Dual Implementation Guides in FHIR and CDA

BACKGROUND

The Fast Healthcare Interoperability Resources (FHIR) and Clinical Document Architecture (CDA) are standards for the healthcare industry, designed to improve the exchange of health data by interoperability. Both standards are constrained through what are known as Implementation Guides (IG) for specific use.

OBJECTIVES

Both of these two standards are widely in use and play an important role in the Austrian healthcare system. Concepts existing in CDA and FHIR must be aligned between both standards.

METHODS

Many existing approaches are presented and discussed, none are fully suited to the needs in Austria.

RESULTS

The IG Publisher has already been used for CDA IGs, beside of its intended FHIR support, but never for both in one IG. Even the International Patient Summary (IPS), existing as CDA and FHIR specification, does not solve the needed comparability between these two.

CONCLUSION

As the IG Publisher is widely used and supports CDA, it should be used for Dual Implementation Guides. Further work and extension of IG Publisher is necessary to enhance the readability of the resulting IGs.

Interoperability in a Post-Roe Era: Sustaining Progress While Protecting Reproductive Health Information

This Viewpoint proposes a solution to better safeguard reproductive health information in patient records that are now more complete owing to the interoperability of health information exchange networks.

What do users think of the UK's three COVID-19 contact-tracing apps? A comparative analysis

OBJECTIVES

Our goal was to gain insights into the user reviews of the three COVID-19 contact-tracing mobile apps, developed for the different regions of the UK: 'NHS COVID-19' for England and Wales, 'StopCOVID NI' for Northern Ireland and 'Protect Scotland' for Scotland. Our two research questions are (1) what are the users' experience and satisfaction levels with the three apps? and (2) what are the main issues (problems) that users have reported about the apps?

METHODS

We assess the popularity of the apps and end users' perceptions based on user reviews in app stores. We conduct three types of analysis (data mining, sentiment analysis and topic modelling) to derive insights from the combined set of 25 583 user reviews of the aforementioned three apps (submitted by users until the end of 2020).

RESULTS

Results show that end users have been generally dissatisfied with the apps under study, except the Scottish app. Some of the major issues that users have reported are high battery drainage and doubts on whether apps are really working.

DISCUSSION

Towards the end of 2020, the much-awaited COVID-19 vaccines started to be available, but still, analysing the users' feedback and technical issues of these apps, in retrospective, is valuable to learn the right lessons to be ready for similar circumstances in future.

CONCLUSION

Our results show that more work is needed by the stakeholders behind the apps (eg, apps' software engineering teams, public-health experts and decision makers) to improve the software quality and, as a result, the public adoption of these apps. For example, they should be designed to be as simple as possible to operate (need for usability).

Exploring JSON-LD as an Executable Definition of FHIR RDF to Enable

This study developed and evaluated a JSON-LD 1.1 approach to automate the Resource Description Framework (RDF) serialization and deserialization of Fast Healthcare Interoperability Resources (FHIR) data, in preparation for updating the FHIR RDF standard. We first demonstrated that this JSON-LD 1.1 approach can produce the same output as the current FHIR RDF standard. We then used it to test, document and validate several proposed changes to the FHIR RDF specification, to address usability issues that were uncovered during trial use. This JSON-LD 1.1 approach was found to be effective and more declarative than the existing custom-code-based approach, in converting FHIR data from JSON to RDF and vice versa. This approach should enable future FHIR RDF servers to be implemented and maintained more easily.

Using informatics to improve cancer surveillance

OBJECTIVES

This review summarizes past and current informatics activities at the Centers for Disease Control and Prevention National Program of Cancer Registries to inform readers about efforts to improve, standardize, and automate reporting to public health cancer registries.

TARGET AUDIENCE

The target audience includes cancer registry experts, informaticians, public health professionals, database specialists, computer scientists, programmers, and system developers who are interested in methods to improve public health surveillance through informatics approaches.

SCOPE

This review provides background on central cancer registries and describes the efforts to standardize and automate reporting to these registries. Specific topics include standardized data exchange activities for physician and pathology reporting, software tools for cancer reporting, development of a natural language processing tool for processing unstructured clinical text, and future directions of cancer surveillance informatics.

One-Way and Round-Trip Analysis Demonstrates Surprising Limitations of Standards-Based Terminology Maps

The informatics community has a long-standing vision of freely flowing and highly re-usable patient-specific clinical data that improves care quality and safety. We sought to evaluate the extent to which a standards-based mapping approach is sufficient to support semantic interoperability. We simulated large-scale clinical data transmission and measured semantic success between VA and DoD systems via one-way testing (OWT) and round-trip testing (RTT). Simulations were accomplished via SQL queries and production standards-based maps for medications, allergens, document titles, vitals and payers. Success rates for mapping local codes to national standards varied from 62.5% for DoD document titles and medications, to 100% for VA and DoD vital signs. Successful, one-way testing was considerably lower, ranging from 8.52% to 62.7%. Round-trip success rates were lower still, ranging from 1.7% to 76.3%. We present an error framework, lessons learned, and proposed mitigating steps to enhance standards-based semantic interoperability.

FHIR OWL: Transforming OWL ontologies into FHIR terminology resources

The FHIR specification provides a mechanism to access clinical terminologies using a standard API, and many existing terminologies, such as SNOMED CT, are well supported. However, in areas such as genomics, terminologies from other domains are starting to be used in clinical settings. Many of these are authored or distributed in Web Ontology Language (OWL) format. In this paper we describe a transformation between OWL ontologies and FHIR terminology resources. The results show that there are several challenges in implementing the transformation, with the major one being the lack of a modularisation mechanism in the FHIR code system resource that resembles the import mecha nism available in OWL. A workaround with minimal drawbacks was successfully implemented in this solution. The availability of this transformation is significant because it enables a broad range of terminologies that are currently available in OWL to be available using the FHIR API.

Balancing Functionality versus Portability for SMART on FHIR Applications: Case Study for a Neonatal Bilirubin Management Application

SMART on FHIR applications are standards-based tools integrated with electronic health record (EHR) systems and intended for dissemination across EHR platforms. A key challenge for disseminating many apps is that EHR vendors provide different levels of support for FHIR. Thus, app developers must balance functionality versus portability. In this case study, a feature-rich app for neonatal bilirubin management was developed prioritizing physician-requested functionality, with custom FHIR interfaces implemented within the EHR as needed. Following wide intra-institutional use, several approaches are being pursued for adapting the app for cross-institutional dissemination: user surveys and interviews to identify least-valued app features which could potentially be omitted; enabling the application to provide differential features depending on available EHR FHIR capabilities; replacing custom FHIR interfaces with native EHR FHIR interfaces as they became available; and using a canonical logical data model known as QUICK that can be mapped to different FHIR versions and profiles.

High Performance Computing on Flat FHIR Files Created with the New SMART/HL7 Bulk Data Access Standard

The FHIR Bulk Data API is designed to create a uniform capability for population-level exports from clinical systems, into a file format often referred to as "Flat-FHIR." Leveraging the SMART backend services authentication and authorization profile, the approach enables healthcare providers and organizations to define and access cohorts from electronic health records and payor claims data with "push button" simplicity--a substantial advance over the current state, where each site of care needs highly skilled extraction transform and load (ETL) efforts.

Call for Data Standardization: Lessons Learned and Recommendations in an Imaging Study

PURPOSE

Data sharing creates potential cost savings, supports data aggregation, and facilitates reproducibility to ensure quality research; however, data from heterogeneous systems require retrospective harmonization. This is a major hurdle for researchers who seek to leverage existing data. Efforts focused on strategies for data interoperability largely center around the use of standards but ignore the problems of competing standards and the value of existing data. Interoperability remains reliant on retrospective harmonization. Approaches to reduce this burden are needed.

METHODS

The Cancer Imaging Archive (TCIA) is an example of an imaging repository that accepts data from a diversity of sources. It contains medical images from investigators worldwide and substantial nonimage data. Digital Imaging and Communications in Medicine (DICOM) standards enable querying across images, but TCIA does not enforce other standards for describing nonimage supporting data, such as treatment details and patient outcomes. In this study, we used 9 TCIA lung and brain nonimage files containing 659 fields to explore retrospective harmonization for cross-study query and aggregation. It took 329.5 hours, or 2.3 months, extended over 6 months to identify 41 overlapping fields in 3 or more files and transform 31 of them. We used the Genomic Data Commons (GDC) data elements as the target standards for harmonization.

RESULTS

We characterized the issues and have developed recommendations for reducing the burden of retrospective harmonization. Once we harmonized the data, we also developed a Web tool to easily explore harmonized collections.

CONCLUSION

While prospective use of standards can support interoperability, there are issues that complicate this goal. Our work recognizes and reveals retrospective harmonization issues when trying to reuse existing data and recommends national infrastructure to address these issues.

Interactive biomedical ontology matching

Due to continuous evolution of biomedical data, biomedical ontologies are becoming larger and more complex, which leads to the existence of many overlapping information. To support semantic inter-operability between ontology-based biomedical systems, it is necessary to identify the correspondences between these information, which is commonly known as biomedical ontology matching. However, it is a challenge to match biomedical ontologies, which dues to: (1) biomedical ontologies often possess tens of thousands of entities, (2) biomedical terminologies are complex and ambiguous. To efficiently match biomedical ontologies, in this paper, an interactive biomedical ontology matching approach is proposed, which utilizes the Evolutionary Algorithm (EA) to implement the automatic matching process, and gets a user involved in the evolving process to improve the matching efficiency. In particular, we propose an Evolutionary Tabu Search (ETS) algorithm, which can improve EA's performance by introducing the tabu search algorithm as a local search strategy into the evolving process. On this basis, we further make the ETS-based ontology matching technique cooperate with the user in a reasonable amount of time to efficiently create high quality alignments, and make use of EA's survival of the fittest to eliminate the wrong correspondences brought by erroneous user validations. The experiment is conducted on the Anatomy track and Large Biomedic track that are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the experimental results show that our approach is able to efficiently exploit the user intervention to improve its non-interactive version, and the performance of our approach outperforms the state-of-the-art semi-automatic ontology matching systems.

Interoperability Progress and Remaining Data Quality Barriers of Certified Health Information Technologies

The Consolidated Clinical Document Architecture (C-CDA) is the primary standard for clinical document exchange in the United States. While document exchange is prevalent today, prior research has documented challenges to high quality, effective interoperability using this standard. Many electronic health records (EHRs) have recently been certified to a new version of the C-CDA standard as part of federal programs for EHR adoption. This renewed certification generated example documents from 52 health information technologies that have been made publicly available. This research applies automated tooling and manual inspection to evaluate conformance and data quality of these testing artifacts. It catalogs interoperability progress as well as remaining barriers to effective data exchange. Its findings underscore the importance of programs that evaluate data quality beyond schematron conformance to enable the high quality and safe exchange of clinical data.

Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP

Manually annotated clinical corpora are commonly used as the gold standards for the training and evaluation of clinical natural language processing (NLP) tools. The creation of these manual annotation corpora, however, is both costly and time-consuming. There is an emerging need in the clinical NLP community for reusing existing annotation corpora across different clinical NLP tasks. The objective of this study is to design, develop and evaluate a framework and accompanying tools to support the standardization and integration of annotation corpora using the HL7 Fast Healthcare Interoperability Resources (FHIR) specification. The framework contains two main modules: 1) an automatic schema transformation module, in which the annotation schema in each corpus is automatically transformed into the FHIR-based schema; 2) an expert-based verification and annotation module, in which existing annotations can be verified and new annotations can be added for new elements defined in FHIR. We evaluated the framework using various annotation corpora created as part of different clinical NLP projects at the Mayo Clinic. We demonstrated that it is feasible to leverage FHIR as a standard data model for standardizing heterogeneous annotation corpora for their reuse and integration in advanced clinical NLP research and practices.

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Promoting national and international standards to build interoperable clinical applications

During the last decade, software supporting healthcare delivery has proliferated. This software can be divided into electronic medical record (EHR) systems and applications that treat EHRs as platforms. These collect, manage, and interpret medical data, thereby adding value to associated EHRs. To reduce the burden of developing for multiple EHR platforms, a group of standards has evolved that allow software written for one vendor's EHR to be introduced into settings supported by other vendors. The Health Services Platform Consortium (HSPC) is a collaborative effort to advocate for standards that will make healthcare applications truly interoperable. In this document, we discuss the approach adopted by the consortium and the standards central to this approach. We discriminate between interoperability standards that support the plug-and-play transfer of applications from one vendor's EHR to another and knowledge portability standards that allow knowledge artifacts used in one software environment to be introduced effectively in others.

Automated Population of an i2b2 Clinical Data Warehouse using FHIR

HL7 Fast Healthcare Information Resources (FHIR) is rapidly becoming the de-facto standard for the exchange of clinical and healthcare related information. Major EHR vendors and healthcare providers are actively developing transformations between existing EHR databases and their corresponding FHIR representation. Many of these organizations are concurrently creating a second set of transformations from the same sources into integrated data repositories (IDRs). Considerable cost savings could be realized and overall quality could be improved were it possible to transformation primary FHIR EHR data directly into an IDR. We developed a FHIR to i2b2 transformation toolkit and evaluated the viability of such an approach.

SMART on FHIR: a standards-based, interoperable apps platform for electronic health records

Objective In early 2010, Harvard Medical School and Boston Children’s Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART).

Methods We adopted contemporary web standards for application programming interface transport, authorization, and user interface, and standard medical terminologies for coded data. In our initial design, we created our own openly licensed clinical data models to enforce consistency and simplicity. During the second half of 2013, we updated SMART to take advantage of the clinical data models and the application-programming interface described in a new, openly licensed Health Level Seven draft standard called Fast Health Interoperability Resources (FHIR). Signaling our adoption of the emerging FHIR standard, we called the new platform SMART on FHIR.

Results We introduced the SMART on FHIR platform with a demonstration that included several commercial healthcare IT vendors and app developers showcasing prototypes at the Health Information Management Systems Society conference in February 2014. This established the feasibility of SMART on FHIR, while highlighting the need for commonly accepted pragmatic constraints on the base FHIR specification.

Conclusion In this paper, we describe the creation of SMART on FHIR, relate the experience of the vendors and developers who built SMART on FHIR prototypes, and discuss some challenges in going from early industry prototyping to industry-wide production use.

European Patient Summary Guideline: Focus on Greece

The European Patient Summary (PS) guideline specifies a minimal dataset of essential and important information for unplanned or emergency care initially defined in the epSOS project with aim to improve patients' safety and quality of Care. The eHealth Network of European Union (EU) Member State (MS) representatives established under Article 14 of the EU directive 2011/24 on patient rights to cross-border healthcare adopted PS guideline in November 2013 and since then the guideline has been part of MS strategic eHealth implementation plans, standardization efforts, and concrete regional, national, European and international projects. This paper reviews implementation efforts for the implementation of an operational patient summary service in Greece drawing on challenges and lessons learned for sustainable standards-based large scale eHealth deployment in Europe and abroad, as well as the reuse of best practices from international standards and integration profiles.

HeartDrive: A Broader Concept of Interoperability to Implement Care Processes for Heart Failure

This paper originates from the HeartDrive project, a platform of services for a more effective, efficient and integrated management of heart failure and comorbidities. HeartDrive establishes a cooperative approach based on the concepts of continuity of care and extreme, patient oriented, customization of diagnostic, therapeutic and follow-up procedures. Definition and development of evidence based processes, migration from parceled and episode based healthcare provisioning to a workflow oriented model and increased awareness and responsibility of citizens towards their own health and wellness are key objectives of HeartDrive. In two scenarios for rehabilitation and home monitoring we show how the results are achieved by providing a solution that highlights a broader concept of cooperation that goes beyond technical interoperability towards semantic interoperability explicitly sharing process definitions, decision support strategies and information semantics.

Towards mHealth Assessment Guidelines for interoperability: HL7 FHIR

The number of health-related mobile apps (mHealth apps) has increased dramatically over the last three years. Health professionals have started recommending apps to their patients, while healthcare systems, advocacy groups, and professional societies review or commission apps of relevance to their members. Still the issues surrounding mHealth apps are strongly debated as policy makers and legislators seek to strike the right balance between a voluntary code of conduct and regulation that can offer eHealth consumers the guidance and support they need. This paper reviews the EU policy landscape surrounding mobile health focusing on issues identified in the Green paper and follow-up activities. Then, it moves on to discuss HL7 FHIR, the mHealth WG, and relevant standardization projects and reflect on the implications for large scale eHealth deployment in Europe.

Documentation and Reporting of Nutrition - Interoperability, Standards, Practice and Procedures

Interoperability, fragmentation, standardization and data integrity are key challenges in efforts to improve documentation, streamline reporting and ensure quality of care. This workshop aims at demonstrating and discussing health politics and solutions aimed to improve nutritional status in elderly.

Clinical Predictive Modeling Development and Deployment through FHIR Web Services

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

Policy Management Standards Enabling Trustworthy pHealth

Current paradigm changes for improving safety, quality and efficiency of care processes under massive deployment of information and communication technologies (ICT) place high requirements on privacy and security. These mainly focus on privilege management and access control harmonized in international standards and their further evolution. NIST and ISO, but especially HL7 play a prominent role in this context. Starting with classic role-based access control (RBAC) foundations to new specifications for security and privacy labeling of segmented health information, HL7 security is presented as a scalable intermediate solution on the way to comprehensive privilege management and access control by explicit, ontology-based, formal and therefore machine-processable policies. The successfully balloted HL7 labeling specification supports context-sensitive communication and cooperation between different stakeholders and processes with different purposes of use, based on meta-data of information, actors and processes involved. Basics of policy management and practical solutions are discussed.

Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL

Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.

A Personal Health Record System for Diabetes Care Conforming to the ISO 16527 Interoperability Requirements

A Personal Health Record (PHR) is a health information repository controlled and managed directly by a patient or his/her custodian, or a person interested in his/her own health. PHR System's adoption and compliance with international standards is foremost important because it can help to meet international, national, regional or institutional interoperability and portability policies. In this paper, an interoperable PHR System for supporting the control of type 2 diabetes mellitus is proposed, which meets the mandatory interoperability requirements proposed in the Personal Health Record System Functional Model standard (ISO 16527). After performing a detailed analysis of different applications and platforms for the implementation of electronic Personal Health Records, the adaptation of the Indivo Health open source platform was completed. Interoperability functions were added to this platform by integrating the Mirth Connect platform. The assessment of the platform's interoperability capabilities was carried out by a group of experts, who verified the interoperability requirements proposed in the ISO 16527 standard.

The internet of things for personalized health

Advances in information and communications technologies (ICT) enable new personalized health care concepts which are often characterized by four "P" terms, i.e. personalized, predictive, preventive and participatory. However, real world implementations of the complete 4P spectrum hardly exist today. The Internet of Things (IoT) has been defined as an extension to the current Internet that enables pervasive communication between the physical and the virtual world. Smart devices and enabling elements like Near Field Communication (NFC) and Radio Frequency Identification (RFID) technology already exist and increasingly will be a mainstream element of our lives. This future vision paper attempts to assess if and how the Internet of Things for personalized health (IoT4pH) can help to facilitate the 4P healthcare paradigm and discusses related challenges and opportunities.

Towards automated biomedical ontology harmonization

The use of biomedical ontologies is increasing, especially in the context of health systems interoperability. Ontologies are key pieces to understand the semantics of information exchanged. However, given the diversity of biomedical ontologies, it is essential to develop tools that support harmonization processes amongst them. Several algorithms and tools are proposed by computer scientist for partially supporting ontology harmonization. However, these tools face several problems, especially in the biomedical domain where ontologies are large and complex. In the harmonization process, matching is a basic task. This paper explains the different ontology harmonization processes, analyzes existing matching tools, and proposes a prototype of an ontology harmonization service. The results demonstrate that there are many open issues in the field of biomedical ontology harmonization, such as: overcoming structural discrepancies between ontologies; the lack of semantic algorithms to automate the process; the low matching efficiency of existing algorithms; and the use of domain and top level ontologies in the matching process.