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 5 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:
2,865 total A01
11 total A02
2,865 total A03
36,297 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: 13,877
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: 618
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: 39,162
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: 14,238 bundles containing an average of 100 FHIR resources in each bundle (~1,423,000 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 (Units). You buy access to one synthetic data pack containing 1,000 patients with five years of longitudinal records. Pricing is based on units of product access under a contract, not on usage or instance size. There are no separate tiers, add-ons, or scaling options in this listing. Each unit grants access to the fully-synthetic healthcare dataset described. To adjust the data volume or request tailored datasets, you would contact the vendor about custom options outside this fixed pack.
Top-of-mind questions for buyers
What does one unit of Product Access give me in this data pack?
One unit grants access to a fully-synthetic dataset covering 1,000 patients with five years of longitudinal records. The data includes clinical and claims records generated using a Monte Carlo simulation technique. It spans healthcare messages across several HL7 standards, including ADT, ORU, VXU, CCD, and FHIR.
What conditions and use cases does the synthetic data cover?
The dataset models clinically relevant scenarios such as appendicitis, deep venous thrombosis, food insecurity, hypertension, osteoporosis, and pulmonary embolism. You can use it for interoperability testing, risk assessment, gaps-in-care analysis, machine learning training, and end-to-end solution testing. All records are synthetic and free from real patient information.
Can I get a larger dataset or one tailored to my needs?
This listing covers one fixed pack of 1,000 patients with five years of data. It does not scale within the listing itself. For a different data volume or a dataset built for your specific requirements, you would contact the vendor about custom or bespoke options outside this pack.
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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.
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.