Artificial Intelligence (AI) dalam Pelayanan Keperawatan: Studi Literatur

Authors

  • Moh Heri Kurniawan Universitas Aisyah Pringsewu
  • Hanny Handiyani Universitas Indonesia
  • Tuti Nuraini Universitas Indonesia
  • Rr Tutik Sri Hariyati Universitas Indonesia

DOI:

https://doi.org/10.33746/fhj.v10i01.556

Keywords:

artificial intelligence, pelayanan keperawatan, studi literatur, machine learning

Abstract

Penelitian tentang artificial intelligence (AI) dalam layanan kesehatan telah meningkat dalam beberapa dekade terakhir. Hal ini menunjukkan potensi besar dalam meningkatkan kualitas perawatan. Namun, penerapan AI dalam keperawatan menimbulkan kekhawatiran terkait bias data dan dampak potensial bagi pasien. Selain itu penelitian terkait AI dan manfaatnya dalam keperawatan masih terbatas. Tujuan penelitian  ini untuk menjabarkan hasil penelitian terkait teknologi AI dalam pelayanan keperawatan. Metode penelitian yang digunakan ialah literature review. Pencarian terhadap studi-studi yang relevan dilakukan di beberapa database yaitu PUBMED, Scopus dan Google Scholar dengan kata kunci serta istilah yang terkait dengan keperawatan, artificial intelligence, dan machine learning dalam rentang tahun 2012-2022. Kriteria inklusi meliputi penelitian pengembangan atau validasi teknologi berbasis AI yang digunakan dalam layanan keperawatan dan desain studi, termasuk eksperimental atau observasional dengan menggunakan pendekatan kualitatif, kuantitatif, atau gabungan keduanya. Sedangkan kriteria ekslusi yaitu artikel yang tidak relevan dengan keperawatan, non-eksperimental, non-observasional, atau artikel tinjauan literatur. Hasil penelitian menunjukkan dari total 3713 paper yang ditemukan hanya 10 paper yang masuk dalam kriteria. Penggunaan AI dalam pelayanan keperawatan dapat memberikan banyak manfaat tetapi juga memerlukan pertimbangan yang matang. Oleh karena itu, lebih banyak penelitian diperlukan untuk mengatasi tantangan yang dihadapi dan untuk memaksimalkan potensi AI dalam meningkatkan kualitas pelayanan keperawatan.

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References

AI HLEG: High-Level Expert Group on Artificial intelligence. (2019). A Definition of AI: Main Cababilities and Disciplines. European Commission.

Ala-Kitula, A., Talvitie-Lamberg, K., Tyrvainen, P., & Silvennoinen, M. (2017). Developing Solutions for Healthcare — Deploying Artificial Intelligence to an Evolving Target. 2017 International Conference on Computational Science and Computational Intelligence (CSCI), 1637–1642. https://doi.org/10.1109/CSCI.2017.285

Al-Shaqi, R., Mourshed, M., & Rezgui, Y. (2016). Progress in ambient assisted systems for independent living by the elderly. SpringerPlus, 5(1), 624. https://doi.org/10.1186/s40064-016-2272-8

Amato, F., Bianchi, S., Comai, S., Crovari, P., Pasquarelli, M. G. G., Imtiaz, A., Masciadri, A., Toldo, M., & Yuyar, E. (2018). CLONE. Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good - Goodtechs ’18, 255–260. https://doi.org/10.1145/3284869.3284906

Ambagtsheer, R. C., Shafiabady, N., Dent, E., Seiboth, C., & Beilby, J. (2020). The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set. International Journal of Medical Informatics, 136, 104094. https://doi.org/10.1016/j.ijmedinf.2020.104094

ANA Center for Ethics and Human Rights. (2022). The Ethical Use of Artificial Intelligence in Nursing Practice.

Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2020). Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review. JMIR Nursing, 3(1), e23939. https://doi.org/10.2196/23939

Cho, I., Park, I., Kim, E., Lee, E., & Bates, D. W. (2013). Using EHR data to predict hospital-acquired pressure ulcers: A prospective study of a Bayesian Network model. International Journal of Medical Informatics, 82(11), 1059–1067. https://doi.org/10.1016/j.ijmedinf.2013.06.012

Evans, R. S., Kuttler, K. G., Simpson, K. J., Howe, S., Crossno, P. F., Johnson, K. v, Schreiner, M. N., Lloyd, J. F., Tettelbach, W. H., Keddington, R. K., Tanner, A., Wilde, C., & Clemmer, T. P. (2015). Automated detection of physiologic deterioration in hospitalized patients. Journal of the American Medical Informatics Association, 22(2), 350–360. https://doi.org/10.1136/amiajnl-2014-002816

Karimian, G., Petelos, E., & Evers, S. M. A. A. (2022). The ethical issues of the application of artificial intelligence in healthcare: a systematic scoping review. AI and Ethics, 2(4), 539–551. https://doi.org/10.1007/s43681-021-00131-7

Kluge, E.-H. W. (2020). Artificial intelligence in healthcare: Ethical considerations. Healthcare Management Forum, 33(1), 47–49. https://doi.org/10.1177/0840470419850438

Krishnan, R. H., & Pugazhenthi, S. (2014). Mobility assistive devices and self-transfer robotic systems for elderly, a review. Intelligent Service Robotics, 7(1), 37–49. https://doi.org/10.1007/s11370-013-0142-6

Lee, D., & Yoon, S. N. (2021). Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. International Journal of Environmental Research and Public Health, 18(1), 271. https://doi.org/10.3390/ijerph18010271

Matheny, M. E., Whicher, D., & Thadaney Israni, S. (2020). Artificial Intelligence in Health Care. JAMA, 323(6), 509. https://doi.org/10.1001/jama.2019.21579

McCarthy, M. K. (2019). Artificial Intelligence in Health: Ethical Considerations for Research and Practice. HIMSS.

McGrow, K. (2019). Artificial intelligence: Essentials for nursing. Nursing, 49(9), 46–49. https://doi.org/10.1097/01.NURSE.0000577716.57052.8d

Parthasarathy, R., Steinbach, T., Knight, J., & Knight, L. (2018). Framework to Enhance Nurses’ Use of EMR. Hospital Topics, 96(3), 85–93. https://doi.org/10.1080/00185868.2018.1488545

Rigby, M. J. (2019). Ethical Dimensions of Using Artificial Intelligence in Health Care. AMA Journal of Ethics.

Robert, N. (2019). How artificial intelligence is changing nursing. Nursing Management, 50(9), 30–39. https://doi.org/10.1097/01.NUMA.0000578988.56622.21

Seibert, K., Domhoff, D., Bruch, D., Schulte-Althoff, M., Fürstenau, D., Biessmann, F., & Wolf-Ostermann, K. (2021). Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review. Journal of Medical Internet Research, 23(11), e26522. https://doi.org/10.2196/26522

Stokes, F., & Palmer, A. (2020). Artificial Intelligence and Robotics in Nursing: Ethics of Caring as a Guide to Dividing Tasks Between AI and Humans. Nursing Philosophy, 21(4). https://doi.org/10.1111/nup.12306

Tang, V., Siu, P. K. Y., Choy, K. L., Lam, H. Y., Ho, G. T. S., Lee, C. K. M., & Tsang, Y. P. (2019). An adaptive clinical decision support system for serving the elderly with chronic diseases in healthcare industry. Expert Systems, 36(2), e12369. https://doi.org/10.1111/exsy.12369

Tran, B., Vu, G., Ha, G., Vuong, Q.-H., Ho, M.-T., Vuong, T.-T., La, V.-P., Ho, M.-T., Nghiem, K.-C., Nguyen, H., Latkin, C., Tam, W., Cheung, N.-M., Nguyen, H.-K., Ho, C., & Ho, R. (2019). Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study. Journal of Clinical Medicine, 8(3), 360. https://doi.org/10.3390/jcm8030360

von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., Michalowski, M., Mitchell, J., Nibber, R., Olalia, M. A., Pruinelli, L., Ronquillo, C. E., Topaz, M., & Peltonen, L.-M. (2022). Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153. https://doi.org/10.1016/j.ijnurstu.2021.104153

Wahl, B., Cossy-Gantner, A., Germann, S., & Schwalbe, N. R. (2018). Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Global Health, 3(4), e000798. https://doi.org/10.1136/bmjgh-2018-000798

Xiong, G. L., Bayen, E., Nickels, S., Subramaniam, R., Agrawal, P., Jacquemot, J., Bayen, A. M., Miller, B., & Netscher, G. (2019). Real-time video detection of falls in dementia care facility and reduced emergency care. The American Journal of Managed Care, 25(7), 314–315.

Yamamoto, K., Yoshii, M., Kinoshita, F., & Touyama, H. (2020). Classification vs Regression by CNN for Handwashing Skills Evaluations in Nursing Education. 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 590–593. https://doi.org/10.1109/ICAIIC48513.2020.9064974

Ye, C., Li, J., Hao, S., Liu, M., Jin, H., Zheng, L., Xia, M., Jin, B., Zhu, C., Alfreds, S. T., Stearns, F., Kanov, L., Sylvester, K. G., Widen, E., McElhinney, D., & Ling, X. B. (2020). Identification of elders at higher risk for fall with statewide electronic health records and a machine learning algorithm. International Journal of Medical Informatics, 137, 104105. https://doi.org/10.1016/j.ijmedinf.2020.104105

Zampieri, F. G., Salluh, J. I. F., Azevedo, L. C. P., Kahn, J. M., Damiani, L. P., Borges, L. P., Viana, W. N., Costa, R., Corrêa, T. D., Araya, D. E. S., Maia, M. O., Ferez, M. A., Carvalho, A. G. R., Knibel, M. F., Melo, U. O., Santino, M. S., Lisboa, T., Caser, E. B., Besen, B. A. M. P., … Soares, M. (2019). ICU staffing feature phenotypes and their relationship with patients’ outcomes: an unsupervised machine learning analysis. Intensive Care Medicine, 45(11), 1599–1607. https://doi.org/10.1007/s00134-019-05790-z

Zhou, Y., Li, Z., & Li, Y. (2021). Interdisciplinary collaboration between nursing and engineering in health care: A scoping review. International Journal of Nursing Studies, 117, 103900. https://doi.org/10.1016/j.ijnurstu.2021.103900

Published

2023-04-11

How to Cite

Kurniawan, M. H., Handiyani, H., Nuraini, T., & Hariyati, R. T. S. (2023). Artificial Intelligence (AI) dalam Pelayanan Keperawatan: Studi Literatur. Faletehan Health Journal, 10(01), 77–84. https://doi.org/10.33746/fhj.v10i01.556