HIMSS Patient Data Matching on FHIR Testing Event

8/14/2015 6:00am, EDT - 2:00pm, EDT

HIMSS Innovation Center | Cleveland, OH


HIMSS Innovation Center

Invitation to participate in HIMSS Patient Data Matching on FHIR Testing Event

When:             August 14th, 2015 from 9-5
Where:            HIMSS Innovation Center
                       4th Floor of the Global Center of Health Innovation, Cleveland OH
Who:               HHS Innovators, Algorithm Vendors, Argonauts Members, Coders
Registration:  Register Here

The event will be both educational and a hands-on development opportunity.  In one day at the HIMSS Innovation Center in Cleveland, Ohio:

  • Learn from world leading experts in patient data matching, synthetic data development, and the emerging FHIR standard, and

  • Participate in testing and application development activities relating to patient data matching

Challenges to patient matching include issues such as data quality and data standardization.  FHIR, a rapidly emerging standard has the potential to simplify the process of matching by enabling a data agnostic approach to linking data.  Furthermore, access to realistic patient data is needed for testing of matching algorithms.  One solution is the use of synthetic patient data.  Synthetic patient data is computer generated data designed to mimic real world personal health data (PHI).  This non-PHI data can be instrumental for both testing of patient matching algorithms and training.

The event will be structured to implement the following:

Scenario 1:  Test Your Matching Algorithms

Connect matching algorithms to a FHIR resource server containing synthetic patient resources.  The matching algorithms will be updated to take in FHIR patient resources and then perform a de-duplication of the records.  A final list of patient resources should be produced.  Basic performance metrics can then be calculated to determine the success of the matching exercise.  Use the provided tools, or bring your own and connect them up.

Scenario 2:  Development Exercise

Develop applications that allow EHRs to easily update the status of patients who are deceased. A synthetic centralized mortality database, such as the National Death Index or a state’s vital statistics registry, will be made available through a FHIR interface.  External data sources, such as EHRs, will be matched against this repository to flag decedents. The applications should be tailored to deliver data to decision makers. This scenario will focus on how different use cases drive different requirements for matching.

FHIR Diagram