ArticleJournal of the American Medical Informatics Association : JAMIA2018
Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record.
Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 132 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
132 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Synthetic data generation methods for longitudinal and time series health data: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review.BMC medical informatics and decision making · 2023Pooled it
- A Patient Simulation Framework for Risk Assessment of Conversational Health Care AI: Development and Evaluation Study.JMIR AI · 2026Article
- Standardizing Disaster Health Data Visualization Using Fast Healthcare Interoperability Resources in Indonesia: Dashboard Development and Technical Evaluation.JMIR medical informatics · 2026Article
- Validating methods for inferring co-occurring diseases: a flexible framework for simulating synthetic data.BMC medical research methodology · 2026Article
- Eleven quick tips for Biomedical Federated Learning.PLoS computational biology · 2026Article
- Benchmarking Fast Healthcare Interoperability Resources-Based Analytics: Quantitative Study of RESTful Server Queries and Big Data Engines.JMIR medical informatics · 2026Article
- A generative approach for semantic auditing of electronic health records.NPJ digital medicine · 2026Article
- Selecting synthetic data for successful simulation-based transfer learning in dynamical biological systems.BMC bioinformatics · 2026Article
- Artificial intelligence-generated synthetic data for cancer research and clinical trials.Nature reviews. Cancer · 2026Review
- Methods for Generating and Evaluating Synthetic Longitudinal Patient Data: A Systematic Review.Journal of healthcare informatics research · 2026Review
- SynthCraft: An AI partner for synthetic data generation to support data access and augmentation in healthcare.PLOS digital health · 2026Article
- Deep generative hidden Markov models for synthetic patient data generation: a novel approach for medical AI research.BMC medical informatics and decision making · 2026Article
- Leveraging generative AI to enhance Synthea model development.JAMIA open · 2026Article
- EvoMDT: a self-evolving multi-agent system for structured clinical decision-making in multi-cancer.NPJ digital medicine · 2026Article
- K-anonymity decay in multi-turn clinical large language model conversations.Frontiers in digital health · 2026Article
- AI-driven quality enhancement of medical datasets: a closed-loop framework of synthesis, annotation, quality control, and integration.Frontiers in medicine · 2026Review
- From Concept to Implementation: A Policy and Standards Roadmap for a Global Medical Record System for Travelers with Chronic Disease.Clinical epidemiology · 2026Article
- Comparative performance of four large language models in generating evidence-based exercise prescriptions using FITT-VP framework.Frontiers in physiology · 2026Article
- Crossing borders securely: synthetic data and federated networks for privacy-preserving access to real-world data and emerging use cases.NPJ digital medicine · 2025Review
72 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveOur objective is to create a source of synthetic electronic health records that is readily available; suited to industrial, innovation, research, and educational uses; and free of legal, privacy, security, and intellectual property restrictions. MATERIALS AND
methodsWe developed Synthea, an open-source software package that simulates the lifespans of synthetic patients, modeling the 10 most frequent reasons for primary care encounters and the 10 chronic conditions with the highest morbidity in the United States.
resultsSynthea adheres to a previously developed conceptual framework, scales via open-source deployment on the Internet, and may be extended with additional disease and treatment modules developed by its user community. One million synthetic patient records are now freely available online, encoded in standard formats (eg, Health Level-7 [HL7] Fast Healthcare Interoperability Resources [FHIR] and Consolidated-Clinical Document Architecture), and accessible through an HL7 FHIR application program interface. DISCUSSION: Health care lags other industries in information technology, data exchange, and interoperability. The lack of freely distributable health records has long hindered innovation in health care. Approaches and tools are available to inexpensively generate synthetic health records at scale without accidental disclosure risk, lowering current barriers to entry for promising early-stage developments. By engaging a growing community of users, the synthetic data generated will become increasingly comprehensive, detailed, and realistic over time.
conclusionSynthetic patients can be simulated with models of disease progression and corresponding standards of care to produce risk-free realistic synthetic health care records at scale.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.