Fast Healthcare Interoperability Resources Standard Research Articles

Evolving Software Architecture Design in Telemedicine: A PRISMA-based Systematic Review.

This article presents a systematic review of recent advancements in telemedicine architectures for continuous monitoring, providing a comprehensive overview of the evolving software engineering practices underpinning these systems. The review aims to illuminate the critical role of telemedicine in delivering healthcare services, especially during global health crises, and to emphasize the importance of effectiveness, security, interoperability, and scalability in these systems. A systematic review methodology was employed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. As the primary research method, the PubMed, IEEE Xplore, and Scopus databases were searched to identify articles relevant to telemedicine architectures for continuous monitoring. Seventeen articles were selected for analysis, and a methodical approach was employed to investigate and synthesize the findings. The review identified a notable trend towards the integration of emerging technologies into telemedicine architectures. Key areas of focus include interoperability, security, and scalability. Innovations such as cognitive radio technology, behavior-based control architectures, Health Level Seven International (HL7) Fast Healthcare Interoperability Resources (FHIR) standards, cloud computing, decentralized systems, and blockchain technology are addressing challenges in remote healthcare delivery and continuous monitoring. This review highlights major advancements in telemedicine architectures, emphasizing the integration of advanced technologies to improve interoperability, security, and scalability. The findings underscore the successful application of cognitive radio technology, behavior-based control, HL7 FHIR standards, cloud computing, decentralized systems, and blockchain in advancing remote healthcare delivery.

Pediatric Consent on FHIR.

Standardizing and formalizing consent processes and forms can prevent ambiguities, convey a more precise meaning, and support machine interpretation of consent terms. Our goal was to introduce a systematic approach to standardizing and digitizing pediatric consent forms, which are complex due to legal requirements for child and legal guardian involvement. First, we reviewed the consent requirements from the Arizona regulation, and we used 21 pediatric treatment consents from five Arizona health care organizations to propose and evaluate an implementation-agnostic Consent for Treatment Framework. Second, we assessed the adequacy of the Fast Healthcare Interoperability Resources (FHIR) to support the proposed framework. The resulting Consent for Treatment Framework supports compliance with the state consent requirements and has been validated with pediatric consent forms. We also demonstrated that the FHIR standard has the required expressiveness to compute the framework's specifications and express the 21 consent forms. Health care organizations can apply the shared open-source code and FHIR implementation guidelines to standardize the design of machine-interpretable pediatric treatment consent forms. The resulting FHIR-based executable models may support compliance with the law and support interoperability and data sharing.

CodeX quality measures for cancer: Leveraging FHIR and mCODE to support digital quality measures.

466 Background: CodeX is a member-driven Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) Accelerator, building a community to fast-track interoperable data modeling and implementation of new FHIR data standards leading to step-change improvements in patient care and research. The Quality Measures for Cancer project asks the question, “Can oncology quality measures be effectively authored and executed using minimal Common Oncology Data Elements (mCODE) — an initiative intended to assemble a core set of structured data elements for oncology electronic health records (EHRs) — and FHIR, given that current measures must be manually collected and abstracted?” The Quality Measures for Cancer project aims to provide a less burdensome path for all parties involved in the quality measure lifecycle to share standardized oncology quality measure data. Methods: The Quality Measures for Cancer project has assembled a team of leading healthcare professionals from American Society of Clinical Oncology (ASCO), American Society for Radiation Oncology (ASTRO), Telligen, Evernorth, and MITRE to create a solution that demonstrates the ability to author and evaluate digital quality measures using FHIR standards, along with mCODE profiles and extensions, for value-based programs and clinical quality improvement in the oncology domain. More specifically, the initial project scope focuses efforts to: Develop a process for identifying the required discrete data to be used for data collection and aggregation; and prove that measures can be authored, generate accurate results, and can be executed using mCODE and FHIR. Results: Over the first year of project work, the Quality Measures for Cancer team has demonstrated that mCODE and FHIR can be used to author and execute oncology measures. The team has fully authored and tested two proof of concept ASCO antiemetic electronic clinical quality measures (eCQMs) using mCODE, FHIR, and the Quality Measures Implementation Guide. A demonstration is available to show the team's recent success with testing the feasibility and value of authoring and executing the two ASCO antiemetic eCQMs using mCODE and FHIR, evaluating the measure, and discussing how burden is reduced for providers, as well as submitters and receivers of quality measures. Conclusions: Long-term, the CodeX Quality Measures for Cancer team posits that by leveraging mCODE and FHIR to assist in the development and authoring of innovative oncology quality measures, real and impactful insight and assessment into true quality measures could be made if mCODE and other FHIR Implementation Guides are implemented and leveraged by an ecosystem of health organizations. This project is acting as an exemplar showing what can be achieved by leveraging several quality-specific FHIR Implementation Guides to create and roll out new, innovative quality measures.

Computer-Supported Collaborative Design of Standardized Clinical Cases.

The creation of computer-supported collaborative clinical cases is an area of research in teaching that has been widely studied. However, the reuse of cases and their sharing with other platforms is a problem that encapsulates knowledge in isolated platforms without interoperability. This paper proposes a workflow ecosystem for the collaborative design and distribution of clinical cases through online computing platforms that (i) allow medical students to create clinical cases collaboratively in a dedicated environment; (ii) make it possible to export these clinical cases in terms of the HL7 FHIR interoperability standard; (iii) provide support to transform imported cases into learning object repositories, and (iv) use e-learning standards (e.g., IMS CP, SCORM) to incorporate this content into widely-used learning management systems, letting medical students democratize a valuable knowledge that would otherwise be confined within proprietary platforms. To demonstrate the feasibility of developing a workflow ecosystem based on IT platforms to enable collaborative creation, export, and deployment of clinical cases. The ecosystem infrastructure for computer-supported collaborative design of standardized clinical cases consists of three platforms: (i) Mosaico, a platform used in the design of clinical cases; (ii) Clavy, a tool for the flexible management of learning object repositories, which is used to orchestrate the transformation and processing of these clinical cases; and (iii) Moodle, a Learning Management System (LMS) that is geared towards publishing the processed clinical cases and delivering their course deployment stages in IMS CP/SCORM format. The generation of cases in Mosaico is exported in the HL7 FHIR interoperability standard to Clavy, responsible for creating and deploying a learning object in Moodle. The main result is an interoperable ecosystem that demonstrates the feasibility of automating the stages of collaborative clinical case creation, export through HL7 FHIR, and deployment in an LMS, enabling the generation of IMS Content Packages associated with the original Mosaico clinical cases that can be deployed in conventional third-party LMSs. This allows the democratization and sharing of clinical cases to different platforms in standard and interoperable formats. In this article, we have proposed, implemented, and demonstrated the feasibility of developing a standards-based workflow that interoperates multiple platforms with heterogeneous technologies to create, transform and deploy clinical cases online. This achieves the objective of transforming the created cases into a platform for online deployment in a learning management system.

Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review.

Machine learning-enabled clinical information systems (ML-CISs) have the potential to drive health care delivery and research. The Fast Healthcare Interoperability Resources (FHIR) data standard has been increasingly applied in developing these systems. However, methods for applying FHIR to ML-CISs are variable. This study evaluates and compares the functionalities, strengths, and weaknesses of existing systems and proposes guidelines for optimizing future work with ML-CISs. Embase, PubMed, and Web of Science were searched for articles describing machine learning systems that were used for clinical data analytics or decision support in compliance with FHIR standards. Information regarding each system's functionality, data sources, formats, security, performance, resource requirements, scalability, strengths, and limitations was compared across systems. A total of 39 articles describing FHIR-based ML-CISs were divided into the following three categories according to their primary focus: clinical decision support systems (n=18), data management and analytic platforms (n=10), or auxiliary modules and application programming interfaces (n=11). Model strengths included novel use of cloud systems, Bayesian networks, visualization strategies, and techniques for translating unstructured or free-text data to FHIR frameworks. Many intelligent systems lacked electronic health record interoperability and externally validated evidence of clinical efficacy. Shortcomings in current ML-CISs can be addressed by incorporating modular and interoperable data management, analytic platforms, secure interinstitutional data exchange, and application programming interfaces with adequate scalability to support both real-time and prospective clinical applications that use electronic health record platforms with diverse implementations.

The Design and Construction of a 12-Channel Electrocardiogram Device Developed on an ADS1293 Chip Platform

An accurate and compact electrocardiogram (ECG) device will greatly assist doctors in diagnosing heart diseases. It will also help to address the increasing number of deaths caused by heart disease. Accordingly, the goal of the project is to design and construct an easy-to-use compact 12-lead electrocardiogram device that communicates with a computer to create a system that can continuously monitor heart rate and which can be connected to allied medical systems. The design is based on an ECG receiver circuit utilizing an IC ADS1293 and an Arduino Nano. The ADS1293 has built-in input Electromagnetic Interference (EMI) filters, quantizers, and digital filters, which help in reducing the size of the device. The software has been created using the C# programming language, with Windows Presentation Foundation (WPF), aiding the collection of the ECG signals from the receiving circuit via the computer port. An ECG Multiparameter Simulator has been used to calibrate the ECG device. Finally, a plan has been developed to connect the arrangement to health systems according to HL7 FHIR (Health Level Seven Fast Healthcare Interoperability Resources) through Representational State Transfer Application Programming Interface (Rest API). The ECG device, completed at the cost of U$169 excluding labor, allows for the signal of 12 leads of ECG signal to be obtained from 10 electrodes mounted on the body. The processed ECG data was written to a JSON file with a maximum recording time of up to three days, managed by a Structured Query Language Server (SQL) Server database. The software retrieves patient data from electrical medical records in accordance with HL7 FHIR standards. A compact and easy-to-use ECG device was successfully designed to record ECG signals. An in-house developed software was also completed to display and store the ECG signals.

Assessing clinical site readiness for electronic health record (EHR)-to-electronic data capture (EDC) automated data collection

BackgroundeSource software is used to automatically copy a patient's electronic health record data into a clinical study's electronic case report form. However, there is little evidence to assist sponsors in identifying the best sites for multi-center eSource studies. MethodsWe developed an eSource site readiness survey. The survey was administered to principal investigators, clinical research coordinators, and chief research information officers at Pediatric Trial Network sites. ResultsA total of 61 respondents were included in this study (clinical research coordinator, 22; principal investigator, 20; and chief research information officer, 19). Clinical research coordinators and principal investigators ranked medication administration, medication orders, laboratory, medical history, and vital signs data as having the highest priority for automation. While most organizations used some electronic health record research functions (clinical research coordinator, 77%; principal investigator, 75%; and chief research information officer, 89%), only 21% of sites were using Fast Healthcare Interoperability Resources standards to exchange patient data with other institutions. Respondents generally gave lower readiness for change ratings to organizations that did not have a separate research information technology group and where researchers practiced in hospitals not operated by their medical schools. ConclusionsSite readiness to participate in eSource studies is not merely a technical problem. While technical capabilities are important, organizational priorities, structure, and the site's support of clinical research functions are equally important considerations.

Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study.

Clinical decision support (CDS) can improve health care with respect to the quality of care, patient safety, efficiency, and effectiveness. Establishing a CDS system in a health care setting remains a challenge. A few hospitals have used self-developed in-house CDS systems or commercial CDS solutions. Since these in-house CDS systems tend to be tightly coupled with a specific electronic health record system, the functionality and knowledge base are not easily shareable. A shared interoperable CDS system facilitates the sharing of the knowledge base and extension of CDS services. The study focuses on developing and deploying the national CDS service for the drug-allergy interaction (DAI) check for health care providers in Korea that need to introduce the service but lack the budget and expertise. To provide the shared interoperable CDS service, we designed and implemented the system based on the CDS Hooks specification and Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The study describes the CDS development process. The system development went through requirement analysis, design, implementation, and deployment. In particular, the concept architecture was designed based on the CDS Hooks structure. The MedicationRequest and AllergyIntolerance resources were profiled to exchange data using the FHIR standard. The discovery and DAI check application programming interfaces and rule engine were developed. The CDS service was deployed on G-Cloud, a government cloud service. In March 2021, the CDS service was launched, and 67 health care providers participated in the CDS service. The health care providers participated in the service with 1,008,357 DAI checks for 114,694 patients, of which 33,054 (3.32%) cases resulted in a "warning." Korea's Ministry of Health and Welfare has been trying to build an HL7 FHIR-based ecosystem in Korea. As one of these efforts, the CDS service initiative has been conducted. To promote the rapid adoption of the HL7 FHIR standard, it is necessary to accelerate practical service development and to appeal to policy makers regarding the benefits of FHIR standardization. With the development of various case-specific implementation guides using the Korea Core implementation guide, the FHIR standards will be distributed nationwide, and more shared interoperable health care services will be introduced in Korea.

Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR).

BackgroundReferral linkages are crucial for efficient functioning of primary health care (PHC) systems. Fast Healthcare Interoperability Resource (FHIR) is an open global standard that facilitates structuring of health information for coordinated exchange among stakeholders.ObjectiveThe objective of this study is to design FHIR profiles and present methodology and the profiled FHIR resource for Maternal and Child Health referral use cases in Ebonyi state, Nigeria—a typical low- and middle-income country (LMIC) setting.MethodsPracticing doctors, midwives, and nurses were purposefully sampled and surveyed. Different referral forms were reviewed. The union of data sets from surveys and forms was aggregated and mapped to base patient FHIR resource elements, and extensions were created for data sets not in the core FHIR specification. This study also introduced FHIR and its relation to the World Health Organization’s (WHO’s) International Classification of Diseases.ResultsWe found many different data elements from the referral forms and survey responses even in urban settings. The resulting FHIR standard profile is published on GitHub for adaptation or adoption as necessary to aid alignment with WHO recommendations. Understanding data sets used in health care and clinical practice for information sharing is crucial in properly standardizing information sharing, particularly during the management of COVID-19 and other infectious diseases. Development organizations and governments can use this methodology and profile to fast-track FHIR standards adoption for paper and electronic information sharing at PHC systems in LMICs.ConclusionsWe presented our methodology for profiling the referral resource crucial for the standardized exchange of new and expectant moms’ information. Using data from frontline providers and mapping to the FHIR profile helped contextualize the standardized profile.

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

BackgroundAn essential step in any medical research project after identifying the research question is to determine if there are sufficient patients available for a study and where to find them. Pursuing digital feasibility queries on available patient data registries has proven to be an excellent way of reusing existing real-world data sources. To support multicentric research, these feasibility queries should be designed and implemented to run across multiple sites and securely access local data. Working across hospitals usually involves working with different data formats and vocabularies. Recently, the Fast Healthcare Interoperability Resources (FHIR) standard was developed by Health Level Seven to address this concern and describe patient data in a standardized format. The Medical Informatics Initiative in Germany has committed to this standard and created data integration centers, which convert existing data into the FHIR format at each hospital. This partially solves the interoperability problem; however, a distributed feasibility query platform for the FHIR standard is still missing.ObjectiveThis study described the design and implementation of the components involved in creating a cross-hospital feasibility query platform for researchers based on FHIR resources. This effort was part of a large COVID-19 data exchange platform and was designed to be scalable for a broad range of patient data.MethodsWe analyzed and designed the abstract components necessary for a distributed feasibility query. This included a user interface for creating the query, backend with an ontology and terminology service, middleware for query distribution, and FHIR feasibility query execution service.ResultsWe implemented the components described in the Methods section. The resulting solution was distributed to 33 German university hospitals. The functionality of the comprehensive network infrastructure was demonstrated using a test data set based on the German Corona Consensus Data Set. A performance test using specifically created synthetic data revealed the applicability of our solution to data sets containing millions of FHIR resources. The solution can be easily deployed across hospitals and supports feasibility queries, combining multiple inclusion and exclusion criteria using standard Health Level Seven query languages such as Clinical Quality Language and FHIR Search. Developing a platform based on multiple microservices allowed us to create an extendable platform and support multiple Health Level Seven query languages and middleware components to allow integration with future directions of the Medical Informatics Initiative.ConclusionsWe designed and implemented a feasibility platform for distributed feasibility queries, which works directly on FHIR-formatted data and distributed it across 33 university hospitals in Germany. We showed that developing a feasibility platform directly on the FHIR standard is feasible.

Analysis and Implementation of Microservice Architecture Related to Patient Drug Schedule Based on FHIR Standard

In several previous studies, smart devices have been developed to help improve a patient's medication adherence but have problems, namely data management that is not centralized and not integrated, so that mitigation is quite vulnerable. In this study, a platform was built that can manage data centrally and apply the FHIR (Fast Healthcare Interoperability Resources) health data standard. The main components used to implement the FHIR standard are resources and REST APIs. The resource is a data model that defines the structure and data elements that are exchanged. This data exchange is carried out on top of the REST API using the HTTP protocol. Platform testing uses positive/negative testing and stress testing methods to be able to see the performance of the platform. The test results show that the platform prototype can provide a response that is in accordance with the request given and has a very tolerant error value of 0% with a latency value of 3 to 22 seconds with a total of 100 to 130 users.

ACTION-EHR: Patient-Centric Blockchain-Based Electronic Health Record Data Management for Cancer Care.

BackgroundWith increased specialization of health care services and high levels of patient mobility, accessing health care services across multiple hospitals or clinics has become very common for diagnosis and treatment, particularly for patients with chronic diseases such as cancer. With informed knowledge of a patient’s history, physicians can make prompt clinical decisions for smarter, safer, and more efficient care. However, due to the privacy and high sensitivity of electronic health records (EHR), most EHR data sharing still happens through fax or mail due to the lack of systematic infrastructure support for secure, trustable health data sharing, which can also cause major delays in patient care.ObjectiveOur goal was to develop a system that will facilitate secure, trustable management, sharing, and aggregation of EHR data. Our patient-centric system allows patients to manage their own health records across multiple hospitals. The system will ensure patient privacy protection and guarantee security with respect to the requirements for health care data management, including the access control policy specified by the patient.MethodsWe propose a permissioned blockchain-based system for EHR data sharing and integration. Each hospital will provide a blockchain node integrated with its own EHR system to form the blockchain network. A web-based interface will be used for patients and doctors to initiate EHR sharing transactions. We take a hybrid data management approach, where only management metadata will be stored on the chain. Actual EHR data, on the other hand, will be encrypted and stored off-chain in Health Insurance Portability and Accountability Act–compliant cloud-based storage. The system uses public key infrastructure–based asymmetric encryption and digital signatures to secure shared EHR data.ResultsIn collaboration with Stony Brook University Hospital, we developed ACTION-EHR, a system for patient-centric, blockchain-based EHR data sharing and management for patient care, in particular radiation treatment for cancer. The prototype was built on Hyperledger Fabric, an open-source, permissioned blockchain framework. Data sharing transactions were implemented using chaincode and exposed as representational state transfer application programming interfaces used for the web portal for patients and users. The HL7 Fast Healthcare Interoperability Resources standard was adopted to represent shared EHR data, making it easy to interface with hospital EHR systems and integrate a patient’s EHR data. We tested the system in a distributed environment at Stony Brook University using deidentified patient data.ConclusionsWe studied and developed the critical technology components to enable patient-centric, blockchain-based EHR sharing to support cancer care. The prototype demonstrated the feasibility of our approach as well as some of the major challenges. The next step will be a pilot study with health care providers in both the United States and Switzerland. Our work provides an exemplar testbed to build next-generation EHR sharing infrastructures.

A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

BackgroundMobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (EHR) data. Raw sensor data have no semantics of their own; therefore, a computer system cannot interpret these data automatically. In addition, the interoperability of sensor data and EHR medical data is a challenge. EHR data collected from distributed systems have different structures, semantics, and coding mechanisms. As a result, building a transparent CDSS that can work as a portable plug-and-play component in any existing EHR ecosystem requires a careful design process. Ontology and medical standards support the construction of semantically intelligent CDSSs.MethodsThis paper proposes a comprehensive MH framework with an integrated CDSS capability. This cloud-based system monitors and manages type 1 diabetes mellitus. The efficiency of any CDSS depends mainly on the quality of its knowledge and its semantic interoperability with different data sources. To this end, this paper concentrates on constructing a semantic CDSS based on proposed FASTO ontology.ResultsThis realistic ontology is able to collect, formalize, integrate, analyze, and manipulate all types of patient data. It provides patients with complete, personalized, and medically intuitive care plans, including insulin regimens, diets, exercises, and education sub-plans. These plans are based on the complete patient profile. In addition, the proposed CDSS provides real-time patient monitoring based on vital signs collected from patients’ wireless body area networks. These monitoring include real-time insulin adjustments, mealtime carbohydrate calculations, and exercise recommendations. FASTO integrates the well-known standards of HL7 fast healthcare interoperability resources (FHIR), semantic sensor network (SSN) ontology, basic formal ontology (BFO) 2.0, and clinical practice guidelines. The current version of FASTO includes 9577 classes, 658 object properties, 164 data properties, 460 individuals, and 140 SWRL rules. FASTO is publicly available through the National Center for Biomedical Ontology BioPortal at https://bioportal.bioontology.org/ontologies/FASTO.ConclusionsThe resulting CDSS system can help physicians to monitor more patients efficiently and accurately. In addition, patients in rural areas can depend on the system to manage their diabetes and emergencies.

A Pharmacogenomics Clinical Decision Support Service Based on FHIR and CDS Hooks.

Pharmacogenomics (PGx) is often considered a low-hanging fruit for genomics-electronic health record (EHR) integrations, and many have expressed the notion that drug-gene interaction checking might one day become as much a commodity in EHRs as drug-drug and drug-allergy checking. In addition, the U.S. Office of the National Coordinator has recognized the trend toward storing complete sequencing data outside the EHR in a Genomic Archiving and Communication System (GACS) and has emphasized the need for "pilots that test Fast Healthcare Interoperability Resources (FHIR) Genomics for GACS integration with EHRs." We sought to develop a PGx clinical decision support (CDS) service, leveraging the emerging FHIR and CDS Hooks standards, and based on an assumption that pharmacogene sequencing data would be stored alongside the EHR in a GACS. We developed a PGx CDS service as a functional prototype. The service is triggered by a medication order in the EHR. When evoked, the service looks for relevant genetic data in a GACS and returns corresponding recommendations back to the ordering clinician. Where the patient has no genetic data on file, the service can recommend pretreatment genetic testing where applicable. Overall, we were able to meet our objectives and deploy a functional prototype, interfaced with a commercial EHR. We identified several areas where FHIR or CDS Hooks lacked necessary semantics or have implementation ambiguity. Primary FHIR challenges included multiple ways to say the same thing, which exacerbated the complexity of variant to allele conversion and lack of representation of deoxyribonucleic acid region(s) studied. Primary CDS Hooks challenges included the complexity of executing an authenticated query against one system (GACS) upon being triggered by a different system (the EHR), and limitations in the types of actionable recommendations that can be returned to the EHR. In conclusion, we have found that PGx CDS based on FHIR and CDS Hooks appears to represent a promising means of genomics-EHR integration. More real-world testing along with a set of use-case driven GACS interface requirements will push us closer to the U.S. National Human Genome Research Institute vision of a plug-in PGx app.

RETRACTED ARTICLE: Securing e-health records using keyless signature infrastructure blockchain technology in the cloud

Health record maintenance and sharing are one of the essential tasks in the healthcare system. In this system, loss of confidentiality leads to a passive impact on the security of health record whereas loss of integrity leads can have a serious impact such as loss of a patient’s life. Therefore, it is of prime importance to secure electronic health records. Health records are represented by Fast Healthcare Interoperability Resources standards and managed by Health Level Seven International Healthcare Standards Organization. Centralized storage of health data is attractive to cyber-attacks and constant viewing of patient records is challenging. Therefore, it is necessary to design a system using the cloud that helps to ensure authentication and that also provides integrity to health records. The keyless signature infrastructure used in the proposed system for ensuring the secrecy of digital signatures also ensures aspects of authentication. Furthermore, data integrity is managed by the proposed blockchain technology. The performance of the proposed framework is evaluated by comparing the parameters like average time, size, and cost of data storage and retrieval of the blockchain technology with conventional data storage techniques. The results show that the response time of the proposed system with the blockchain technology is almost 50% shorter than the conventional techniques. Also they express the cost of storage is about 20% less for the system with blockchain in comparison with the existing techniques.

Validation and Testing of Fast Healthcare Interoperability Resources Standards Compliance: Data Analysis.

BackgroundThere is wide recognition that the lack of health data interoperability has significant impacts. Traditionally, health data standards are complex and test-driven methods played important roles in achieving interoperability. The Health Level Seven International (HL7) standard Fast Healthcare Interoperability Resources (FHIR) may be a technical solution that aligns with policy, but systems need to be validated and tested.ObjectiveOur objective is to explore the question of whether or not the regular use of validation and testing tools improves server compliance with the HL7 FHIR specification.MethodsWe used two independent validation and testing tools, Crucible and Touchstone, and analyzed the usage and result data to determine their impact on server compliance with the HL7 FHIR specification.ResultsThe use of validation and testing tools such as Crucible and Touchstone are strongly correlated with increased compliance and “practice makes perfect.” Frequent and thorough testing has clear implications for health data interoperability. Additional data analysis reveals trends over time with respect to vendors, use cases, and FHIR versions.ConclusionsValidation and testing tools can aid in the transition to an interoperable health care infrastructure. Developers that use testing and validation tools tend to produce more compliant FHIR implementations. When it comes to health data interoperability, “practice makes perfect.”

An Integrated Model to Capture the Provision of Health and Social Care Services Based on the ContSys and FHIR Standards

In the last decades, there is a shif in the provision of health services from the formal facilities to home care. The delivery of care at home is considered a sustainable approach that not only results in substantial cost savings but is also a key step towards achieving optimal outcomes in the delivery of high-quality health services. Moreover, the adoption of this approach is facilitated by the prompt development of medical and non-medical technologies that can simplify care coordination and enable distant monitoring of the patient. However, home care requires the integration and coordination of health and social stakeholders in a continuity of care perspective. This requires the adoption of standards to defi ne a common shared conceptual model that improves the interoperability among information systems and organizations. In this paper to accomplish this task we combine the ContSys standard and the HL7 FHIR (Fast Healthcare Interoperability Resources) framework to identify concepts to be exchanged between systems, organizations and providers involved in the health and social context. This model has been developed to improve the integration and coordination of social and health care services within the Italian H@H project.

Feasibility of Representing a Danish Microbiology Model Using FHIR.

Achieving interoperability in health is a challenge and requires standardization. The newly developed HL7 standard: Fast Healthcare Interoperability Resources (FHIR) promises both flexibility and interoperability. This study investigates the feasibility of expressing a Danish microbiology message model content in FHIR to explore whether complex in-use legacy models can be migrated and what challenges this may pose. The Danish microbiology message model (the DMM) is used as a case to illustrate challenges and opportunities accosted with applying the FHIR standard. Mapping of content from DMM to FHIR was done as close as possible to the DMM to minimize migration costs except when the structure of the content did not fit into FHIR. From the DMM a total of 183 elements were mapped to FHIR. 75 (40.9%) elements were modeled as existing FHIR elements and 96 (52.5%) elements were modeled as extensions and 12 (6.6%) elements were deemed unnecessary because of build-in FHIR characteristics. In this study, it was possible to represent the content of a Danish message model using HL7 FHIR.

Enabling Better Interoperability for HealthCare: Lessons in Developing a Standards Based Application Programing Interface for Electronic Medical Record Systems.

We sought to enable better interoperability and easy adoption of healthcare applications by developing a standardized domain independent Application Programming Interface (API) for an Electronic Medical Record (EMR) system. We leveraged the modular architecture of the Open Medical Record System (OpenMRS) to build a Fast Healthcare Interoperability Resources (FHIR) based add-on module that could consume FHIR resources and requests made on OpenMRS. The OpenMRS FHIR module supports a subset of FHIR resources that could be used to interact with clinical data persisted in OpenMRS. We demonstrate the ease of connecting healthcare applications using the FHIR API by integrating a third party Substitutable Medical Apps & Reusable Technology (SMART) application with OpenMRS via FHIR. The OpenMRS FHIR module is an optional component of the OpenMRS platform. The FHIR API significantly reduces the effort required to implement OpenMRS by preventing developers from having to learn or work with a domain specific OpenMRS API. We propose an integration pathway where the domain specific legacy OpenMRS API is gradually retired in favor of the new FHIR API, which would be integrated into the core OpenMRS platform. Our efforts indicate that a domain independent API is a reality for any EMR system. These efforts demonstrate the adoption of an emerging FHIR standard that is seen as a replacement for both Health Level 7 (HL7) Version 2 and Version 3. We propose a gradual integration approach where our FHIR API becomes the preferred method for communicating with the OpenMRS platform.