FHIR dispatches:
Smile cdr and hapi product blog



The Growth of HL7 FHIR

Published: 11 Feb 2018 at 15:06   By: James

One of the things we often talk about in the FHIR standards development community is where FHIR currently sits on Gartner’s Hype Cycle. The hype cycle is a coarse measure of the trajectory of new technologies on a journey from being “new and exciting silver bullets” to eventually being “boring useful technologies”.

When you are a proponent of a new technology (as I certainly am with FHIR), probably the most important aspect to remember about the hype cycle is that you really only ever know where you are at any given time long after that time has passed. In other words, it’s fun to ask yourself “have we passed the Peak of Inflated Expectations yet?” but you really won’t know until much later.

Speculating is perhaps a fool’s errand. I probably shouldn’t try but I can’t help but wonder if we have passed the peak yet.

The trajectory of HAPI FHIR’s growth is interesting. FHIR has been growing over the last few years by all kinds of metrics. The connectathons keep getting bigger, the number of vendors participating keeps on getting bigger, and FHIR DevDays keeps on getting bigger.

If I look at our website in Google Analytics, I am curious about the trajectory.

While HAPI FHIR has seen pretty steady growth over the last few years, that growth has been either tapering or at least very unstable over the last 8 months.

Certainly I don’t think HAPI FHIR has stopped growing. The number of messages on the support forum and the number of people with big production implementations these days certainly doesn’t suggest that; however, things have certainly been weird the last 8 months.

Let’s look at interest in FHIR overall. The next thing to look at is the FHIR Google Trends graph, which measures the number of people searching for terms on Google (a pretty decent indicator of general interest). The following graph shows the last 4 years for FHIR.

It would seem that FHIR itself saw a crazy explosion of interest back in May, too. That makes sense since FHIR R3 was released right before that peak.

Let’s compare that with the graph for IHE. I don’t think anyone would disagree that IHE sits firmly atop the Plateau of Productivity. Most people in the world of health informatics know what can be accomplished with IHE’s profiles, and certainly I’ve worked with many organizations who use them to accomplish good things.

The FHIR and IHE Graph shows interest in FHIR in BLUE and IHE in RED.

So what can we take from this? I think the right side of the graph is quite interesting. FHIR itself has kind of levelled off recently and has hit similar metrics to those of a very productive organization.

I probably shouldn’t attach too much meaning to these graphs, but I can’t help but wonder…


Tags: #Hype Cycle, #HL7, #HL7v2, #FHIR


HL7 FHIR Applications Roundtable Results

Published: 31 Jan 2018 at 17:00   By: Clement

Health Sciences South Carolina, powered by Smile CDR, were voted Best in Show for their presentation at the recent HL7 FHIR Applications Roundtable in New Orleans!

Here’s the gist of the presentation:

HSSC and Smile CDR have developed a FHIR based Clinical Data Repository infrastructure which spans several facilities. In this architecture, each facility is able to have a dedicated repository of clinical data which is populated in realtime based on feeds from various hospital EHR systems. Hospital data is normalized into FHIR Patient, Encounter, Condition, Observation, and other resources. This data infrastructure is then combined with an EMPI to provide standardized research data reporting, and to enable SMART on FHIR based apps with a longitudinal view of data across institutions.

You can watch the presentation here, and download the presentation here.

Congrats to the HSSC and Smile CDR teams!


Tags: #HL7, #FHIR Applications Roundtable, #Health Data, #Carolina Health, #SMART on FHIR, #Interoperability


New HAPI FHIR and Smile CDR Releases

Published: 24 Nov 2017 at 11:19   By: James

We are very happy to announce that we have finalized the simultaneous releases of HAPI FHIR 3.1.0 and Smile CDR 2017.11.R01.

Smile CDR 2017.11.R01

This release contains a number of enhancements, several performance enhancements, as well as some bugfixes.

The complete list of changes is available in the product Changelog.

Key improvements include:

  • Various improvements to HL7 v2.x processing modules, including support for Condition resources, better extended charset support, better detection/rejection of invalid messages (e.g. ADT^A01 with no patient specified) and more detail on mapping issues being sent to the transaction log.
  • Support for SQL Server (MSSQL) has been added
  • Audit log access via the JSON Admin API has been added
  • An annoying bug has been fixed that caused a user’s password to be reset when their permissions were changed via the Web Admin Conosle


This release brings a number of improvements:

  • Support for Android has been restored, and improved while we're at it! The use of a special "uberjar" with its own classifier is no longer required, hapi-fhir-android works as a normal Gradle dependency in your Android build. See the HAPI FHIR Android Integration Test for an example.
  • Support for the Cache-Control header has been added for JPA server searches, allowing a client to request that cached results not be used.
  • A number of bugs were fixed and performance improvements were made (see the changelog for a full list)
  • Spring has been upgraded to the 5.0 series.
  • Some initial refactoring has occurred towards enabling ElasticSearch support in JPA server. Note that any existing JPA projects will need to add an additional property in their Spring config called hibernate.search.model_mapping. See this line in the example project.
  • Support for Spring Boot has been added to many of the modules of the libaray. See the Spring Boot Samples for examples of how to use this.

Visit our release page or grab a copy via the Maven repositories.


Tags: #Smile CDR, #Releases, #HAPI FHIR