Standard Health Record

The Standard Health Record Collaborative is working to create the Standard Health Record (SHR), a single, high-quality health record for every individual in the United States. The SHR provides the foundation for the collection, communication, and aggregation of patient data, into one accurate, timely, precise, relevant, and complete record. SHR will accelerate secondary uses in public health, disease surveillance, post-approval monitoring, and patient-centered outcomes research. By establishing a single target for health data, the SHR can solve clinical interoperability and support a wide-range of clinicians, caregivers and healthcare providers.

Enabling transparency and precise communication across the healthcare system, the SHR leads clinicians and the American public to realize major benefits through improved care coordination, reduction of medical errors, minimization of waste, fraud, and abuse, and decreased costs that accompany healthier lives.

Currently, SHR provides standards for recording information about:

• Actors who play a role in the health space
• Immunization history of patients
• Human behaviors that impact present and future health (e.g. SmokingStatus and ContraceptiveMethodsUsed)
• Patient demographics
• Environmental factors that impact patient health and treatment access
• Life histories of patients, reflecting any changes over time
• Medications, highlighting treatment specific details and medication adherence
• Vital sign metrics crucial to emergency and in-patient treatment (e.g. DiastolicPressure and OxygenSaturation)

As an open source project, the SHR engages a broad community and can provide a powerful model for global health. To contribute, please visit the Standard Health Record Collaborative on Github. Additionally, in the spirit of engaging the open source community, we maintain a blog where we share posts on topics in data modeling, our experience with FHIR, and other healthcare topics. Visit us at lightmyfhir.org to read more!

Synthea

Synthea is a Synthetic Patient Population Simulator that is used to generate the synthetic patients. Synthea outputs synthetic, realistic (but not real) patient data and associated health records in a variety of formats. Read our wiki for more information.

Currently, Synthea features:

• Birth to Death Lifecycle
• Configuration-based statistics and demographics (defaults with Massachusetts Census data)
• Modular Rule System
• • Drop in Generic Modules
  • Custom Ruby rules modules for additional capabilities
• Primary Care Encounters, Emergency Room Encounters, and Symptom-Driven Encounters
• Conditions, Allergies, Medications, Vaccinations, Observations/Vitals, Labs, Procedures, CarePlans
• Formats
• • FHIR (STU3 v1.8)
  • C-CDA
• Rendering Rules and Disease Modules with Graphviz

To contribute please visit Synthea on Github.

SyntheticMass

SyntheticMass contains a million realistic but fictional residents of the state of Massachusetts. The synthetic population statistically mirrors the real population in terms of demographics, disease burden, vaccinations, medical visits, and social determinants. SyntheticMass establishes a risk-free environment for experimenting with:

• Data Visualization
• Risk stratification
• Care management
• Clinical decision support
• Patient reported data integration
• Evaluation of new treatment models
• Privacy and consent models
• Security and authorization models
• Third-party app development

SyntheticMass will provide a sandbox for Health IT developers, researchers and clinicians interested in exploring new healthcare solutions. It enables this through:

• Realistic data for fictional patients
• Data that is free of protected health information (PHI) and personally identifiable information (PII) constraints
• Datasets updated over time based on clinical healthcare models and epidemiological models of population health.

To contribute please visit SyntheticMass on Github

Flux Notes™

Flux Notes is an open source, standard health record-based application that demonstrates the capture of structured high quality, longitudinal and computable health records data without disrupting the clinicians' preferred narrative approach. The new health records data will support clinical oncology research and care.

Flux Notes aims to:

• Inform data-driven patient care
• Drive rare disease research
• Inform therapeutics development
• Inform regulatory decision-making
• Optimize utilization
• Lower provider burden

Flux Notes has two versions, Flux Notes Lite and Flux Notes Full. Flux Notes Lite helps clinicians capture data to drive clinical endpoints, such as disease status and toxicity. This information is stored in a structured data format that can be easily analyzed and shared across multiple clinical care sites. Flux Notes Full allows information capture via extensible structured phrases driven by the Standard Health Record (SHR). To contribute, visit the GitHub Repository.

ICAREdata™ Project

The goal of the ICAREdata Project is to support the collection of high-quality real-world data, that is complete, accurate, and computable, in a way that enables clinical oncology research.

Establishing a large scale, prospective collection and integration of high quality clinical data across multiple clinical care sites would increase the available data to include both data from randomized clinical trials (RCTs) and high-quality real-world data (RWD). This approach would also allow development of effective treatment strategies for cohorts of patients that are not amenable to study in RCTs such as rare tumors or uncommon disease types, as well as allow an understanding of the natural history and response to therapy for diseases where multiple sequential therapeutic regimens are employed. Additionally, our goal is to inform regulatory decision making by helping to determine how to best use real-world evidence for medical product regulatory decision-making and achieving efficient and accurate post-market surveillance of FDA-approved therapeutics. Lastly, this will inform data driven patient care by understanding the efficacy and safety of approved therapeutic agents in underrepresented and minority populations and accumulating a large number of patients and data required to achieve success in personalized medicine.

The Data Curation Study

The Data Curation Study is a retrospective study to evaluate the ability of a high quality, longitudinal and computable standard health record to support evidence-based, data-driven and personalized decisions in the domain of breast cancer treatment.

The approach for each of the three breast cancer patients:

• Collect longitudinal data for N years prior to the patient’s cancer diagnosis from the patient, prior and current providers and payers
• Configuration-based statistics and demographics (defaults with Massachusetts Census data)
• Curate the patient data to establish an integrated high quality, longitudinal and computable standard health record (SHR)
• Prototype visualizations of an individual patient’s SHR informed by subject matter expertise guidance on key factors in treatment decisions
• Evaluate the ability of the SHR to support evidence-based, data driven and personalized breast cancer treatment decisions

The goal is to assess the ”quality” of real world data and value of particular types of data to support breast cancer treatment decisions along with associated “cost” to collect data.

Clinical Information Interoperability Council

MITRE’s goal is to ensure that its investment in the Standard Health Record data modeling, FHIR profiling, and tooling migrates into, strengthens and expands open health data standards efforts. Health Level 7 (HL7) is the leading standards development organization for health informatics. MITRE is an active contributor to HL7’s Clinical Information Modeling Initiative (CIMI) and FHIR groups.

CIMI is the primary place where solutions to modeling requirements will be discussed and developed for the new Clinical Information Interoperability Council (CIIC) and likely for other uses. CIIC is driven by clinicians, generally through professional health societies. CIIC is a forum for gathering the clinical requirements to important project. From these requirements, open standard models can be built, thus enabling accurate collection, easy sharing, deep analysis of all data, and actions that improve the health of people and populations. MITRE serves on the leadership team of CIIC.

About the team behind Standard Health Record Collaborative

The MITRE Corporation is a not-for-profit company working in the public interest, operating multiple federally funded research and development centers (FFRDCs). FFRDCs are unique organizations that assist the United States government with scientific research and analysis, development and acquisition, and systems engineering and integration. MITRE does not have commercial interests and cannot compete for anything except the right to operate FFRDCs. This lack of commercial conflicts of interest forms the basis for MITRE’s objectivity and subsequent ability to acquire sensitive and proprietary information from the government and industry to inform critical initiatives.

The CMS Alliance to Modernize Healthcare (CAMH) FFRDC, sponsored by the Centers for Medicare & Medicaid Services (CMS), assists both the CMS and the Department of Health and Human Services (HHS) in performing research and analysis on various topics that fall within the national health domain. As the CAMH FFRDC operator and partner, MITRE serves as an objective, independent advisor to CMS and HHS operating divisions. As the only broadly healthcare-focused FFRDC, CAMH supports many of the complex analysis and critical thinking requirements that encompass the business, policy, technology, and operational interests across CMS and HHS.