# PatientSim: A Persona-Driven Simulator for Realistic Doctor-Patient Interactions

arXiv: https://arxiv.org/abs/2505.17818 · HTML: https://mlsanity.com/paper/2505.17818/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 71 references that are in the map.
- First posted on arXiv 23 May 2025.

## Builds on (most cited first, 23 of 23)

- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams](https://mlsanity.com/paper/2009.13081/) (2020)
- [PubMedQA: A Dataset for Biomedical Research Question Answering](https://mlsanity.com/paper/1909.06146/) (2019)
- [Prometheus: Inducing Fine-grained Evaluation Capability in Language Models](https://mlsanity.com/paper/2310.08491/) (2023)
- [MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering](https://mlsanity.com/paper/2203.14371/) (2022)
- [Toxicity in ChatGPT: Analyzing Persona-assigned Language Models](https://mlsanity.com/paper/2304.05335/) (2023)
- [MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://mlsanity.com/paper/2311.10537/) (2023)
- [AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments](https://mlsanity.com/paper/2405.07960/) (2024)
- [Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents](https://mlsanity.com/paper/2405.02957/) (2024)
- [MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making](https://mlsanity.com/paper/2404.15155/) (2024)
- [MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://mlsanity.com/paper/2406.00922/) (2024)
- [AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator](https://mlsanity.com/paper/2402.09742/) (2024)
- [PersonaGym: Evaluating Persona Agents and LLMs](https://mlsanity.com/paper/2407.18416/) (2024)
- [Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles](https://mlsanity.com/paper/2407.00870/) (2024)
- [Self-Evolving Multi-Agent Simulations for Realistic Clinical Interactions](https://mlsanity.com/paper/2503.22678/) (2025)
- [Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulator](https://mlsanity.com/paper/2403.08495/) (2024)
- [MEDCO: Medical Education Copilots Based on A Multi-Agent Framework](https://mlsanity.com/paper/2408.12496/) (2024)
- [Towards a Client-Centered Assessment of LLM Therapists by Client Simulation](https://mlsanity.com/paper/2406.12266/) (2024)
- [LLMs Can Simulate Standardized Patients via Agent Coevolution](https://mlsanity.com/paper/2412.11716/) (2024)
- [Leveraging Large Language Model as Simulated Patients for Clinical Education](https://mlsanity.com/paper/2404.13066/) (2024)
- [An Automatic Evaluation Framework for Multi-turn Medical Consultations Capabilities of Large Language Models](https://mlsanity.com/paper/2309.02077/) (2023)
- [PIORS: Personalized Intelligent Outpatient Reception based on Large Language Model with Multi-Agents Medical Scenario Simulation](https://mlsanity.com/paper/2411.13902/) (2024)
- [Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm](https://mlsanity.com/paper/2408.08693/) (2024)

## Built on by (most cited first, 30 of 32)

- [EHRWorld: A Patient-Centric Medical World Model for Long-Horizon Clinical Trajectories](https://mlsanity.com/paper/2602.03569/) (2026)
- [Simulated Students in Tutoring Dialogues: Substance or Illusion?](https://mlsanity.com/paper/2601.04025/) (2026)
- [OdysSim: Building Foundation Models for Human Behavior Simulation](https://mlsanity.com/paper/2606.14199/) (2026)
- [The Dialogue That Heals: A Comprehensive Evaluation of Doctor Agents' Inquiry Capability](https://mlsanity.com/paper/2509.24958/) (2025)
- [KnowGuard: Knowledge-Driven Abstention for Multi-Round Clinical Reasoning](https://mlsanity.com/paper/2509.24816/) (2025)
- [Guideline-Grounded Evidence Accumulation for High-Stakes Agent Verification](https://mlsanity.com/paper/2603.02798/) (2026)
- [The Persona Paradox: Medical Personas as Behavioral Priors in Clinical Language Models](https://mlsanity.com/paper/2601.05376/) (2026)
- [PICon: A Multi-Turn Interrogation Framework for Evaluating Persona Agent Consistency](https://mlsanity.com/paper/2603.25620/) (2026)
- [TriageSim: A Conversational Emergency Triage Simulation Framework from Structured Electronic Health Records](https://mlsanity.com/paper/2603.10035/) (2026)
- [MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability](https://mlsanity.com/paper/2604.08788/) (2026)
- [The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy](https://mlsanity.com/paper/2607.11175/) (2026)
- [Multi-Stage Patient Role-Playing Framework for Realistic Clinical Interactions](https://mlsanity.com/paper/2601.10951/) (2026)
- [LegalWorld: A Life-Cycle Interactive Environment for Legal Agents](https://mlsanity.com/paper/2606.18728/) (2026)
- [When Avatars Have Personality: Effects on Engagement and Communication in Immersive Medical Training](https://mlsanity.com/paper/2509.14132/) (2025)
- [Think Like a Doctor: Conversational Diagnosis through the Exploration of Diagnostic Knowledge Graphs](https://mlsanity.com/paper/2602.01995/) (2026)
- [H-AdminSim: A Multi-Agent Simulator for Realistic Hospital Administrative Workflows with FHIR Integration](https://mlsanity.com/paper/2602.05407/) (2026)
- [VeriSim: A Configurable Framework for Stress-Testing Medical AI Under Patient Communication Noise](https://mlsanity.com/paper/2604.10441/) (2026)
- [STREAM: A Data-Centric Framework for Mining High-Value Task-Oriented Dialogues from Streaming Media](https://mlsanity.com/paper/2605.25162/) (2026)
- [Persona Non Grata: LLM Persona-Driven Generations in MCQA are Unstable in Distinct Dimensions](https://mlsanity.com/paper/2607.00937/) (2026)
- [The complexities of patient-centred conversational artificial intelligence](https://mlsanity.com/paper/2607.08625/) (2026)
- [Evaluating the Effectiveness of Persona Simulation in Opinion Prediction with GPT-4.1](https://mlsanity.com/paper/2607.20589/) (2026)
- [Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies](https://mlsanity.com/paper/2608.05993/) (2026)
- [EmoPatient: An Emotion-Directed Patient Simulator for Realistic Palliative Care Communication Training](https://mlsanity.com/paper/2608.07495/) (2026)
- [ELICITED: EHR-grounded Longitudinal Interactive Conversations for Information-seeking Triage Evaluation and Decision-making](https://mlsanity.com/paper/2608.09024/) (2026)
- [When Patients Cut In: Extending Clinical Conversational AI Safety to Interruptions](https://mlsanity.com/paper/2608.29241/) (2026)
- [SIC-Agents: Benchmarking and Building an Adaptive Simulator for Pediatric Serious Illness Communication Training](https://mlsanity.com/paper/2608.29481/) (2026)
- [GPAgentBench-2K: Benchmarking Large Language Model Agents in Complex Clinical Action Space](https://mlsanity.com/paper/2608.30188/) (2026)
- [When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors](https://mlsanity.com/paper/2609.09887/) (2026)
- [DischargeBench: Pre-Deployment Evaluation of LLM Discharge Educators through Persona-Grounded Patient Simulation](https://mlsanity.com/paper/2609.20827/) (2026)
- [Clinician-Grounded Quality Assurance for AI-Assisted Psychiatric Intake](https://mlsanity.com/paper/2609.21149/) (2026)

## Abstract (arXiv)

Doctor-patient consultations require multi-turn, context-aware communication tailored to diverse patient personas. Training or evaluating doctor LLMs in such settings requires realistic patient interaction systems. However, existing simulators often fail to reflect the full range of personas seen in clinical practice. To address this, we introduce PatientSim, a patient simulator that generates realistic and diverse patient personas for clinical scenarios, grounded in medical expertise. PatientSim operates using: 1) clinical profiles, including symptoms and medical history, derived from real-world data in the MIMIC-ED and MIMIC-IV datasets, and 2) personas defined by four axes: personality, language proficiency, medical history recall level, and cognitive confusion level, resulting in 37 unique combinations. We evaluate eight LLMs for factual accuracy and persona consistency. The top-performing open-source model, Llama 3.3 70B, is validated by four clinicians to confirm the robustness of our framework. As an open-source, customizable platform, PatientSim provides a reproducible and scalable solution that can be customized for specific training needs. Offering a privacy-compliant environment, it serves as a robust testbed for evaluating medical dialogue systems across diverse patient presentations and shows promise as an educational tool for healthcare. The code is available at https://github.com/dek924/PatientSim.