Using a statistic population health model generator, this data set is made up of highly realistic, but synthetic patient data that can be used for testing purposes without risk of disclosing PHI (protected health information).
This dataset is for single organization use only. Please contact us for more information on synthetic datasets for multi-partner use, FHIR server options available for testing, or hand curated datasets to meet your needs.
This data pack is a synthetic healthcare dataset comprised of 1000 patients with 3 years of longitudinal history.
Using a Monte Carlo simulation technique, each synthetic record is modeled to emulate clinically relevant treatment scenarios. During the generation synthetic patients progress through a series of healthcare encounters. It is these encounters and their events that are used to generate the dataset which is comprised of healthcare data messages across several HL7 messaging standards.
These records are highly realistic and even include gaps of information like a patient record in a real-world healthcare ecosystem.
Common conditions that may be contained in the data pack:
• Appendicitis
• Cancer
• Covid
• Deep venous thrombosis
• Diabetes
• Food Insecurity (SDOH)
• Hypertension
• Osteoporosis
• Pregnancy
• Pulmonary embolism
• STIs
• Zika
HL7 Message standards output that may be included for a synthetic patient record:
ADT
Admission, Discharge, Transfer (ADT) messages are used to communicate patient demographics, visit information and patient state at a healthcare facility.
This synthetic data set contains the following number of synthetic Admit, Discharge and Transfer (ADT) messages in HL7 messaging standard version 2.6 with the following event types:
• A01 - Admit / visit notification
• A03 - Discharge/end visit
• A04 - Register a patient
Message count in data set: 2,416 total A01
2 total A02
2,416 total A03
21,661 total A04
VXU
Unsolicited Vaccination Update (VXU) messages are used to receive and send patient’s vaccination information.
This synthetic data set contains synthetic Unsolicited Vaccination Record (VXU) messages in HL7 messaging standard version 2.5.1 with an event type of V04.
Message count in data set: 9,197
ORU
ORUs are unsolicited transmission of an observation message designed contain information about a patient's clinical observations and are used for transmitting patient’s laboratory results to other systems.
This synthetic data set contains synthetic Observation Result (ORU) messages in HL7 messaging standard version 2.5.1 with an event type of R01.
Message count in data set: 1,113
CCD
Continuity of Care Documents (CCD) are XML based markup standard built using HL7 Clinical Document Architecture (CDA) elements. CCD’s carry summary information about the patient within the broader context of the personal health record.
Current data fields in CCD’s:
• Patient demographics
• Medications
• Allergies
• Encounters
• Problem lists
• Diagnosis
• Lab results
• Immunization
• Social History
Message count in data set: 24,077
FHIR
Fast Healthcare Interoperability Resources (FHIR) is a modern standard for exchanging healthcare information electronically. FHIR leverages web standards like HTTP, RESTful APIs, and JSON to enable seamless communication between different healthcare systems, applications, and devices.
FHIR facilitates interoperability by providing a framework for representing and exchanging clinical data in a structured, standardized format, allowing healthcare stakeholders to easily access and share patient information across disparate systems, leading to improved care coordination, streamlined workflows, and enhanced patient outcomes.
The synthetic patient records generated by our statistic population health model generator are output in JSON FHIR version R4 resources.
Message count in data set: 11,692 bundles containing an average of 100 FHIR resources in each bundle (~1,169,200 total FHIR resources)
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This listing uses a single pricing dimension called Product Access, billed by units under a contract. You buy access to one fixed synthetic data pack: 1,000 patients with three years of longitudinal records. There are no tiers, instance sizes, or usage add-ons to compare. Pricing scales only by the number of access units you purchase. Each unit grants access to the same defined dataset, so you choose quantity based on how many teams or copies you need.
Top-of-mind questions for buyers
What exactly does one Product Access unit include in this data pack?
One unit grants access to a fixed synthetic dataset: 1,000 patients with three years of longitudinal records. Each record models clinically relevant treatment scenarios generated through Monte Carlo simulation. The data spans several HL7 messaging standards, including ADT, ORU, VXU, CCD, and FHIR. The dataset is fully synthetic with no real patient information.
What happens to my cost if I need to add more teams or copies of the dataset?
Cost scales only by the number of Product Access units you buy. Each added unit grants access to the same defined dataset. There are no usage overages or tier boundaries to cross. You choose quantity upfront based on how many teams or copies you need, and cost rises in step with unit count.
What conditions and use cases does the dataset support for testing?
The dataset models common conditions such as appendicitis, deep venous thrombosis, food insecurity, hypertension, osteoporosis, and pulmonary embolism. It supports interoperability testing, patient data exchange, risk assessment, social determinants of health, and end-to-end solution testing. The synthetic records also work for training and testing software applications and machine learning models.
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Using a statistic population health model generator, this data set is made up of highly realistic, but synthetic patient data that can be used for testing purposes without risk of disclosing PHI (protected health information).
This dataset is for single organization use only. Please contact us for more information on synthetic datasets for multi-partner use, FHIR server options available for testing, or hand curated datasets to meet your needs.
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.
DataMasque helps enterprises accelerate development, testing, analytics and AI with synthetically identical customer data. Fully functional, realistic and privacy compliant.