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The Rheinisch-Westfälische Technische Hochschule Aachen, or RWTH Aachen University, is a prestigious public research university in Aachen and the largest technical university in Germany. Their university hospital, Uniklinik RWTH Aachen, is one of the participants of the Medical Informatics Initiative (MII) in Germany and also an active user of Firely’s Simplifier.net platform and Firely Server. For this case study we interviewed Danny Wenders from the Data Integration Center at Uniklinik RWTH Aachen to talk about two exciting FHIR use cases that significantly accelerate patient care and research. He is one of the FHIR experts within the hospital and is responsible for their FHIR Server.
The power of data for patient care and research
The following initiatives became possible when the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, or BMBF) launched its 120 million euro (€ 120,000,000) medical informatics funding scheme to make data from healthcare and research more useful and meaningful. Uniklinik RWTH Aachen became part of the MII SMITH consortium, along with Leipzig University Medical Center, University Hospital Jena and other partners.
Within the MII, relevant data is collected from the source systems of the various partners. This results in large data sets among various patient populations. The main goal of the MII architecture is to enable complex analyses on these aggregated data sets, ultimately resulting in better analytics than previously possible. The SMITH consortium’s use cases focus on patient care and clinical research. To leverage the value of data, the MII agreed on a core data set and a common format. Unsurprisingly, they chose FHIR as the technical format for the core data models.
HELP and ASIC to improve and save patient lives
Danny Wenders tells us that Uniklinik RWTH Aachen is involved in several MII use cases, two of which belong to the SMITH consortium. The first use case is called HELP, an application that electronically supports physicians in the diagnostic and therapeutic procedure for patients with bloodstream infections due to staphylococcal bacteremia. They developed a hospital-wide Computer-aided Decision Support System (CDSS) to improve patient care for these cases. The HELP application provides medical details with information and recommendations on the next diagnostic and therapeutic steps for an antibiotic therapy. Thus, patient care can be improved and antibiotic-related multi-resistance can be avoided.
The second use case Danny shared is called ASIC. This clinical use case focuses on the early diagnosis of intensive care patients with ARDS (Acute Respiratory Distress Syndrome). This is made possible by continuously screening and monitoring data via the Patient Data Management System (PDMS). To do this, Uniklinik RWTH Aachen developed the ASIC mobile application. By using the ASIC app, relevant data like ventilation parameters are taken from the PDMS and is analyzed for the potential presence of ARDS. If ARDS is suspected, the app sends an alert at an early stage and thus enables the intensive care physician to execute rapid diagnostic measures and therapeutic action according to the guidelines. The physician checks the complete diagnostic criteria for ARDS (Berlin criteria) using additional patient data at the bedside. If the criteria is met after the medical review and the diagnosis is confirmed, the app displays the respective severity and the relevant guideline-based therapy recommendations. Talk about saving lives with data.
FHIR is easy, getting into FHIR is not
In the MII, FHIR is one of the key building blocks for creating apps like these. It is the canonical data model for all the use cases of all the consortia of university hospitals. The FHIR Profiles and Implementation Guides for the various MII projects are maintained on Simplifier.net. For Uniklinik RWTH Aachen this means that all their data is converted to the FHIR data models defined by MII. This is the most challenging step because data is spread over various systems in different hospitals with their own technical formats and semantics.
“Once the data is available in FHIR, it’s relatively easy to build apps. But getting all the data into the MII definitions of FHIR is the real challenge.”Danny Wenders, Uniklinik RWTH Aachen
For data conversion, for instance of HL7v2 messages, SMITH uses the InterSystems DTL tooling and the InterSystems proprietary data model SDA (Summary Document Architecture) as an intermediate step. This process involves data cleansing, harmonization, deduplication, and getting rid of dialects in v2.
The steps towards FHIR
Once data is transformed into SDA and stored in InterSystems IRIS, the data can be requested via a FHIR API. Upon invocation, the data is then converted to FHIR and stored in Firely Server. App developers of the use case-specific apps only need to know about the FHIR API and do not need to worry about the heavy lifting of getting data into FHIR. FHIR is the preferred data model for the use cases. Firstly, because it is an open standard, secondly, because it has a rich API. And lastly, there is no vendor locking. The FHIR ecosystem has an abundance of (open-source) tooling available.
Powerful FHIR search
We asked Danny Wenders why they use Firely Server instead of other FHIR servers in the market. His initial answer: the rich implementation of FHIR search within Firely Server made it easier for them to build the necessary features and algorithms for MII.
“We chose Firely Server mainly because of its rich implementation of FHIR search. This allows us to build the features we need to build the algorithms in MII.”Danny Wenders, Uniklinik RWTH Aachen
It wasn’t the only reason. Danny also highlights the support for SQL Server, the option of building a Facade, and the superior performance of Firely Server. While Firely Server is deployed on internal servers using the binaries, the database is hosted on a separate server. In fact, two instances of Firely Server are deployed: one for the pseudonymized data for research purposes, another for personal health data for clinical care.
Plans for the future
When asking Danny about the plans for future expansion, he mentions the implementation of authentication and authorization within the consortium which is something that is currently still on their backlog.
Beyond and after MII
The MII funding has recently been extended by the federal government. This is good news of course, but it remains to be seen what will happen with the projects after the MII grants are ended. Danny is hopeful. Other MII projects use different approaches but one thing is always the same: FHIR.
“An open FHIR data platform will become a necessary building block in any university hospital, both for research and for clinical care. You need an easy and open entry point for doctor and patient apps and research.”Danny Wenders, Uniklinik RWTH Aachen