Difference between revisions of "AID 201705 Meeting in Madrid"

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==Sunday Q3/Q4 (joint with FHIR)==
 
==Sunday Q3/Q4 (joint with FHIR)==
 
===Agenda===
 
===Agenda===
#*FHIR related presentations
+
#Announcements
#Architecting a FHIR frontend using a legacy database backend, (Rene Spronk, Ringholm, NL)
+
#FHIR related presentations
#*High level introductory discussion of implementation issues
+
##Architecting a FHIR frontend using a legacy database backend, (Rene Spronk, Ringholm, NL)
#Building FHIR Servers on existing Relational Databases (Robert Worden, , UK)
+
##*High level introductory discussion of implementation issues
#*To make a FHIR Server from an  existing healthcare relational database, you have to develop transforms between FHIR resources and the native database formats - in both directions (for GET and PUT). One way to do this is to use the FHIR Transform Engine. This gives bi-directional transforms from declarative mappings - saving coding effort, and increasing reliability. Transforms integrate with the HAPI server engine. An example implementation is described.
+
##Building FHIR Servers on existing Relational Databases (Robert Worden, , UK)
#*There is an important side-benefit to this approach. RESTFul FHIR searches are converted to efficient SQL queries, automatically - supporting a wide range of searches without coding.
+
##*To make a FHIR Server from an  existing healthcare relational database, you have to develop transforms between FHIR resources and the native database formats - in both directions (for GET and PUT). One way to do this is to use the FHIR Transform Engine. This gives bi-directional transforms from declarative mappings - saving coding effort, and increasing reliability. Transforms integrate with the HAPI server engine. An example implementation is described.
#Building a FHIR frontend using Spark/Vonk (Christiaan Knaap, Furore, NL)
+
##*There is an important side-benefit to this approach. RESTFul FHIR searches are converted to efficient SQL queries, automatically - supporting a wide range of searches without coding.
#*Vonk is the newly architected Furore FHIR database frontend
+
##Building a FHIR frontend using Spark/Vonk (Christiaan Knaap, Furore, NL)
#Implementing databases for FHIR  - 3 years experience report (Niqoula Ruschkov, FHIRBase, RU)   
+
##*Vonk is the newly architected Furore FHIR database frontend
#*With the upcoming SQL standard 2017 with JSON - the FHIRBase approach will be suitable for Oracle, MSSQL and other compliant databases.
+
##Implementing databases for FHIR  - 3 years experience report (Niqoula Ruschkov, FHIRBase, RU)   
#FHIRForms: generating clinical forms from FHIR profile definitions (Robert Worden, , UK)  
+
##*With the upcoming SQL standard 2017 with JSON - the FHIRBase approach will be suitable for Oracle, MSSQL and other compliant databases.
 +
##FHIRForms: generating clinical forms from FHIR profile definitions (Robert Worden, , UK)  
 
#''Other presentations''
 
#''Other presentations''
  

Revision as of 18:32, 29 March 2017

Return to: WGM Minutes > 2017 > May Madrid

This is the agenda of the AID WG for the WGM in Madrid ES, May 2017.

Sunday Q3/Q4 (joint with FHIR)

Agenda

  1. Announcements
  2. FHIR related presentations
    1. Architecting a FHIR frontend using a legacy database backend, (Rene Spronk, Ringholm, NL)
      • High level introductory discussion of implementation issues
    2. Building FHIR Servers on existing Relational Databases (Robert Worden, , UK)
      • To make a FHIR Server from an existing healthcare relational database, you have to develop transforms between FHIR resources and the native database formats - in both directions (for GET and PUT). One way to do this is to use the FHIR Transform Engine. This gives bi-directional transforms from declarative mappings - saving coding effort, and increasing reliability. Transforms integrate with the HAPI server engine. An example implementation is described.
      • There is an important side-benefit to this approach. RESTFul FHIR searches are converted to efficient SQL queries, automatically - supporting a wide range of searches without coding.
    3. Building a FHIR frontend using Spark/Vonk (Christiaan Knaap, Furore, NL)
      • Vonk is the newly architected Furore FHIR database frontend
    4. Implementing databases for FHIR - 3 years experience report (Niqoula Ruschkov, FHIRBase, RU)
      • With the upcoming SQL standard 2017 with JSON - the FHIRBase approach will be suitable for Oracle, MSSQL and other compliant databases.
    5. FHIRForms: generating clinical forms from FHIR profile definitions (Robert Worden, , UK)
  3. Other presentations

Monday Q3

Agenda

  1. Administrative
    • Approval of the minutes

Wednesday Q1

Agenda

    • Projects
    • Next meeting