(Wednesday, 8/1/2018) 7:30 AM - 9:30 AM
Room: Karl Dean Ballroom B1
Purpose: Assess and capitalize FHIR (Fast Health Interoperability Resources) framework for effective data curation and exchange among multiple radiotherapy delivery systems and EMRs to build a smart analytics portal that can host quality assurance (QA), assessment tools and prospective decision-support analytics and apps for Radiation Oncology practice.
Methods: Capitalizing on the FHIR framework, an integrated data curation and analytics portal, titled HINGE (Health Information Gateway and Exchange), was built to extract, aggregate and exchange data from treatment planning and management systems (TPS and TMS), physician notes and DICOM-RT files using RESTful APIs and documents, under a service-oriented architecture (SOA) framework. HINGE has (i) TMS-extraction scripts that curate the data in JSON format and store it in a document-oriented database (ii) built-in DICOM-RT API to extract dosimetry and imaging data for dose calculations and treatment planning over HTTP protocol, (ii) natural language processing (NLP) module to extract relevant clinical measures from the clinician notes and transfer it in JSON format to the database (iii) RESTful APIs for decision-support and genomics module to provide supplementary insight to treatment predictions, treatment outcomes and research hypotheses. HINGE application would be deployed at several local healthcare facilities and transmit information to a centralized QA server and thus is suited for big data analytics. All of the modules in HINGE are self-contained and act as services among many application components over the HTTP protocol.
Results: HINGE modules exchange information in JSON format and store the data in a document-oriented database, thereby making any FHIR complaint application/software well-suited to use the HINGE infrastructure. HINGE framework readily allows deployment of prospective SMART (Substitutable Medical Apps, Reusable Technology) apps to further build upon the decision-support and predictive analytics module of HINGE.
Conclusion: An implementation of HINGE application has demonstrated successful implementation and promising potential of FHIR framework principles
Funding Support, Disclosures, and Conflict of Interest: This work is funded under the VA ROPA contract
Keywords
Data Acquisition, Quality Assurance, Quality Control
Taxonomy
IM/TH- Formal quality management tools: General (most aspects)
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