| Autor: |
Piyawat Lertvittayakumjorn, Ivan Petej, Anna van der Gaag, Juan Caceres Silva, Yang Gao, Yamuna Krishnamurthy, Ann Gallagher, Kostas Stathis, Zubin Austin, Robert Jago, Michelle Webster |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Journal of Nursing Regulation. 12:11-19 |
| ISSN: |
2155-8256 |
| DOI: |
10.1016/s2155-8256(21)00112-5 |
| Popis: |
This project aimed to develop an artificial intelligence (AI)–based tool for improving the consistency and efficiency of decision-making in the nursing complaints process in three jurisdictions. This article describes the tool and the overall process of its development. The AI tool was not designed to replace human judgment but rather to perform three data-driven decision support tasks: (a) an independent risk prediction of the case, (b) a comparison with previous similar cases, and (c) a cross reference to relevant parts of the regulatory standards or rules in each jurisdiction. Three nursing regulatory bodies in the United States, the United Kingdom, and Australia provided anonymized data from 5,700 cases for tool design and testing. Regulatory staff were involved in each stage of development and supported the potential role of an AI-based tool such as this in improving the efficiency and effectiveness of decision-making in disciplinary processes in nursing regulation nationally and internationally.. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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