A Framework for Criteria-Based Selection and Processing of Fast Healthcare Interoperability Resources (FHIR) Data for Statistical Analysis: Design and Implementation Study

Abstract

Background The harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming original clinical data. The Fast Healthcare Interoperability Resources (FHIR) format was designed primarily to represent clinical processes; therefore, it closely resembles the clinical data model and is more widely available across modern electronic health records. However, no common standardized data format is directly suitable for statistical analyses, and data need to be preprocessed before statistical analysis. Objective This study aimed to elucidate how FHIR data can be queried directly with a preprocessing service and be used for statistical analyses. Methods We propose that the binary JavaScript Object Notation format of the PostgreSQL (PSQL) open source database is suitable for not only storing FHIR data, but also extending it with preprocessing and filtering services, which directly transform data stored in FHIR format into prepared data subsets for statistical analysis. We specified an interface for this preprocessor, implemented and deployed it at University Hospital Erlangen-Nürnberg, generated 3 sample data sets, and analyzed the available data. Results We imported real-world patient data from 2016 to 2018 into a standard PSQL database, generating a dataset of approximately 35.5 million FHIR resources, including “Patient,” “Encounter,” “Condition” (diagnoses specified using International Classification of Diseases codes), “Procedure,” and “Observation” (laboratory test results). We then integrated the developed preprocessing service with the PSQL database and the locally installed web-based KETOS analysis platform. Advanced statistical analyses were feasible using the developed framework using 3 clinically relevant scenarios (data-driven establishment of hemoglobin reference intervals, assessment of anemia prevalence in patients with cancer, and investigation of the adverse effects of drugs). Conclusions This study shows how the standard open source database PSQL can be used to store FHIR data and be integrated with a specifically developed preprocessing and analysis framework. This enables dataset generation with advanced medical criteria and the integration of subsequent statistical analysis. The web-based preprocessing service can be deployed locally at the hospital level, protecting patients’ privacy while being integrated with existing open source data analysis tools currently being developed across Germany.

Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository

“…1 schematically presents the integration of the DQA tool in the MIRACUM DIC infrastructure. Pseudonymized data are transferred via ETL processes from the source systems via a FHIR gateway server 37 into the target research data repositories. The DQA tool is able to analyze each database on its own or to compare the analysis results of two independent databases, e.g., to validate the ETL jobs.…”

“…The previously reported version of the DQA tool only focused on the DQ evaluation of the i2b2 research data repository. 15 The present work includes the extension of the DQ checks to the MIRACUM OMOP repository, 40 the FHIR gateway server, 37 and a MIRACUM staging database by complementing the respective data elements in the MDR with the information required by the DQA tool as well as providing corresponding SQL statements.…”

Generation of a Fast Healthcare Interoperability Resources (FHIR)-based Ontology for Federated Feasibility Queries in the Context of COVID-19: Feasibility Study

“…Regardless, an ontology and a mapping would have also been needed to utilize the Leaf approach. Other existing solutions utilizing the FHIR standard for federated feasibility queries rely on computer scientists to transfer their research questions to FHIR Search, CQL, or SQL [ 24 , 25 ]. Existing FHIR-based federated feasibility query tools with a graphical UI, developed for health care professionals, rely on manual curation of search criteria [ 26 , 27 ].…”

The Architecture of a Feasibility Query Portal for Distributed COVID-19 Fast Healthcare Interoperability Resources (FHIR) Patient Data Repositories: Design and Implementation Study

“…The first step toward developing our tool was to define a list of capabilities (requirements) our platform should support. Building on previous studies on usability [ 21 ], query platforms [ 22 ], feasibility queries [ 23 ], and expert interviews, we curated and prioritized our requirements using Atlassian Confluence as collaboration platform [ 24 ]. The prioritization of the features was based on the added value of a feature and the potential estimated implementation cost.…”