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Abstract
With the development of technology to reduce human errors in medical settings, healthcare has adopted various automation in its systems. This automation system aims to enhance efficiency, accuracy, and patient outcomes. However, the introduction of new systems can change the work environment and lead to undesired outcomes. To examine this relationship, a systematic literature review was conducted using the two keywords ‘healthcare automation’ and ‘human error at work’. The analysis begins by obtaining metadata from different sources, including Google Scholar, Scopus, Web of Science, and Dimension. Various bibliometric tools such as VOSViewer, BibExcel, MaxQDA, CiteSpace, and Google Ngram were utilized to gather insights and relationships between the two topics. These approaches help understand the general trends and climate of the two topics and fields. This comprehensive analysis not only expands our understanding of each topic individually but also highlights the link between the two topics, showcasing the complex relationship of technology, healthcare, and work settings.
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References
Ahsen, M.E., Ayvaci, M.U.S., Raghunathan, S.: When algorithmic predictions use human-generated data: a bias-aware classification algorithm for breast cancer diagnosis. Inf. Syst. Res.30(1), 97–116 (2019)
Burton, J.W., Stein, M.K., Jensen, T.B.: A systematic review of algorithm aversion in augmented decision making. J. Behav. Decis. Mak.33(2), 220–239 (2020)
Carayon, P., Wooldridge, A., Hoonakker, P., Hundt, A.S., Kelly, M.M.: SEIPS 3.0: human-centered design of the patient journey for patient safety. Appl. Ergon.84, 103033 (2020).https://doi.org/10.1016/j.apergo.2019.103033
Davenport, T., Kalakota, R.: The potential for artificial intelligence in healthcare. Future Healthc. J.6(2), 94–98 (2019).https://doi.org/10.7861/futurehosp.6-2-94
Đorđević, M., et al.: Effects of automation on sustainability of Immunohistochemistry laboratory. Healthcare9(7), 866 (2021).https://doi.org/10.3390/healthcare9070866
Fruehwirt, W., Duckworth, P.: Towards better healthcare: What could and should be automated? Technol. Forecast. Soc. Change172, 120967 (2021)
Ganiats, T.: Human error in medicine. JAMA J. Am. Med. Assoc.273(14), 1156 (1995).https://doi.org/10.1001/jama.1995.03520380092046
Gaynor, M., Wyner, G., & Gupta, A.: Dr. Watson? Balancing automation and human expertise in healthcare delivery. Leveraging applications of formal methods, verification and validation. Spec. Tech. Appl., 561–569 (2014).https://doi.org/10.1007/978-3-662-45231-8_46
Iversen, F., Gressgård, L.J., Thorogood, J.L., Balov, M.K., Hepsø, V.: Drilling automation: Potential for human error. OnePetro (2013).https://onepetro.org/DC/article/28/01/45/204773/Drilling-Automation-Potential-for-Human-Error
Karltun, A., Karltun, J., Berglund, M., Eklund, J.: HTO – a complementary ergonomics approach. Appl. Ergon.59, 182–190 (2017).https://doi.org/10.1016/j.apergo.2016.08.024
Khan, B., et al.: Drawbacks of artificial intelligence and their potential solutions in the healthcare sector. Biomed. Mater. Devices (2023).https://doi.org/10.1007/s44174-023-00063-2
Krieger, A.: Safeguarding the health of healthcare workers during future pandemics, using robotics and automation. Principal Investigator (2022).https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222716&HistoricalAwards=false
Leydesdorff, L.: Bibliometrics/citation networks. arXiv preprintarXiv:1502.06378 (2015)
Mao, X.: An evaluation of the effects of human factors and ergonomics on health care and patient safety practices: a systematic review. PLoS ONE (2015).https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0129948
Salvendy, G. (ed.): Handbook of Human Factors and Ergonomics. Wiley, Hoboken (2012)
Schmidhuber, J.: Deep learning in neural networks: an overview. Neural Netw.61, 85–117 (2015)
Singh, N., Jain, M., Kamal, M.M., Bodhi, R., Gupta, B.: Technological paradoxes and artificial intelligence implementation in healthcare. An application of paradox theory. Technol. Forecast. Soc. Change198, 122967 (2024)
Singh Rehan, H.: Medication errors are preventable. J. Pharmacovigil.s2 (2015).https://doi.org/10.4172/2329-6887.s2-005
Williams, D.J., Ratchev, S., Chandra, A., Hirani, H.: The application of assembly and automation technologies to healthcare products. CIRP Ann.55(2), 617–642 (2006)
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Purdue University, West Lafayette, IN, 47906, USA
Min Ho Cho, Yejin Seo & Vincent G. Duffy
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- Yejin Seo
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- Vincent G. Duffy
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Correspondence toYejin Seo.
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Purdue University, West Lafayette, IN, USA
Vincent G. Duffy
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Cho, M.H., Seo, Y., Duffy, V.G. (2024). Literature Review on Human-Automation Interaction: Relationship Between Healthcare Automation and Human Error at Work. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. HCII 2024. Lecture Notes in Computer Science, vol 14710. Springer, Cham. https://doi.org/10.1007/978-3-031-61063-9_2
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