A Nationwide Chronic Disease Management Solution via Clinical Decision Support Services: Software Development and Real-Life Implementation Report.

BACKGROUND: The increasing population of older adults has led to a rise in the demand for health care services, with chronic diseases being a major burden. Person-centered integrated care is required to address these challenges; hence, the Turkish Ministry of Health has initiated strategies to implement an integrated health care model for chronic disease management. We aim to present the design, development, nationwide implementation, and initial performance results of the national Disease Management Platform (DMP). OBJECTIVE: This paper's objective is to present the design decisions taken and technical solutions provided to ensure successful nationwide implementation by addressing several challenges, including interoperability with existing IT systems, integration with clinical workflow, enabling transition of care, ease of use by health care professionals, scalability, high performance, and adaptability. METHODS: The DMP is implemented as an integrated care solution that heavily uses clinical decision support services to coordinate effective screening and management of chronic diseases in adherence to evidence-based clinical guidelines and, hence, to increase the quality of health care delivery. The DMP is designed and implemented to be easily integrated with the existing regional and national health IT systems via conformance to international health IT standards, such as Health Level Seven Fast Healthcare Interoperability Resources. A repeatable cocreation strategy has been used to design and develop new disease modules to ensure extensibility while ensuring ease of use and seamless integration into the regular clinical workflow during patient encounters. The DMP is horizontally scalable in case of high load to ensure high performance. RESULTS: As of September 2023, the DMP has been used by 25,568 health professionals to perform 73,715,269 encounters for 16,058,904 unique citizens. It has been used to screen and monitor chronic diseases such as obesity, cardiovascular risk, diabetes, and hypertension, resulting in the diagnosis of 3,545,573 patients with obesity, 534,423 patients with high cardiovascular risk, 490,346 patients with diabetes, and 144,768 patients with hypertension. CONCLUSIONS: It has been demonstrated that the platform can scale horizontally and efficiently provides services to thousands of family medicine practitioners without performance problems. The system seamlessly interoperates with existing health IT solutions and runs as a part of the clinical workflow of physicians at the point of care. By automatically accessing and processing patient data from various sources to provide personalized care plan guidance, it maximizes the effect of evidence-based decision support services by seamless integration with point-of-care electronic health record systems. As the system is built on international code systems and standards, adaptation and deployment to additional regional and national settings become easily possible. The nationwide DMP as an integrated care solution has been operational since January 2020, coordinating effective screening and management of chronic diseases in adherence to evidence-based clinical guidelines.

Providing semantic interoperability between clinical care and clinical research domains.

Improving the efficiency with which clinical research studies are conducted can lead to faster medication innovation and decreased time to market for new drugs. To increase this efficiency, the parties involved in a regulated clinical research study, namely, the sponsor, the clinical investigator and the regulatory body, each with their own software applications, need to exchange data seamlessly. However, currently, the clinical research and the clinical care domains are quite disconnected because each use different standards and terminology systems. In this article, we describe an initial implementation of the Semantic Framework developed within the scope of SALUS project to achieve interoperability between the clinical research and the clinical care domains. In our Semantic Framework, the core ontology developed for semantic mediation is based on the shared conceptual model of both of these domains provided by the BRIDG initiative. The core ontology is then aligned with the extracted semantic models of the existing clinical care and research standards as well as with the ontological representations of the terminology systems to create a model of meaning for enabling semantic mediation. Although SALUS is a research and development effort rather than a product, the current SALUS knowledge base contains around 4.7 million triples representing BRIDG DAM, HL7 CDA model, CDISC standards and several terminology ontologies. In order to keep the reasoning process within acceptable limits without sacrificing the quality of mediation, we took an engineering approach by developing a number of heuristic mechanisms. The results indicate that it is possible to build a robust and scalable semantic framework with a solid theoretical foundation for achieving interoperability between the clinical research and clinical care domains.

Interoperability of medical device information and the clinical applications: an HL7 RMIM based on the ISO/IEEE 11073 DIM.

Medical devices are essential to the practice of modern healthcare services. Their benefits will increase if clinical software applications can seamlessly acquire the medical device data. The need to represent medical device observations in a format that can be consumable by clinical applications has already been recognized by the industry. Yet, the solutions proposed involve bilateral mappings from the ISO/IEEE 11073 Domain Information Model (DIM) to specific message or document standards. Considering that there are many different types of clinical applications such as the electronic health record and the personal health record systems, the clinical workflows, and the clinical decision support systems each conforming to different standard interfaces, detailing a mapping mechanism for every one of them introduces significant work and, thus, limits the potential health benefits of medical devices. In this paper, to facilitate the interoperability of clinical applications and the medical device data, we use the ISO/IEEE 11073 DIM to derive an HL7 v3 Refined Message Information Model (RMIM) of the medical device domain from the HL7 v3 Reference Information Mode (RIM). This makes it possible to trace the medical device data back to a standard common denominator, that is, HL7 v3 RIM from which all the other medical domains under HL7 v3 are derived. Hence, once the medical device data are obtained in the RMIM format, it can easily be transformed into HL7-based standard interfaces through XML transformations because these interfaces all have their building blocks from the same RIM. To demonstrate this, we provide the mappings from the developed RMIM to some of the widely used HL7 v3-based standard interfaces.

Guideline-driven telemonitoring and follow-up of cardiovascular implantable electronic devices using IEEE 11073, HL7 & IHE profiles.

For patients with Cardiovascular Implantable Electronic Devices (CIEDs), telemonitoring promises improved quality of life and safety, since events recorded by the device or observed by the patient can alert a health professional. Taking into account the latest clinical guidelines when responding to such alerts, is a topic of active research addressed by the iCARDEA project. A key technical challenge is correlating telemonitoring CIED report data in a vendor-independent format with Electronic Health Record (EHR) data collected in the hospital and Personal Health Record (PHR) data entered by the patient, in guideline-driven care processes. The iCARDEA CIED exposure service component presented in this paper employs standards specifications from ISO/IEEE 11073 (Health Informatics, Point-of-care Medical Device Communication) and HL7v2.x in the context of Integrating the Healthcare Enterprise (IHE) profiles to deliver telemonitoring CIED report data from two different CIED vendors to the adaptive care planner that implements guideline-driven care plans. Experience gained with implementation and initial component testing is discussed, while challenges and expectations for future health information standards to effectively support EHR-integrated guide-line-driven telemonitoring services are highlighted.

Providing interoperability of eHealth communities through peer-to-peer networks.

Providing an interoperability infrastructure for Electronic Healthcare Records (EHRs) is on the agenda of many national and regional eHealth initiatives. Two important integration profiles have been specified for this purpose, namely, the "Integrating the Healthcare Enterprise (IHE) Cross-enterprise Document Sharing (XDS)" and the "IHE Cross Community Access (XCA)." IHE XDS describes how to share EHRs in a community of healthcare enterprises and IHE XCA describes how EHRs are shared across communities. However, the current version of the IHE XCA integration profile does not address some of the important challenges of cross-community exchange environments. The first challenge is scalability. If every community that joins the network needs to connect to every other community, i.e., a pure peer-to-peer network, this solution will not scale. Furthermore, each community may use a different coding vocabulary for the same metadata attribute, in which case, the target community cannot interpret the query involving such an attribute. Yet another important challenge is that each community may (and typically will) have a different patient identifier domain. Querying for the patient identifiers in the target community using patient demographic data may create patient privacy concerns. In this paper, we address each of these challenges and show how they can be handled effectively in a superpeer-based peer-to-peer architecture.

Achieving clinical statement interoperability using R-MIM and archetype-based semantic transformations.

Effective use of electronic healthcare records (EHRs) has the potential to positively influence both the quality and the cost of health care. Consequently, sharing patient's EHRs is becoming a global priority in the healthcare information technology domain. This paper addresses the interoperability of EHR structure and content. It describes how two different EHR standards derived from the same reference information model (RIM) can be mapped to each other by using archetypes, refined message information model (R-MIM) derivations, and semantic tools. It is also demonstrated that well-defined R-MIM derivation rules help tracing the class properties back to their origins when the R-MIMs of two EHR standards are derived from the same RIM. Using well-defined rules also enable finding equivalences in the properties of the source and target EHRs. Yet an R-MIM still defines the concepts at the generic level. Archetypes (or templates), on the other hand, constrain an R-MIM to domain-specific concepts, and hence, provide finer granularity semantics. Therefore, while mapping clinical statements between EHRs, we also make use of the archetype semantics. Derivation statements are inferred from the Web Ontology Language definitions of the RIM, the R-MIMs, and the archetypes. Finally, we show how to transform Health Level Seven clinical statement instances to EHRcom clinical statement instances and vice versa by using the generated mapping definitions.

An interoperability test framework for HL7-based systems.

Health Level Seven (HL7) is a prominent messaging standard in the eHealth domain, and with HL7 v2, it addresses only the messaging layer. However, HL7 implementations also deal with the other layers of interoperability, namely the business process layer and the communication layer. This need is addressed in HL7 v3 by providing a number of normative transport specification profiles. Furthermore, there are storyboards describing HL7 v3 message choreographies between specific roles in specific events. Having alternative transport protocols and descriptive message choreographies introduces great flexibility in implementing HL7 standards, yet, this brings in the need for test frameworks that can accommodate different protocols and permit the dynamic definition of test scenarios. In this paper, we describe a complete test execution framework for HL7-based systems that provides high-level constructs allowing dynamic set up of test scenarios involving all the layers in the interoperability stack. The computer-interpretable test description language developed offers a configurable system with pluggable adaptors. The Web-based GUIs make it possible to test systems over the Web anytime, anywhere, and with any party willing to do so.

A semantically enriched clinical guideline model enabling deployment in heterogeneous healthcare environments.

Clinical guidelines are developed to assist healthcare practitioners to make decisions on patient's medical problems, and as such they communicate with external applications to retrieve patient data to initiate medical actions through clinical workflows, and transmit information to alert/reminder systems. The interoperability problems in the healthcare information technology domain prevent wider deployment of clinical guidelines because each deployment requires a tedious custom adaptation phase. In this paper, we provide machine-processable mechanisms that express the semantics of clinical guideline interfaces so that automated processes can be used to access the clinical resources for guideline deployment and execution. To be able to deploy the semantically extended guidelines to healthcare settings semiautomatically, the underlying application's semantics must also be available. We describe how this can be achieved based on two prominent implementation technologies in use in the eHealth domain: integrating healthcare enterprise cross-enterprise document sharing integration profile for discovering and exchanging electronic healthcare records and Web service technology for interacting with the clinical workflows and wireless medical sensor devices. The system described in this paper is realized within the scope of the SAPHIRE Project.

Collaborative business process support in eHealth: integrating IHE profiles through ebXML business process specification language.

Integrating healthcare enterprise (IHE) specifies integration profiles describing selected real world use cases to facilitate the interoperability of healthcare information resources. While realizing a complex real-world scenario, IHE profiles are combined by grouping the related IHE actors. Grouping IHE actors implies that the associated business processes (IHE profiles) that the actors are involved must be combined, that is, the choreography of the resulting collaborative business process must be determined by deciding on the execution sequence of transactions coming from different profiles. There are many IHE profiles and each user or vendor may support a different set of IHE profiles that fits to its business need. However, determining the precedence of all the involved transactions manually for each possible combination of the profiles is a very tedious task. In this paper, we describe how to obtain the overall business process automatically when IHE actors are grouped. For this purpose, we represent the IHE profiles through a standard, machine-processable language, namely, Organization for the Advancement of Structured Information Standards (OASIS) ebusiness eXtensible Markup Language (ebXML) Business Process Specification (ebBP) Language. We define the precedence rules among the transactions of the IHE profiles, again, in a machine-processable way. Then, through a graphical tool, we allow users to select the actors to be grouped and automatically produce the overall business process in a machine-processable format.

Enhancing IHE XDS for federated clinical affinity domain support.

One of the key problems in healthcare informatics is the inability to share patient records across enterprises. To address this problem, an important industry initiative called "integrating the healthcare enterprise (IHE)" specified the "cross enterprise document sharing (XDS)" profile. In the IHE XDS, healthcare enterprises that agree to work together form a "clinical affinity domain" and store healthcare documents in an ebXML registry/repository architecture to facilitate their sharing. The affinity domains also agree on a common set of policies such as coding lists to be used to annotate clinical documents in the registry/repository and the common schemes for patient identification. However, since patients expect their records to follow them as they move from one clinical affinity domain to another, there is a need for affinity domains to be federated to enable information exchange. In this paper, we describe how IHE XDS can be enhanced to support federated clinical affinity domains. We demonstrate that federation of affinity domains are facilitated when ontologies, rather than coding term lists, are used to annotate clinical documents. Furthermore, we describe a patient identification protocol that eliminates the need to keep a master patient index file for the federation.

A secure semantic interoperability infrastructure for inter-enterprise sharing of electronic healthcare records.

Healthcare professionals need access to accurate and complete healthcare records for effective assessment, diagnosis and treatment of patients. The non-interoperability of healthcare information systems means that interenterprise access to a patient's history over many distributed encounters is difficult to achieve. The ARTEMIS project has developed a secure semantic web service infrastructure for the interoperability of healthcare information systems. Healthcare professionals share services and medical information using a web service annotation and mediation environment based on functional and clinical semantics derived from healthcare standards. Healthcare professionals discover medical information about individuals using a patient identification protocol based on pseudonymous information. The management of care pathways and access to medical information is based on a well-defined business process allowing healthcare providers to negotiate collaboration and data access agreements within the context of strict legislative frameworks.