1. RAIN Live Oak Data Provenance API
Stage 1 – ONC Data Provenance Challenge -

2. Data Provenance In Diverse Exchange
Data Provenance has the power to transform disparate patient records spanning numerous facilities into a unified chart of a patient's health status and history. Reliable provenance improves trust in data, clarifies the parties involved in each medical encounter, and better illustrates how each piece of information fits into the large image of that patient's health and care needs.

3. Challenges To Implementing Data Provenance
Diverse Repositories: The wide range of health data vendors active today create a range of repository designs and schemas; widely usable provenance generators must be flexible to data structures
Reliable Exchange: Varied health document standards, structures and selected dataset can see some data elements omitted when shared; Data Provenance must be included to maintain a chain of integrity
Evolving Exchange: As new exchange modes emerge and new document models such as FHIR are introduced, clinical repositories must be able to maintain provenance across the full spectrum of storage and exchange methods available to them
Standardized, automated Data Provenance will maintain integrity and improve quality of care informed by that data

4. Cross-Platform Provenance Generation & Validation
The outcome of our project will be a cross-platform library supporting generation, management, serialization, and validation of Data Provenance independent of specific repository or document types.
This Provenance Toolset will serve as a component of health systems, acting as a plug-in or independent service to handle management of provenance on behalf of other system components.
This de-coupled approach, facilitated by a simple API to enable schema-specific expansion, will give varied data services access to provenance generation and validation without requiring those services to handle such operations themselves.

5. Varied Datasets & Document Standards
The nature of provenance varies depending both on the type of data being addressed and the document standard carrying it. To address these variances our Provenance Toolset will include design principles such as:
Provenance As Object: Abstracting provenance data as a dynamic object, rather then a concrete document, will enable the Toolset to more easily apply logic, validate member fields, and translate/format user-provided data
Extensible Serialization: Once generated, provenance models can then be serialized into text form for inclusion in health documents. By separating data processing from the final concrete document type we will increase flexibility and allow serialization according to a variety of library-included or user defined document guidelines
Partial Templates: Flexible serialization will also enable flexible deserialization, allowing the Toolset to accept partial or pre-generated Provenance documents as input. Once deserialized, the provenance records can then be edited, updated, validated and fully filled-in before being re-serialized for including in a final document

6. Core Data Points
In developing a cross-platform Data Provenance Toolset, the baseline for our data model will be the FHIR Provenance resource. This provides a strong starting point for provenance documents, which can then be adapted/expanded to meet the needs of other documents standards.
Major FHIR Provenance data elements include:
Period of activity
Provenance timestamp
Relevant location
Event/activity type
Actor(s) involved
Such data elements can be manually or programatically populated to support conformance, as well as interacting with cooperative APIs to retrieve information (such as specific individual or location information) from a remote repository.
A final key element of Provenance is the digital signature, vital for ensuring integrity of the provenance and to attest to the party responsible for provenance generation. The Toolset will enable automated generation of such signatures using key-pairs owned by the generating part.

7. Provenance Anywhere.
Data Provenance is a needed next step in the progression of health infomatics. As medical data systems grow ever larger, serving ever more patients, physicians needs to know more about the data they rely on to make clinical decisions.
A flexible, platform-independent Provenance Toolset will expedite the integration of provenance into existing and new health systems by delivering an abstracted API that handles generation, management and validation as a self-contained service.
A Toolset capable to generating provenance for a variety of repository and document types will ensure more consistent and widely adopted provenance, improving trust in data, enabling better use of patient-generated data, and reducing redundancy by ensuring integrity and improving the viable life-span of provenance-backed patient health records.
As data moves, provenance travels with it, ensuring accuracy and improving outcomes at every stage of care.

8. For Additional Information Contact
Timothy Tyndall – Executive Director – RAIN Live Oak –
Ayami Tyndall – Network Systems Director – RAIN Live Oak –