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This study investigates the use of a large language model system to improve efficiency and quality in emergency department (ED) discharge letter writing.
Moore, C., Wisnivesky, J., Williams, S., Mcginn, T.: Medical errors related to discontinuity of care from an inpatient to an outpatient setting. Journal of general internal medicine 18
2003
Earlier work this paper cites.
Forster, A.J., Clark, H.D., Menard, A., Dupuis, N., Chernish, R., Chandok, N., Khan, A., Walraven, C.: Adverse events among medical patients after discharge from hospital. CMAJ 170
2004
Earlier work this paper cites.
Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D.M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., Amodei, D.: Language Models are Few-Shot Learners (2020). https://doi.org/10.48550/arXiv.2005.14165
2005
Earlier work this paper cites.
Kripalani, S., LeFevre, F., Phillips, C.O., Williams, M.V., Basaviah, P., Baker, D.W.: Deficits in communication and information transfer between hospital-based and primary care physicians. JAMA 297
2007
Earlier work this paper cites.
Schwarz, C.M., Hoffmann, M., Schwarz, P., Kamolz, L.P., Brunner, G., Sendlhofer, G.: A systematic literature review and narrative synthesis on the risks of medical discharge letters for patients’ safety. BMC health services research 19
2019
Earlier work this paper cites.
Lewis, P., Ott, M., Du, J., Stoyanov, V.: Pretrained language models for biomedical and clinical tasks: Understanding and extending the state-of-the-art. In: Proceedings of the 3rd Clinical Natural Language Processing Workshop, pp. 146–157. Association for Computational Linguistics, Online (2020). https://doi.org/10.18653/v1/2020.clinicalnlp-1.17 . https://aclanthology.org/2020.clinicalnlp-1.17
2020
Earlier work this paper cites.
Chintagunta, B., Katariya, N., Amatriain, X., Kannan, A.: Medically aware GPT-3 as a data generator for medical dialogue summarization. In: Shivade, C., Gangadharaiah, R., Gella, S., Konam, S., Yuan, S., Zhang, Y., Bhatia, P., Wallace, B. (eds.) Proceedings of the Second Workshop on Natural Language Processing for Medical Conversations, pp. 66–76. Association for Computational Linguistics, Online (2021). https://doi.org/10.18653/v1/2021.nlpmc-1.9 . https://aclanthology.org/2021.nlpmc-1.9
2021
Cited alongside, same era.
Sammani, A., Bagheri, A., Van Der Heijden, P.G.M., Riele, A.S.J.M.T., Baas, A.F., Oosters, C.A.J., Oberski, D., Asselbergs, F.W.: Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks. npj digital medicine 4
2021
Cited alongside, same era.
Emergency Medicine, T.R.C.: Discharge to General Practice. The Royal College of Emergency Medicine (2022). https://rcem.ac.uk/wp-content/uploads/2022/10/Discharge_to_General_Practice_Updated_Oct22.pdf
2022
Cited alongside, same era.
Ali, S.R., Dobbs, T.D., Hutchings, H.A., Whitaker, I.S.: Using chatgpt to write patient clinic letters. The Lancet Digital Health 5
2023
Later among the works it cites.
Tang, L., Sun, Z., Idnay, B., Nestor, J.G., Soroush, A., Elias, P.A., Xu, Z., Ding, Y., Durrett, G., Rousseau, J.F., Weng, C., Peng, Y.: Evaluating large language models on medical evidence summarization. npj digital medicine 6
2023
Later among the works it cites.
Leighis, C.: Guide to Professional Conduct And Ethics for Registered Medical Practitioners. Comhairle na nDochtúirí Leighis Medical Council (2024). https://www.medicalcouncil.ie/news-and-publications/publications/guide-to-professional-conduct-and-ethics-for-registered-medical-practitioners-2024.pdf
2024
Closest in time.
Zaretsky, J., Kim, J., Baskharoun, S., Zhao, Y., Austrian, J., Aphinyanaphongs, Y., Gupta, R., Blecker, S., Feldman, J.: Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format. JAMA network open 7
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Radford, A., Kim, J.W., Xu, T., Brockman, G., McLeavey, C., Sutskever, I.: Robust Speech Recognition via Large-Scale Weak Supervision (2022). https://doi.org/10.48550/arXiv.2212.04356
2022
Cited alongside, same era.
Emergency Medicine, R.C.: Position Statement regarding Artificial Intelligence. Royal College of Emergency Medicine (2022). https://rcem.ac.uk/wp-content/uploads/2022/12/RCEM_Position_Statement_-Artificial_Intelligence_Dec_2022.pdf
2022
Cited alongside, same era.
2024
Closest in time.
Mirza, F., Tang, O., Connolly, I., Abdulrazeq, H., Lim, R., Dean, G., Priebe, C., Chandler, C., Libby, T., Groff, M., Shin, J., Telfeian, A., Doberstein, C., Asaad, W., Gokaslan, Z., Zou, J., Ali, R.: Using chatgpt to facilitate truly informed medical consent. NEJM AI 1
2024
Closest in time.