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Creates a minimal set of complete, realistic synthetic patients for FHIR US Core v3.1.0 by generating a population of patients in Synthea and finding a small representive set that contain all required data elements. This small set of patients is ideal for testing because it is suitable for demonstrating support for MUST SUPPORT data elements without requiring a large set of patients or sacrificing realism.


This uscore-data-script requires working installations of Ruby and Java. After cloning this repository, run:

cd <path>/uscore-data-script
bundle install

Creating the Data Set

  1. Run uscore-data-script

The uscore-data-script will execute Synthea to generate synthetic patients, load the resulting FHIR Bundles, and select certain patients based on criteria described below.

bundle exec ruby uscore-data-script.rb [mrburns]

There is an optional mrburns parameter, which if included, will generate a single longitudinal patient who possesses at least one resource conforming to every US Core profile. In other words, one patient with everything. If the mrburns parameter is not included, the script will generate a small collection of testing patients.

  1. Use Data

Use the data files located in /output/data. It includes

What uscore-data-script does

This data script searches through patient data generated by Synthea and attempts to pick the minimum number of patients satisfying these criteria:

  • At least one male, at least one female
  • One white, one black, one Hispanic
  • One child, one adult, one elderly
  • One must be a smoker
  • One must have an allergy
  • The child must have immunizations
  • The child must not be a smoker
  • The elderly patient must have an implantable device
  • All patients together must satisfy all US Core Implementation Guide profiles

After selecting patients, the data script then makes the following modifications:

  • Remove excess (>30 of each resource type per patient) resources that aren't required to fulfill a needed profile.
  • If no smoker was found, make one of the patients a smoker.
  • Pick one patient, select a condition and replace the category with data absent reason unknown.
  • Pick one patient, select the patient name, and replace name data with data absent reason unknown.
  • If no stand-alone Medication was found (i.e. all the medications were RxNorm codes) then pick a patient, and modify a MedicationRequest to have a reference to a stand-alone Medication.
  • Add a "discharge Disposition" to each encounter.
  • Add a "Goal" to each patient, unless one exists.
  • Loop through resource types that require multiple must-support reference types, and ensure we have at least one of each on at least one patient.
  • Loop through resource/profile types that require multiple must-support choice types, and ensure we have at least one of each on at least one patient (only for date/time choice types at the moment).
  • Remove all Claims and Explanation of Benefits.
  • Update each Patient Provenance references.

Finally, the data script runs the FHIR Validator on each Bundle and writes the results to ./output/validation


  • This script does not include every single Must Support element.
    • In particular, Observation.dataAbsentReason on Pediatric BMI and Pediatric Weight, because the Observation.value[x] are required fields. It is not valid for values to be absent.


Copyright 2020 The MITRE Corporation

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.