Opportunities and Challenges of Robotic Process Automation (RPA) in Healthcare

Corresponding author: Yao Keqin, szhealth-yao@163.com

DOI: 10.12201/bmr.202207.00036

•  

  Abstract: Healthcare are seeing significant opportunities and challenges in processing and management as the era of big data and artificial intelligence approaches. Robotic process automation (RPA) is a technology that automates tedious corporate operations, allowing employees to focus on creative thinking, intellectual judgment and decision making. RPA also offers the benefits of lowering cost and enhancing efficiency in the workplace. From the perspectives of accountants, healthcare workers, managers and patients, this article focuses on five situations in which RPA might be employed in healthcare and how it could help the industry prosper. The paper concludes with a discussion of the potential risks and prospects of future direction.

  Key words: Robotic process automation；Healthcare；Potential risks；Artificial intelligence

  Submit time: 22 July 2022

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
• html

• 图表

• dongtingting. Study on the safety impact and countermeasures of medical artificial intelligence products on patients. 2020. doi: 10.12201/bmr.202012.00004

  xiejunxiang. The composition of Key Technologies and Application in Medical Artificial Intelligence. 2020. doi: 10.12201/bmr.202005.00243

  GAO Jing-hong, LI Ming-yuan, WANG Lin, ZhAI Yun-kai, ZHAO Jie. The application and challenges of health and medical big data in the field of precision medicine. 2021. doi: 10.12201/bmr.202106.00014

  zhaorui, shixiuyuan, zhongxueran, renping, tianxueqin, liuchunping, youmao. Construction of clinical application evaluation path of medical artificial intelligence technology based on health technology evaluationRui Zhao, Xiuyuan Shi, Xueran Zhong, Chunping Liu, Ping Ren, Xueqin Tian, Mao You. 2022. doi: 10.12201/bmr.202203.00005

  Guo Min-jiang, Liu Yang, Lu Chun-ji, Jiang Xiaotong, Li Ya-zi. The process and prospect of information construction of immediate reimbursement of inter-provincial healthcare in China. 2021. doi: 10.12201/bmr.202108.00003

  yanwencheng, lijunzhen, chenmei, 卢艳红. Artificial Intelligence for Stomatology: Application in Dental Endodontics. 2021. doi: 10.12201/bmr.202102.00003

  wusijing, xubinbin, huangfeng. Development Status and Policy Suggestions of Medical Artificial Intelligence in Zhejiang Province. 2021. doi: 10.12201/bmr.202101.00015

  Li Ping, Sun Liping, Ren He, Li Huaping, Shao Zeguo. Construction of artificial intelligence thinking training course system for medical device specialty. 2020. doi: 10.12201/bmr.202007.00013

  Yufan Zhu, Xin Zhao, Zhiqiang Yang, Houcheng Zhong, Lin Cai, Yuanlong Xie. Prospect of the Training Model for Artificial Intelligence + Medicine Inter-disciplinary Talents. 2020. doi: 10.12201/bmr.202008.00010

  Gao Wenjuan, Li Jinmiao, Chen Junwei, Xin Haiyan. A Design and Implementation of the Whole Process Traceability Blood Intelligent Management Mode. 2021. doi: 10.12201/bmr.202109.00009

• ID	Submit time	Number	Download
  1	2022-03-25	bmr.202207.00036V1	Download

• Public  Anonymous  To author only Submit Comments