FHIR Use Case

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Full Title

Carequality FHIR Use Case Proposal



Release of PHI can only occur if the record holder has trust not only that it can accurately identify the requester, but that the request itself, and the requester’s policies and practices around the information once it is released, are appropriate. Such trust is straightforward to establish for an individual connection between two partner organizations, by relying on new or existing contractual relationships bolstered by negotiation of security and other technical details. Such an approach is not scalable, however, as the healthcare industry discovered in the context of document exchange via SOAP-based web services. Carequality’s governance framework can provide a “single on ramp” that allows an organization to sign one contract, implement one technical platform, and connect universally to a broad ecosystem of other participants.


In the FHIR spec a EHR is considered to be a data responder. Here we dstinguish between two types, the source and receiver, which can dynamically switch multiple time during a single session.

  1. Data Source = data goes from point A to point B. The source is where the data is coming from. Relative to this document, a data source can be a Query Responder or a Push Initiator.
  2. Data Receiver = data goes from point A to point B. The receiver is where the data is going to. Relative to this document, a data receiver can be a Query Initiator or a Push Recipient.
  3. Record Locator Service(RLS) = provides the ability to identify where records are located based upon criteria such as a Person ID and/or record data type, as well as providing functionality for the ongoing maintenance of this location information.
  4. Provider = A clinician or organization that is directly engaged in treatment services.
  5. Patient = A person who is the subject of health records, or an authorized representative acting on such a person’s behalf.
  6. Transaction = Per the HL7 website; an interaction that submits a set of actions to perform on a server as a single atomic action. Multiple actions on multiple resources of the same or different types may be submitted, and they may be a mix of other operations (e.g. read, search, create, update, delete, etc.)
  7. Research = Work done to improve healthcare costs, outcomes, quality, safety, and innovation via systematic investigation and structured data analysis.

FHIR Taxonomy

  • Patient = the subject of the data (A profile)
  • Observation = an entry into a data base (A profile)
  • Conformance Package will assume the US Core and CMS regulations.
  • Manifest = list of the available profile definitions
  • Implementation Guide = description of profiles in use


  • The patient has a primary care provider with up-to-date medical conditions, prescriptions and allergies.
  • The PCP uses an EHR which is part of the US Healthcare Assurance Framework.
  • All of the parties to data flow are using the US Core profile of the latest FHIR specification.


Primary Scenario:

  1. Patient is traveling, has a shoulder injury and seeks care at local rural care facility.
  2. Physician examines patient and wants to provide a pain medicine, patient cannot provide exact medicines or allergies.
  3. Phisician queries patient Medical Record Locator Service and determines appropriate prescription.

Alternative Paths:

  1. The Primary Care Physician has placed the patient records in an EHR that regularly performs scans of all patients in the EHR for health conditions.
  2. The patient is informed that health concerns are indicated and requests consent from the user to scan other health care records. (This step was missing from the original.)
  3. When indications from the scan show possible areas of concern, the EHR reaches out to all providers of care to the patient using the Medical Record Locator Service
  4. The patient is always informed when such a scan occurs and what the results were found. (This step was less informative in the original.)

A different path using biometrics:

Failed Paths:

  1. Patient not found in MRLS.
  2. Wrong record returned from MRLS
  3. Data is not sufficient to allow doctor confidence in prescribing.


Accepted Risks:

  1. The patient data is incorrect and unknowingly creates more harm that would have occured without the extra (erroneous) data.

Post Condition:

  1. I Patient outcomes are improved and dangerous conditions are avoided.



  1. Web Sites must be trusted before any user information is released.
  2. Trust federations can be used to help users make informed decisions.
  3. User consent and trust must begin before any user information is transferred.
  4. Standards exist to collect needed attributes where-ever they may be.

Workflow Diagram



  • See the wiki page FHIR to the Patient Use Case for the specific use case of the patient (or guardian) downloading machine readable data to their own device.