PATHFinder Agent for Tailored Prenatal Care

Researchers developed PATHFinder Agent, an end-to-end conversational system that gathers patient health and social context through structured dialogue, curates individualized prenatal care plans aligned with the American College of Obstetricians and Gynecologists' PATH guidelines, and surfaces community resources from Michigan 211. Evaluating frontier large language models on expert-curated rubrics across five clinical dimensions, GPT-5.2 achieved the highest average score of 77.6%, while identifying key gaps in antenatal testing recommendations.

arXiv:2607.24768v1 Announce Type: new Abstract: Prenatal care is an important preventive service designed to improve outcomes for pregnant individuals. The American College of Obstetricians and Gynecologists ACOG recently introduced guidelines advocating tailored prenatal care, called PATH Plan for Tailored Healthcare . We present PATHFinder Agent Planner for Appropriate Tailored Healthcare , an end-to-end conversational agentic system that gathers patient health and social context through structured dialogue, curates individualized prenatal care plans aligned with PATH guidelines, and surfaces community resources from Michigan 211. The system features a four-stage workflow spanning patient intake, dynamic interaction, plan synthesis, and clinician oversight. We evaluate frontier large language models LLMs on expert-curated rubrics across five clinical dimensions, finding that GPT-5.2 achieves the highest average score 77.6\% while identifying key gaps in antenatal testing recommendations. We discuss future validation through human participant studies and randomized controlled trials.