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Abstract: Objectives: The present study discusses ethics in building and using applications based on natural language processing in electronic nursing documentation. Specifically, we first focus on the question of how patient confidentiality can be ensured in developing language technology for the nursing documentation domain. Then, we identify and theoretically analyze the ethical outcomes which arise when using natural language processing to support clinical judgement and decision-making. In total, we put forward and justify 10 claims related to ethics in applying language technology to nursing documents. Methods: A review of recent scientific articles related to ethics in electronic patient records or in the utilization of large databases was conducted. Then, the results were compared with ethical guidelines for nurses and the Finnish legislation covering health care and processing of personal data. Finally, the practical experiences of the authors in applying the methods of natural language processing to nursing documents were appended. Results: Patient records supplemented with natural language processing capabilities may help nurses give better, more efficient and more individualized care for their patients. In addition, language technology may facilitate patients’ possibility to receive truthful information about their health and improve the nature of narratives. Because of these benefits, research about the use of language technology in narratives should be encouraged. In contrast, privacy-sensitive health care documentation brings specific ethical concerns and difficulties to the natural language processing of nursing documents. Therefore, when developing natural language processing tools, patient confidentiality must be ensured. While using the tools, health care personnel should always be responsible for the clinical judgement and decision-making. One should also consider that the use of language technology in nursing narratives may threaten patients’ rights by using documentation collected for other purposes. Conclusions: Applying language technology to nursing documents may, on the one hand, contribute to the quality of care, but, on the other hand, threaten patient confidentiality. As an overall conclusion, natural language processing of nursing documents holds the promise of great benefits if the potential risks are taken into consideration. [Copyright &y& Elsevier] more...

Abstract: Background: Nursing narratives are an important part of patient documentation, but the possibilities to utilize them in the direct care process are limited due to the lack of proper tools. One solution to facilitate the utilization of narrative data could be to classify them according to their content. Objectives: Our objective is to address two issues related to designing an automated classifier: domain experts’ agreement on the content of classes Breathing, Blood Circulation and Pain, as well as the ability of a machine-learning-based classifier to learn the classification patterns of the nurses. Methods: The data we used were a set of Finnish intensive care nursing narratives, and we used the regularized least-squares (RLS) algorithm for the automatic classification. The agreement of the nurses was assessed by using Cohen''s κ, and the performance of the algorithm was measured using area under ROC curve (AUC). Results: On average, the values of κ were around 0.8. The agreement was highest in the class Blood Circulation, and lowest in the class Breathing. The RLS algorithm was able to learn the classification patterns of the three nurses on an acceptable level; the values of AUC were generally around 0.85. Conclusions: Our results indicate that the free text in nursing documentation can be automatically classified and this can offer a way to develop electronic patient records. [Copyright &y& Elsevier] more...