RNAO’s Artificial Intelligence Innovations: A Novel Strategy to Advance Evidence-Based Nursing Practice
Abstract
Introduction. Artificial intelligence and machine learning methodologies, such as prediction, pattern recognition, or general inference based on the data used in clinical aspects, must fit within the intended purposes of developing it. This article aims to provide high-level, non-technical details of the initiative and a comprehensive approach that has been taken to integrate AI-powered techniques in evidence-based nursing practices appropriately. Methodology. A multi-pronged phased approach was considered for developing artificial intelligence tools. This approach includes conducting a scoping review, analyzing data to identify patterns of impactful intervention, employing data triangulation, enhancing data collection based on impactful intervention strategies, and developing a prototype (pilot) for an artificial intelligence tool. The process encompasses piloting, testing and training, validation, and implementation. Results. In this early stage of piloting the tool, the primary focus was identifying patterns from various information gathered from healthcare organizations. This analysis revealed opportunities for knowledge generation, facilitated the expedited implementation of guidelines, and enhanced resource efficiency. Discussion. Focusing on a data-driven model to inform best practices for implementing guidelines and identifying the most impactful interventions is facilitated by extensive in-house data storage. The triangulation of approaches to guideline development, implementation, and evaluation contributes to developing this scientifically validated artificial intelligence and machine learning initiative. Conclusion. Any artificial intelligence technique requires extensive data. To provide healthcare organizations with the best available evidence, purposeful efforts must be made to structure data collection and ensure data quality before expanding the development of artificial intelligence tools.
References
Nursing & Compassionate Care in the Age of Artificial Intelligence: Engaging the Emerging Future [Internet]. Ontario:RNAO;2020. Available from: https://rnao.ca/sites/rnao-ca/files/RNAO-AMS_Report-Nursing_and_Compassionate_Care_in_the_Age_of_AI_Final_For_Media_Release_10.21.2020.pdf
Dictionary.com [Internet] Artificial Intelligence. Definition & Meaning. Available from: https://www.dictionary.com/browse/artificial-intelligence
Robert N. How artificial intelligence is changing nursing. Nurs Manage [Internet]. 2019;50(9):30-39. doi: https://doi.org/10.1097/01.numa.0000578988.56622.21
Liao PH, Hsu PT, Chu W, Chu WC. Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan. Health Inform J [Internet]. 2015;21(2):137–48. doi: https://doi.org/10.1177/1460458213509806
Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on nursing education: Scoping review. JMIR Nursing [Internet]. 2021;4(1):e23933. doi: https://doi.org/10.2196%2F23933
Abbott MB, Shaw P. Virtual Nursing Avatars: Nurse Roles and Evolving Concepts of Care. Online J Issues Nurs [Internet]. 2016;21(3):7. doi: https://doi.org/10.3912/ojin.vol21no03ppt39,05
McGrow K. Artificial intelligence: Essentials for nursing. Nursing. [Internet]. 2019;49(9):46–9. doi: https://doi.org/10.1097/01.nurse.0000577716.57052.8d
Fritz RL, Dermody G. A nurse-driven method for developing artificial intelligence in “smart” homes for aging-in-place. Nurs Outlook [Internet]. 2019;67(2):140–53. doi: https://doi.org/10.1016/j.outlook.2018.11.004
Compassion in a technological world: Advancing AMS’s strategic aims. AMS Healthcare [Internet]. 2018. Available from: https://www.ams-inc.on.ca/resource/compassion-in-a-technological-world-advancing-ams-strategic-aims/
Zlotnik A, Alfaro MC, Pérez MCP, Gallardo-Antolín A, Martínez JMM. Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables. CIN-Comput. Inform. Nurs [Internet]. 2016;34(5):224–30. doi: https://doi.org/10.1097/cin.0000000000000230
Iqbal MJ, Javed Z, Sadia H, Qureshi IA, Irshad A, Ahmed R, et al. Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future. Cancer Cell Int Internet]. 2021;21(1):270. doi: https://doi.org/10.1186/s12935-021-01981-1
Amisha, Malik P, Pathania M, Rathaur VK. Overview of artificial intelligence in medicine. J Family Med Prim Care [Internet]. 2019;8(7):2328–31. doi: https://doi.org/10.4103%2Fjfmpc.jfmpc_440_19
Institute of Medicine (US) Committee to Advise the Public Health Service on Clinical Practice Guidelines. Clinical Practice Guidelines: Directions for a New Program [Internet]. Field MJ, Lohr KN, editors. Washington (DC): National Academies Press (US); 1990. Available from: http://www.ncbi.nlm.nih.gov/books/NBK235751/
NQF: Measuring Performance [Internet] Washintong;2023. Available from: https://www.qualityforum.org/measuring_performance/measuring_performance.aspx
Grinspun D, Bajnok I. Transforming Nursing Through Knowledge: Best Practices in Guideline Development Implementation Science and Evaluation. [Internet]. Indianapolis:Sigma Theta Tau International;2018. 562p. Available from: https://sigma.nursingrepository.org/items/6225f54f-0b19-4aaf-ad85-50b688a873f5
Grinspun D, Mazurek-Melnyk, B, Fineout-Overholt E, Naik S, Wallace K. Advancing Optimal Care With Robust Clincial Practice Guidelines. Evidence-Based Practice in Nursing & Healthcare [Internet]. Philadelphia:Lippincott Williams & Wilkins;2022. Recuperado a partir de: https://books.google.com.co/books?id=EPaBEAAAQBAJ&printsec=frontcover&hl=es#v=onepage&q&f=false
Life Out of Sequence: A Data-Driven History of Bioinformatics. by Hallam Stevens [Internet]. San Francisco: Everand;2023. Available from: https://www.everand.com/book/169810452/Life-Out-of-Sequence-A-Data-Driven-History-of-Bioinformatics
Singla S, Medeiros C, Naik S, Howitt L, Grinspun D. The Use of Artificial Intelligence Techniques in Nursing Data Systems: Scoping Review. MedUNAB [Internet]. 2023;26(3):512-521. doi: https://doi.org/10.29375/01237047.4634
Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, et al. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs [Internet]. 2021;77(9):3707–17. doi: https://doi.org/10.1111/jan.14855
Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Nursing in the age of artificial intelligence: protocol for a scoping review. JMIR Res Protoc [Internet]. 2020;9(4):e17490. doi: https://doi.org/10.2196%2F17490
von Gerich H, Moen H, Block LJ, Chu CH, DeForest H, Hobensack M, et al. Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence. Int J Nurs Stud [Internet]. 2022;127:104153. doi: https://doi.org/10.1016/j.ijnurstu.2021.104153
Naik S, Voong S, Bamford M, Smith K, Joyce A, Grinspun D. Assessment of the Nursing Quality Indicators for Reporting and Evaluation (NQuIRE) database using a data quality index. J Am Med Inform Assoc [Internet]. 2020;27(5):776–82. doi: https://doi.org/10.1093/jamia/ocaa031
Naik S, Loft M, Autea M, Medeiros C, Singla S, Kim PS, et al. A case study on the assessment of sustaining evidence-based practice changes and outcomes using the Nursing Quality Indicators for Reporting and Evaluation® (NQuIRE®) data system [version 1; peer review: awaiting peer review]. MedEdPublish [Internet]. 2024. Available from: https://mededpublish.org/articles/14-46/v1
Ahmad S, Jenkins M. Artificial Intelligence for Nursing Practice and Management: Current and Potential Research and Education. Comput Inform Nurs [Internet]. 2022;40(3):139–44. doi: https://doi.org/10.1097/cin.0000000000000871
Downloads
Copyright (c) 2024 MedUNAB
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
| Article metrics | |
|---|---|
| Abstract views | |
| Galley vies | |
| PDF Views | |
| HTML views | |
| Other views | |
