Enhancing Clinical Communication through AI-Powered Recording and Analysis: A Multi-Center Study of Scribr AI Implementation
DOI:
https://doi.org/10.32628/CSEIT241061158Keywords:
Artificial Intelligence in Healthcare, Clinical Documentation Systems, Doctor-Patient Communication, Multilingual Healthcare Technology, Chronic Care ManagementAbstract
This article examines the implementation and effectiveness of Scribr AI, an artificial intelligence-powered system designed to enhance doctor-patient communication through automated recording, transcription, and multilingual support in clinical settings. The article evaluates the platform's impact on clinical documentation, patient comprehension, and longitudinal care management across multiple healthcare facilities. Through a comprehensive article analysis of system usage, patient engagement, and healthcare provider feedback, the article demonstrates significant improvements in communication accuracy, patient understanding, and clinical workflow efficiency. The findings indicate that AI-enabled recording and translation systems can effectively bridge language barriers, enhance patient recall of medical instructions, and support precision medicine through detailed documentation of health histories. Additionally, the study reveals notable benefits for chronic care patients through improved tracking and accessibility of historical health data. These results suggest that AI-powered communication tools can play a crucial role in modernizing healthcare delivery while addressing persistent challenges in doctor-patient communication and medical documentation. The findings have important implications for healthcare institutions seeking to improve patient engagement, reduce communication barriers, and enhance the quality of clinical documentation.
Downloads
References
S. H. Sharkiya, "Quality communication can improve patient-centred health outcomes among older patients: a rapid review," BMC Health Services Research, vol. 23, no. 1, pp. 886, Aug. 2023. https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-023-09869-8
A. Moorhead, "Communication technologies for supporting better healthcare," Research Outreach Health & Medicine, Feb. 2022. https://researchoutreach.org/articles/communication-technologies-for-supporting-better-healthcare/
Thakur, A., Ahuja, L., Vashisth, R., & Simon, R. (2023). "NLP & AI Speech Recognition: An Analytical Review." In 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 123-130). IEEE Xplore. https://ieeexplore.ieee.org/document/10112511
Biswas, A., Sabela, L.S., Sahu, P.K., & Samanta, R.K. (2022). "An Effort Towards Improving Automatic-Transcription Systems." In International Interdisciplinary Conference on Mathematics, Engineering and Science (MESIICON) (pp. 45-52). IEEE Xplore. https://ieeexplore.ieee.org/abstract/document/10093297
Imran, S., Mahmood, T., Morshed, A., & Sellis, T. (2021). "Big Data Analytics in Healthcare — A Systematic Literature Review and Roadmap for Practical Implementation." IEEE/CAA Journal of Automatica Sinica, 8(1), 1-22. https://ieee-jas.net/article/doi/10.1109/JAS.2020.1003384?pageType=en
Dantanarayana, G., & Sahama, T. (2016). "Metrics for eHealth services improvement." In 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) (pp. 1-6). IEEE Xplore. https://ieeexplore.ieee.org/document/7749425
J. Mizera-Pietraszko and P. Świątek, "Access to eHealth language-based services for multinational patients," in 2015 17th International Conference on E-Health Networking, Applications & Services (HealthCom) (pp. 1-6), 2015. https://ieeexplore.ieee.org/document/7454504
Karimian, G., Petelos, E., & Evers, S. M. A. A. (2022). "The ethical issues of the application of artificial intelligence in healthcare: a systematic scoping review." AI and Ethics, 2(3), 539-551. https://link.springer.com/article/10.1007/s43681-021-00131-7
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Scientific Research in Computer Science, Engineering and Information Technology

This work is licensed under a Creative Commons Attribution 4.0 International License.