Building FHIR Servers on Existing Applications Robert Worden
Transcription
Building FHIR Servers on Existing Applications Robert Worden
Building FHIR Servers on Existing Applications Robert Worden [email protected] Outline • • • • • • • FHIR and CDA Building FHIR Servers and Clients Mapping Application Databases to FHIR FHIR Server Demo FHIR Client for Multiple Servers FHIR and Data Matching CDA-FHIR Bridge More Meaningful Use of CDA • When reading a CDA, a physician is not just a blank slate for new information. • Often, he or she knows about the patient already. • The physician needs to compare the new information in the CDA with what they already know. • Their knowledge of the patient may be stored in an EMR. • Comparing requires matching of information from the CDA, with information in the EMR: – Match and identify the patient – Match clinical data for the patient (e.g. allergies, medications,..) • Then (possibly) make updates to the EMR, at the physician’s discretion Architecture for CDA Match/Compare Patient Search Parameters CDA Handler Module: CDA •Extract patient data from CDA •Search and match patients •User chooses the matching patient •Extract clinical information from CDA •Compare with clinical information from application • (User choice of updates to the application) Candidate Matching Patients Selected Matching Patient Clinical Application (e.g. EHR) Patient Clinical Information (Updates to Clinical Information) Few clinical applications support this now. FHIR-enabled CDA Match/Compare User Searches on Patient Patient Resource CDA Candidate Patient resources search FHIR CDA-FHIR Bridge Searches on Clinical Resources Clinical Resources Search, Match and Display (FHIR client) data FHIR Searches on Clinical Resources Clinical Resources FHIR server adapter for application Clinical Application (update) (Updates to Clinical Resources) Three components simplify implementation. Building FHIR Servers and Clients from Existing Applications Client A Server B User Interface User Interface Business Logic Relational Database FHIR Adapter FHIR Adapter Business Logic Relational Database What FHIR Adapters Do • (Client) compose a FHIR search request (e.g. for a Patient Resource, with given NHS number). • (Client) send the FHIR search request • (Server) translate the FHIR search request into search commands for its internal data structures (e.g. SQL) • (Server) translate the results of internal searches (e.g. SQL ResultSets) into FHIR resources • (Server) send a bundle of FHIR Resources • (Client) translate the FHIR resources into its internal data structures (e.g. RDBMS records) Three Kinds of Data Transform 1. FHIR Search => Search commands for internal data structures 2. Internal data structures => FHIR resource 3. FHIR resource => Internal data structures Do you need to write software to do this? No: All three types of data transform can be generated from one set of declarative mappings. Mapping and Transformation Toolset • Define a Logical Model of information to be exchanged (UML, expressed in Eclipse Ecore) • Define Mappings of any physical data structure onto the Logical Model • Mappings state precisely how the physical data structure represents information in the logical model. • Mappings are declarative and easily testable. • Open Source tools are used to define, validate, and test the mappings. • The same tools generate any-to-any transforms between the data structures (in Java or XSLT) • Generated transforms are precise and testable (e.g. round trip tests) Mappings, Transforms, and FHIR CDA XML Structure M = mappings B = Bridge M V2 XML Data Structure M FHIR class model (EMF Ecore) B FHIR Java reference implementation FHIR serialisation (XML or JSON) M Relational Database Structure Any-to-any transforms can be generated from the mappings. We are interested in Relational Database <=> FHIR Mapping a Relational Database to the FHIR Patient Resource FHIR Server Farm • Web service under Tomcat • Currently two FHIR servers, created by mapping Relational Databases to FHIR resources: – PAS system database – ‘Noddy’ patient database (1 table) • • • • • Jdbc access to the databases Read-only FHIR servers for the Patient resource Support a range of Patient searches Each server is defined entirely by configuration files No database-specific or resource-specific code FHIR Server Farm Architecture Web server (e.g. Tomcat) Browser Client Application http FHIR MultiServer jdbc Relational Database 1 Relational Database 2 Configuration Configuration File Configuration File File 3 Relational Database 3 No Database-specific or Resource-specific code! Demo of FHIR Server Farm FHIR and IHE PDQ (HL7 V2.5) FHIR Search QBP^Q22 FHIR Patient Server Patient Resources Patient Demographics Supplier RSP^K22 FHIR and Data Matching • As soon as a provider has two or more FHIR servers for the Patient resource, they can compare the Patients across them (in the common FHIR representation). • An application can interrogate the different FHIR servers, and compare the results • An Open Source Comparative Query Tool can compare across the servers, in terms of the FHIR Patient class model • Bulk data matching and de-duplication can be done across databases (proprietary tool) Searching Multiple FHIR Servers CDA-FHIR Bridge • Enables any incoming CDA as a small FHIR server • The CDA ‘server’ supports FHIR searches on common resources (Patient, AllergyIntolerance,...) • This is not a full transform from CDA to a FHIR Composition resource; extracting specific FHIR resources is much easier • Transforms depend on CDA templates • There will be a different bridge for each CDA profile • There is no dependence on the EHR application – the bridge is universal for each CDA profile • Easy to build The CDA-FHIR Opportunity Applications FHIR-enabled for other reasons Build CDA-FHIR bridges FHIR-enabled applications can easily make Meaningful Use of CDA More applications FHIR-enabled, to make meaningful use of CDA More takeup of CDA Easier to make meaningful use of CDA Virtuous Circle FHIR Mapping Tools: Work In Progress • Deployment: currently deploying a FHIR Patient server for an NHS Trust; more are planned • Searches: extend capability to more types of search, e.g. date range, alternative values,... • Extensions: can hide the extra complexity of FHIR extensions – extensions are identical to core features, in the Ecore class model and in mappings. • Write operations: The tools generate the required data transforms, but will always require business logic • Documentation of the Open Source Tools: Real soon now • FHIR Server Configuration Service: ask [email protected]