Personal Health Train on FHIR:A Privacy Preserving Federated Approach for Analyzing FAIR Data in Healthcare

Big data and machine learning applications focus on retrieving data on a central location for analysis. However, healthcare data can be sensitive in nature and as such difficult to share and make use for secondary purposes. Healthcare vendors are restricted to share data without proper consent from the patient. There is a rising awareness among individual patients as well regarding sharing their personal information due to ethical, legal and societal problems. The current data-sharing platforms in healthcare do not sufficiently handle these issues. The rationale of the Personal Health Train (PHT) approach shifts the focus from sharing data to sharing processing/analysis applications and their respective results. A prerequisite of the PHT-infrastructure is that the data is FAIR (findable, accessible, interoperable, reusable). The aim of the paper is to describe a methodology of finding the number of patients diagnosed with hypertension and calculate cohort statistics in a privacy-preserving federated manner. The whole process completes without individual patient data leaving the source. For this, we rely on the Fast Healthcare Interoperability Resources (FHIR) standard

HL7® FHIR® - Fast Healthcare Interoperability Resources: an introduction

After more than 20 years of experience with HL7 v2.x and 15 years with Version 3.0, HL7 International (http://www.hl7.org/) raised the question how the experience and knowledge gained could be migrated to a new, but simpler standard that is also more modern. The result is a new framework called FHIR (Fast Healthcare Interoperability Resources) that is under development and testing for more than 10 years now and will be explained in the following. The interest in FHIR is rising not only worldwide, but also in Germany leading to more FHIR-based specifications as the foundation for open and standardized interfaces.HL7 International (http://www.hl7.org/) hatte nach 20 Jahren HL7 v2.x und 15 Jahren Version 3.0 überlegt, wie man die Erfahrungen aus den vergangenen Entwicklungen zu einem neuen Standard zusammenführen könnte, der einen Einsatz gleichzeitig einfacher macht. Herausgekommen ist ein umfangreiches Rahmenwerk, das sich FHIR (Fast Healthcare Interoperability Resources) nennt, seit mehr als 10 Jahren in der Entwicklung ist und im nachfolgenden Artikel ausführlicher vorgestellt wird. Weltweit und neuerdings auch in Deutschland findet FHIR immer stärkere Beachtung und wird deshalb zur Grundlage weiterer Ausarbeitungen und Vorgaben für offene Schnittstellen