Abstract
Introduction:
The increased adoption of electronic health records (EHRs) could enable better care for patients by sharing the collected clinical data between care providers and besides better clinical research through secondary use of EHR data. Clinical research is highly dependent on this data, such as demographic information, clinical data, or device observations. Every medical centre in the western world maintains a hospital information system (HIS), usually consisting of many subsystems, that support the clinical workflow, patient safety, and legal demands. Especially in university hospitals, physicians often have obligations in addition to clinical routine: In cooperation with other scientists they conduct clinical or experimental research.
Method:
In order to ensure the reproducibility of research results and for preserving raw data, the general trend favours the pooling of research data in standardized formats. The emerging HL7 Fast Healthcare Interoperability Resources (FHIR) aims to increase interoperability, information integrity, as well as the implementability of data exchange tasks in the healthcare and research IT environment. With focus on the research platform system CentraXX (Kairos GmbH) for biobank and study management, HL7 FHIR is used in this work to improve the semantic integration, (re-)use of relevant data and for connecting point-of care medical data. The transition from the research platform to the central clinical repository is desired to be simple, robust, and direct. In order to align and to map the proprietary CentraXX data model to FHIR resources, the underlying relational database schemata were analysed to specify the scope and the requirements for the desired mapping. In the following step, the list of HL7 FHIR resources was reviewed, considering the usage, limitations, and relationships of each.
Results:
Regarding the fast development of HL7 FHIR, we decided to use a pre-released standard for trial use in version 3 (STU3) in anticipation of upcoming resources changes. Therefore, our mapping can easily be adjusted to the impending update. Eight suitable resources were identified: Patient, Encounter, Observation, Condition, Procedure, Diagnostic Report, Specimen and Consent. Some values are initially missing in the Patient resource, so a specific profile was created to represent the patients’ nationality and blood group.
Discussion:
Any mapping relies on the experts who design the mapping. The validation of the mapping was performed by one medical expert and one technical expert independently, which agreed despite of minor differences. So, a clinical repository allows for the reuse of data, yet the threat of misinterpretation of the data remains. Despite our efforts, there is no complete certainty that the acquisition context and purpose is fully represented in the repository. To minimize this threat, further tools and data quality monitoring efforts are required.
Conclusion:
The comprehensive clinical repository introduced in this paper combines patient demographic and clinical data including device observations in a standardized way. The data collected along the way of a patient’s progression through the healthcare system can thus now be reused for further research projects. As all information is represented in a standardized way, the exchange and pooling of data is significantly simplified.
The increased adoption of electronic health records (EHRs) could enable better care for patients by sharing the collected clinical data between care providers and besides better clinical research through secondary use of EHR data. Clinical research is highly dependent on this data, such as demographic information, clinical data, or device observations. Every medical centre in the western world maintains a hospital information system (HIS), usually consisting of many subsystems, that support the clinical workflow, patient safety, and legal demands. Especially in university hospitals, physicians often have obligations in addition to clinical routine: In cooperation with other scientists they conduct clinical or experimental research.
Method:
In order to ensure the reproducibility of research results and for preserving raw data, the general trend favours the pooling of research data in standardized formats. The emerging HL7 Fast Healthcare Interoperability Resources (FHIR) aims to increase interoperability, information integrity, as well as the implementability of data exchange tasks in the healthcare and research IT environment. With focus on the research platform system CentraXX (Kairos GmbH) for biobank and study management, HL7 FHIR is used in this work to improve the semantic integration, (re-)use of relevant data and for connecting point-of care medical data. The transition from the research platform to the central clinical repository is desired to be simple, robust, and direct. In order to align and to map the proprietary CentraXX data model to FHIR resources, the underlying relational database schemata were analysed to specify the scope and the requirements for the desired mapping. In the following step, the list of HL7 FHIR resources was reviewed, considering the usage, limitations, and relationships of each.
Results:
Regarding the fast development of HL7 FHIR, we decided to use a pre-released standard for trial use in version 3 (STU3) in anticipation of upcoming resources changes. Therefore, our mapping can easily be adjusted to the impending update. Eight suitable resources were identified: Patient, Encounter, Observation, Condition, Procedure, Diagnostic Report, Specimen and Consent. Some values are initially missing in the Patient resource, so a specific profile was created to represent the patients’ nationality and blood group.
Discussion:
Any mapping relies on the experts who design the mapping. The validation of the mapping was performed by one medical expert and one technical expert independently, which agreed despite of minor differences. So, a clinical repository allows for the reuse of data, yet the threat of misinterpretation of the data remains. Despite our efforts, there is no complete certainty that the acquisition context and purpose is fully represented in the repository. To minimize this threat, further tools and data quality monitoring efforts are required.
Conclusion:
The comprehensive clinical repository introduced in this paper combines patient demographic and clinical data including device observations in a standardized way. The data collected along the way of a patient’s progression through the healthcare system can thus now be reused for further research projects. As all information is represented in a standardized way, the exchange and pooling of data is significantly simplified.
Originalsprache | Englisch |
---|---|
Titel | Informatics for Health 2017 |
Erscheinungsdatum | 2017 |
Publikationsstatus | Veröffentlicht - 2017 |
Veranstaltung | Informatics for Health 2017 - Manchester , Großbritannien / Vereinigtes Königreich Dauer: 24.04.2017 → 26.04.2017 http://informaticsforhealth.org/ http://informaticsforhealth.org/ |