21-24 May 2007 (p. 143). CRC Press.
  • Sun, Y., Bi, K., & Yin, S. (2020). Measuring and integrating risk management into green innovation practices for green manufacturing under the global value chain. Sustainability, 12(2), 545.
  • Johns, M. L. (1990). The CIO and IRM (information resources management) alliance: maneuvering for the competitive edge in hospital information management. Topics in Health Record Management, 11(1), 1-7.
  • Miniati, R., Frosini, F., & Dori, F. (2016). Integrated risk and quality management in hospital systems. Clinical Engineering: From Devices to Systems, 117.
  • Somayajula, U. (2021). Artificial Intelligence: An approach to Integrated Risk Management. Available at SSRN 3980768.
  • Ferdosi, M., Rezayatmand, R., & Molavi Taleghani, Y. (2020). Risk management in executive levels of healthcare organizations: insights from a scoping review (2018). Risk management and healthcare policy, 215-243.
  • European Parliamentary Research Service (2022). Artificial intelligence in healthcare:Applications, risks, and ethical and societal impacts. https://www.europarl.europa.eu/RegData/etudes/STUD/2022/729512/EPRS_STU(2022)729512_EN.pdf; (11. 7. 2023)
  • Mousavi Baigi, S. F., Sarbaz, M., Ghaddaripouri, K., Ghaddaripouri, M., Mousavi, A. S., & Kimiafar, K. (2023). Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Health Science Reports, 6(3), e1138.
  • Wilkins, D. E. (2014). Practical planning: extending the classical AI planning paradigm. Elsevier.
  • Bhbosale, S., Pujari, V., & Multani, Z. (2020). Advantages and disadvantages of artificial intellegence. Aayushi International Interdisciplinary Research Journal, 77, 227-230.
  • Sidorenko, E. L., Khisamova, Z. I., & Monastyrsky, U. E. (2021). The main ethical risks of using artificial intelligence in business. Current achievements, challenges and digital chances of knowledge based economy, 423-429.
  • Sunarti, S., Rahman, F. F., Naufal, M., Risky, M., Febriyanto, K., & Masnina, R. (2021). Artificial intelligence in healthcare: opportunities and risk for future. Gaceta Sanitaria, 35, S67-S70.
  • Argaw, S. T., Troncoso-Pastoriza, J. R., Lacey, D., Florin, M. V., Calcavecchia, F., Anderson, D., ... &Flahault, A. (2020). Cybersecurity of Hospitals: discussing the challenges and working towards mitigating the risks. BMC medical informatics and decision making, 20, 1-10.
  • McClean, K., Cross, M., & Reed, S. (2021). Risks to healthcare organizations and staff who manage obese (Bariatric) patients and use of obesity data to mitigate risks: a Literature Review. Journal of Multidisciplinary Healthcare, 577-588.
  • Intellipat (2023). Artificial Intelligence in Healthcare - AI Applications and Uses. Intellipat Blogs. https://intellipaat.com/blog/artificial-intelligence-in-healthcare/?US (10.7. 2023.)
  • Massachusetts General Hospital (2023). Massachusetts General Hospital Web Site. https://www.massgeneral.org/ (11. 6. 2023.)
  • The Johns Hopkins Hospital (2023). The Johns Hopkins Hospital Web Site. https://www.hopkinsmedicine.org/the_johns_hopkins_hospital/ (11.6.2023)
  • Moorfields Private Eye Hospital (2023). Moorfields Private Eye Hospital Web Site. https://www.moorfields-private.co.uk/ (12. 6. 2023)
  • Chang Gung Memorial Hospital (2023) Chang Gung Memorial Hospital International Medical Center Web Site. https://www.changgung.hospital/en/ (12.6. 2023)
  • SNUH (2023) Seoul National University Hospital Web Site http://www.snuh.org/global/en/main.do (14.6-2023)
  • UCSF Health (2023) University of California, San Francisco Medical Center Web Site. https://www.ucsfhealth.org/ (14.6.2023)

Integrated Risk Management and Artificial Intelligence in Hospital

Year 2023, Volume: 7 Issue: 1, 63 - 80, 31.12.2023
https://doi.org/10.61969/jai.1329224

Abstract

The topic revolves around the integration of Artificial Intelligence (AI) in Hospital Integrated Risk Management (IRM). AI offers significant advantages in enhancing risk identification, assessment, and mitigation across various areas of hospital operations. It can contribute to patient safety by enabling early detection of critical conditions, improving clinical risk management, and enhancing decisionmaking processes. AI also plays a vital role in information security and privacy, operational risk management, regulatory compliance, and human resources in hospitals. However, the use of AI in Hospital IRM comes with certain disadvantages and risks that need to be mitigated. These include data quality and bias, interpretability and transparency challenges, privacy and security concerns, reduced human oversight, ethical considerations, and implementation challenges. Mitigating these risks requires robust data governance, addressing bias in AI algorithms, ensuring transparency and accountability, implementing strong cybersecurity measures, and upholding ethical guidelines. To achieve successful implementation, hospitals should prioritize employee competencies, such as domain knowledge, data literacy, AI and data science skills, critical thinking, collaboration, adaptability, and ethical awareness. By developing these competencies and adhering to best practices, hospitals can optimize the use of AI in IRM, improve patient outcomes, enhance operational efficiency, and mitigate risks effectively.

References

  • Mun, J., Housel, T., Jones, R., Carlton, B., & Skots, V. (2020). Acquiring artificial intelligence systems: Development challenges, implementation risks, and cost/benefits opportunities. Naval Engineers Journal, 132(2), 79-94.
  • Rodrigues, A. R. D., Ferreira, F. A., Teixeira, F. J., & Zopounidis, C. (2022). Artificial intelligence, digital transformation and cybersecurity in the banking sector: A multi-stakeholder cognitiondriven framework. Research in International Business and Finance, 60, 101616.
  • Oboni, F., Angelino, C., & Moreno, J. (2007, May). Using artificial intelligence in an integrated risk management programme for a large alpine landslide. In Landslides and Climate Change: Challenges and Solutions: Proceedings of the International Conference on Landslides and Climate Change, Ventnor, Isle of Wight, UK, 21-24 May 2007 (p. 143). CRC Press.
  • Sun, Y., Bi, K., & Yin, S. (2020). Measuring and integrating risk management into green innovation practices for green manufacturing under the global value chain. Sustainability, 12(2), 545.
  • Johns, M. L. (1990). The CIO and IRM (information resources management) alliance: maneuvering for the competitive edge in hospital information management. Topics in Health Record Management, 11(1), 1-7.
  • Miniati, R., Frosini, F., & Dori, F. (2016). Integrated risk and quality management in hospital systems. Clinical Engineering: From Devices to Systems, 117.
  • Somayajula, U. (2021). Artificial Intelligence: An approach to Integrated Risk Management. Available at SSRN 3980768.
  • Ferdosi, M., Rezayatmand, R., & Molavi Taleghani, Y. (2020). Risk management in executive levels of healthcare organizations: insights from a scoping review (2018). Risk management and healthcare policy, 215-243.
  • European Parliamentary Research Service (2022). Artificial intelligence in healthcare:Applications, risks, and ethical and societal impacts. https://www.europarl.europa.eu/RegData/etudes/STUD/2022/729512/EPRS_STU(2022)729512_EN.pdf; (11. 7. 2023)
  • Mousavi Baigi, S. F., Sarbaz, M., Ghaddaripouri, K., Ghaddaripouri, M., Mousavi, A. S., & Kimiafar, K. (2023). Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Health Science Reports, 6(3), e1138.
  • Wilkins, D. E. (2014). Practical planning: extending the classical AI planning paradigm. Elsevier.
  • Bhbosale, S., Pujari, V., & Multani, Z. (2020). Advantages and disadvantages of artificial intellegence. Aayushi International Interdisciplinary Research Journal, 77, 227-230.
  • Sidorenko, E. L., Khisamova, Z. I., & Monastyrsky, U. E. (2021). The main ethical risks of using artificial intelligence in business. Current achievements, challenges and digital chances of knowledge based economy, 423-429.
  • Sunarti, S., Rahman, F. F., Naufal, M., Risky, M., Febriyanto, K., & Masnina, R. (2021). Artificial intelligence in healthcare: opportunities and risk for future. Gaceta Sanitaria, 35, S67-S70.
  • Argaw, S. T., Troncoso-Pastoriza, J. R., Lacey, D., Florin, M. V., Calcavecchia, F., Anderson, D., ... &Flahault, A. (2020). Cybersecurity of Hospitals: discussing the challenges and working towards mitigating the risks. BMC medical informatics and decision making, 20, 1-10.
  • McClean, K., Cross, M., & Reed, S. (2021). Risks to healthcare organizations and staff who manage obese (Bariatric) patients and use of obesity data to mitigate risks: a Literature Review. Journal of Multidisciplinary Healthcare, 577-588.
  • Intellipat (2023). Artificial Intelligence in Healthcare - AI Applications and Uses. Intellipat Blogs. https://intellipaat.com/blog/artificial-intelligence-in-healthcare/?US (10.7. 2023.)
  • Massachusetts General Hospital (2023). Massachusetts General Hospital Web Site. https://www.massgeneral.org/ (11. 6. 2023.)
  • The Johns Hopkins Hospital (2023). The Johns Hopkins Hospital Web Site. https://www.hopkinsmedicine.org/the_johns_hopkins_hospital/ (11.6.2023)
  • Moorfields Private Eye Hospital (2023). Moorfields Private Eye Hospital Web Site. https://www.moorfields-private.co.uk/ (12. 6. 2023)
  • Chang Gung Memorial Hospital (2023) Chang Gung Memorial Hospital International Medical Center Web Site. https://www.changgung.hospital/en/ (12.6. 2023)
  • SNUH (2023) Seoul National University Hospital Web Site http://www.snuh.org/global/en/main.do (14.6-2023)
  • UCSF Health (2023) University of California, San Francisco Medical Center Web Site. https://www.ucsfhealth.org/ (14.6.2023)
There are 23 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence (Other)
Journal Section Review Articles
Authors

Velibor Božić 0009-0005-0395-8884

Early Pub Date September 20, 2023
Publication Date December 31, 2023
Published in Issue Year 2023 Volume: 7 Issue: 1

Cite

APA Božić, V. (2023). Integrated Risk Management and Artificial Intelligence in Hospital. Journal of AI, 7(1), 63-80. https://doi.org/10.61969/jai.1329224

Journal of AI
is indexed and abstracted by
Index Copernicus, ROAD, Google Scholar, IAD

Publisher
Izmir Academy Association
www.izmirakademi.org

Although the scope of our journal is related to artificial intelligence studies, the abbreviation "AI" in the name of the journal is derived from "Academy Izmir".