Synthea
| Developer(s) | MITRE Corp. |
|---|---|
| Initial release | 8 December 2016 |
| Stable release | 1.2.0
/ 8 December 2016 |
| Repository | github |
| Engine | |
| Type | Developer Tool |
| License | Apache |
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Synthea is an open-source data generator platform for electronic clinical data. Developed by researchers at the non-profit MITRE Corp and the HIKER Group, which includes members from universities around the world, Synthea generates "realistic but not real"[1] data that can be used by software developers or researchers in healthcare.
History[edit]
In many countries, health data in electronic form is subject to legal privacy and security regulations. According to the Synthea project leaders, "The use of real patient records, even those that have been anonymized, comes with issues of privacy, confidentiality, and consent. For instance, there is an especially high risk of harm from public disclosure and identification of individuals resulting from the release or use of anonymized health records, and multiple examples of re-identification of these records have already been observed and publicized."[2]
Synthea was developed to generate completely synthetic data while still adhering to basic understandings of medicine and accompanying clinical care guidelines. The framework for the system is based on a model called PADARSER, the Publicly Available Data Approach.[2] which calls for the generation of synthetic patient data in four stages:
- Use publicly available health statistics.
- Assume that access to real electronic health records systems is impossible.
- Makes use of care maps which incorporate known treatment guidelines for conditions.
- Employ methods to ensure records are sufficient for secondary uses that require realistic but not real data.[2]
Architecture [edit]
To initiate its population, Synthea uses seed data from census demographics, CDC prevalence and incidence rates and National Health Institute reports. These demographics are then stored by Synthea and used to help shape the generated population.
To model diseases, Synthea has encoded specific "Clinical Diseases Modules". These modules act as state machines which direct the system to generate synthetic interactions with doctors, admissions to hospitals, and test results based on the disease state.[3]
For instance, the disease map for ear infection will automatically process the following:
- An "ear infection" disease case for 2% of children under 3 and 1% of children under 6. A patient randomly selected for this disease would then receive:
- A visit, referred to as an encounter, with a healthcare provider who encodes a diagnosis for ear infection.
- Prescriptions for a painkiller and an antibiotic medication.
A software developer or researcher can and utilize access the generated data in multiple forms including C-CDA or FHIR, which are the leading data standards in healthcare applications.[4]
As of release v1.0.3, Synthea has modules for the following:
Appendicitis, Asthma, Attention Deficit Disorder, Bronchitis, Colorectal Cancer, COPD, Dementia, Fibromyalgia, Food Allergies, Gout, Accidental Injury, Lung Cancer, Lupus, Metabolic Syndrome, Preventative Standards of Care, Opioid Addiction, Osteoarthritis, Pregnancy, Arthritis, Self Harm, SInusitis, Sore Throat, Joint Replacement, Urinary Tract Infections.
Usage[edit]
Synthea is in active use by a number of academic institutions and health technology vendors.[5]
SyntheticMass is website and server that provides analytics on a realistic simulation of the Massachusetts Healthcare system for the year 2021. The underlying data was generated through Synthea monitoring.
References[edit]
- ↑ HealthITAnalytics. "Open Source EHR Generator Delivers Healthcare Big Data with FHIR". HealthITAnalytics. Retrieved 2017-11-03.
- ↑ 2.0 2.1 2.2 Walonoski, Jason; Kramer, Mark; Nichols, Joseph; Quina, Andre; Moesel, Chris; Hall, Dylan; Duffett, Carlton; Dube, Kudakwashe; Gallagher, Thomas. "Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic healthcare record". Journal of the American Medical Informatics Association. doi:10.1093/jamia/ocx079.
- ↑ synthea: Synthetic Patient Population Simulator, synthetichealth, 2017-10-25, retrieved 2017-11-03
- ↑ "Interoperability, that oft-promised, long sought-after state of data fluidity, has yet to fully arrive in patient records". Retrieved 2017-11-06.
- ↑ HealthITAnalytics. "Open Source EHR Generator Delivers Healthcare Big Data with FHIR". HealthITAnalytics. Retrieved 2017-11-06.
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