Performance, Scalability and Maintenance: An Experimental Study of RPA vs. Autonomous Agents in the Healthcare Domain
Daniel Schulz, Pedro Cabral Buchaim, Bernardo Soares, Fernando Rafael Ensslin Schwengber, Lorenzo Farias, Daniela Duarte da Silva Bagatini, Ana Paula Wernz da Cunha Müller
Abstract
Healthcare information systems are fragmented, and retrieving data from legacy web portals is a recurrent need. Robotic Process Automation (RPA) is deterministic but sensitive to interface changes, whereas autonomous agents based on large language models (Agent Process Automation, APA) promise adaptability at a higher computational cost. Following Design Science Research, we developed and compared an RPA solution (Playwright) and an APA solution (browser-use, LangGraph and Gemini 2.5 Flash-lite) to retrieve mammography and breast ultrasound reports from a laboratory portal, treating reports solely as informational artifacts. Across two rounds (T and T+7), RPA reached 98.90% accuracy and 98.27% F1-score versus 96.49% and 94.48% for APA, was about 13 times faster (16.07 s vs. 207.21 s per patient) and cost about six times less per report (USD 0.030 vs. 0.187). Both reached 100% step success rates; APA varied more over time. For a stable interface, RPA was superior.
Create a lesson
Related papers
OSGR: Observation-Support Graph Reasoning for Earth Observation Question Answering
Dazhou Yu, Zerong Wang, Riyang Bao et al.
Bidirectional Centered Score Matching for Discrete Diffusion Distillation
Peng Tu, Baoyou Chen, Haoyuan Xia et al.
Harness-S: Learning from Sibling Harnesses for Generalizable Agent Training
Kangning Zhang, Wenxiang Jiao, Bowen Fang et al.
Reliability Stress Testing of RAG Retrieval under Query-Relevant Corpus Poisoning
Janet Sung, Kainan Zhou, Gangzhen Qian et al.
Neologism Inoculation Prompting
David Demitri Africa, Cameron Holmes
AceAction-5M: Hierarchical Goals for Generalist Action Learning Across 3D Game Worlds
Kailing Li, Ruoxuan Zhang, Zheyuan Zhou et al.