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Syntactic Interoperability and the Role of Standards
Abstract
To achieve interoperability among information systems in health care, industry stakeholders must develop and implement technical standards that facilitate seamless exchange of data. This chapter defines and describes the concept of health information messaging standards, or technical standards that provide the structure for moving data around in the health-care ecosystem. The chapter explains the role of standards as well as how standards are developed. The chapter further examines the components necessary to support the implementation and adoption of standards, including the need for integration profiles, implementation guides, and interface engines. Finally, the chapter considers emerging standards as well as initiatives that seek to further support broad adoption of standards in health care.
... This design choice was intentional and serves to enhance the algorithm's applicability across multiple healthcare settings and systems. Because many healthcare institutions use CDSSs or EHRs that produce log files in a similar format due to the fact of more standardization of data interoperability protocols e.g., HL7 [51], the algorithm can be readily applied without requiring extensive data transformation or pre-processing except a subject matter expert to check the relevant data columns. However, it's worth noting that this strength is a double-edged sword. ...
Background
Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process.
Methods
The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM’s different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset.
Results
The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard.
Conclusions
In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.
... It is widely recognized as the most commonly used standard process for managing and exchanging medical images. DICOM allows for the integration of diverse image types produced by medical imaging devices such as CBCT into picture archiving and communication systems that may be used by other applications in healthcare delivery [10]. ...
The COVID-19 pandemic had many new post-viral sequelae some of which are yet to be detected. In our case series, we are presenting five patients with different ages, medical backgrounds, and presentations, who were diagnosed with Post COVID-19 Graves’ disease at Royal Hospital from January to December of 2020. The main reason behind this case series is to highlight the variability of presentation and the duration between exposure to the virus and the presentation. In addition, due to the similarity in the presentation of some of the symptoms between COVID-19 infection and Graves' Disease, most of those patients were delayed in getting the proper diagnosis of COVID-19-induced Graves' disease. Hence, this case series can aid in alerting primary care doctors for early detection of such cases and regular follow-up, which can positively impact our national healthcare system.
... Technical interoperability pertains to the way data or information moves from one system or component to another. Related to this is syntactic interoperability, which provides a structure and syntax for the transmitted data [128]. Semantic interoperability refers to the ability of the recipient to understand and make use of the received data, whereas process interoperability concerns the way in which different systems are used in actual work settings. ...
In recent years, there has been an increased focus on early detection, prevention, and prediction of diseases. This, together with advances in sensor technology and the Internet of Things, has led to accelerated efforts in the development of personal health monitoring systems. Semantic technologies have emerged as an effective way to not only deal with the issue of interoperability associated with heterogeneous health sensor data, but also to represent expert health knowledge to support complex reasoning required for decision-making. This study evaluates the state of the art in the use of semantic technologies in sensor-based personal health monitoring systems. Using a systematic approach, a total of 40 systems representing the state of the art in the field are analysed. Through this analysis, six key challenges that such systems must overcome for optimal and effective health monitoring are identified: interoperability, context awareness, situation detection, situation prediction, decision support, and uncertainty handling. The study critically evaluates the extent to which these systems incorporate semantic technologies to deal with these challenges and identifies the prominent architectures, system development and evaluation methodologies that are used. The study provides a comprehensive mapping of the field, identifies inadequacies in the state of the art, and provides recommendations for future research directions.
... The HIE standards aspect defines syntax and structure to operationalize data exchange and have robust and interoperable solutions. Interoperability standards in eHealth are broadly categorized as organizational (process, procedures and alignment), syntactic (structure, content and services), semantic (vocabulary, code sets, terminology), and foundational/technical (transport) interoperability [14]. Together, these standards facilitate a secure, seamless, and timely communication and use of data both within and between countries, organizations, entities and individuals. ...
Lack of interoperability and integration between heterogeneous health systems is a big challenge to realize the potential benefits of eHealth. To best move from siloed applications to interoperable eHealth solutions, health information exchange (HIE) policy and standards are necessary to be established. However, there is no comprehensive evidence on the current status of HIE policy and standards on the African continent. Therefore, this paper aimed to systematically review the status of HIE policy and standards which are currently in practice in Africa. A systematic search of the literature was conducted from Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and Excerpta Medica Database (EMBASE), and a total of 32 papers (21 strategic documents and 11 peer-reviewed papers) were selected based on predefined criteria for synthesis. Results revealed that African countries have paid attention to the development, improvement , adoption, and implementation of HIE architecture for interoperability and standards. Synthetic and semantic interoperability standards were identified for the implementation of HIE in Africa. Based on this comprehensive review, we recommend that comprehensive interoperable technical standards should be set at each national level and should be guided by appropriate governance and legal frameworks, data ownership and use agreements, and health data privacy and security guidelines. On top of the policy issues, there is a need to identify a set of standards (health system standards, communication, messaging standards, terminology/vocabulary standards, patient profile standards, privacy and security, and risk assessment) and implement them throughout all levels of the health system. On top of this, we recommend that the Africa Union (AU) and regional bodies provide the necessary human resource and high-level technical support to African countries to implement HIE policy and standards. To realize the full potential of eHealth in the continent, it is recommended that African countries need to have a common HIE policy, interoperable technical standards, and health data privacy and security guidelines. Currently, there is an ongoing effort by the PLOS DIGITAL HEALTH PLOS Digital Health | https://doi.org/10.1371/journal.pdig. on the continent. A task force has been established from Africa CDC, Health Information Service Provider (HISP) partners, and African and global HIE subject matter experts to provide expertise and guidance in the development of AU policy and standards for HIE. Although the work is still ongoing, the African Union shall continue to support the implementation of HIE policy and standards in the continent. The authors of this review are currently working under the umbrella of the African Union to develop the HIE policy and standard to be endorsed by the head of states of the Africa Union. As a follow-up publication to this, the result will be published in mid-2022. Author summary With the increased deployment of digital health technologies in healthcare settings across the globe, Health Information Exchange (HIE) is getting increasing attention. This is because it helps healthcare organizations to interchange data, especially at times of pandemics and improves patient safety, efficiency, cost-effectiveness, and quality of health care delivery. However, there is limited evidence on the level of adoption and deployment of HIE systems in many middle-and low-income countries including Africa. In this review paper, we summarized the available evidence and provide comprehensive evidence on the level of HIE adoption in Africa. We found that many African countries outlined several initiatives to develop and integrate digital health systems in their strategic documents. They have also proposed the development, improvement, adoption, and implementation of HIE architecture, interoperability, and standards for HIE. Based on the summary of this evidence, the team worked with Africa CDC to develop an African Union (AU) HIE Policy and Standards document to guide the development of HIE in Africa. In the future, we aim to publish the AU HIE Policy and Standards recommendation document as a follow-up paper that can be used by policymakers as well as researchers.
... Digital Imaging and Communications in Medicine (DICOM) was developed by the American College of Radiology and the National Electrical Manufacturers' Association [57], in order to use fully digital images with high resolution instead of physical Xray films [58]. ...
... The HIE standards aspect defines syntax and structure to operationalize data exchange and have robust and interoperable solutions. Interoperability standards in eHealth are broadly categorized as organizational (process, procedures and alignment), syntactic (structure, content and services), semantic (vocabulary, code sets, terminology), and foundational/technical (transport) interoperability [14]. Together, these standards facilitate a secure, seamless, and timely communication and use of data both within and between countries, organizations, entities and individuals. ...
Lack of interoperability and integration between heterogeneous health systems is a big challenge to realize the potential benefits of eHealth. To best move from siloed applications to interoperable eHealth solutions, health information exchange (HIE) policy and standards are necessary to be established. However, there is no comprehensive evidence on the current status of HIE policy and standards on the African continent. Therefore, this paper aimed to systematically review the status of HIE policy and standards which are currently in practice in Africa. A systematic search of the literature was conducted from Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and Excerpta Medica Database (EMBASE), and a total of 32 papers (21 strategic documents and 11 peer-reviewed papers) were selected based on predefined criteria for synthesis. Results revealed that African countries have paid attention to the development, improvement , adoption, and implementation of HIE architecture for interoperability and standards. Synthetic and semantic interoperability standards were identified for the implementation of HIE in Africa. Based on this comprehensive review, we recommend that comprehensive interoperable technical standards should be set at each national level and should be guided by appropriate governance and legal frameworks, data ownership and use agreements, and health data privacy and security guidelines. On top of the policy issues, there is a need to identify a set of standards (health system standards, communication, messaging standards, terminology/vocabulary standards, patient profile standards, privacy and security, and risk assessment) and implement them throughout all levels of the health system. On top of this, we recommend that the Africa Union (AU) and regional bodies provide the necessary human resource and high-level technical support to African countries to implement HIE policy and standards. To realize the full potential of eHealth in the continent, it is recommended that African countries need to have a common HIE policy, interoperable technical standards, and health data privacy and security guidelines. Currently, there is an ongoing effort by the PLOS DIGITAL HEALTH PLOS Digital Health | https://doi.org/10.1371/journal.pdig. on the continent. A task force has been established from Africa CDC, Health Information Service Provider (HISP) partners, and African and global HIE subject matter experts to provide expertise and guidance in the development of AU policy and standards for HIE. Although the work is still ongoing, the African Union shall continue to support the implementation of HIE policy and standards in the continent. The authors of this review are currently working under the umbrella of the African Union to develop the HIE policy and standard to be endorsed by the head of states of the Africa Union. As a follow-up publication to this, the result will be published in mid-2022. Author summary With the increased deployment of digital health technologies in healthcare settings across the globe, Health Information Exchange (HIE) is getting increasing attention. This is because it helps healthcare organizations to interchange data, especially at times of pandemics and improves patient safety, efficiency, cost-effectiveness, and quality of health care delivery. However, there is limited evidence on the level of adoption and deployment of HIE systems in many middle-and low-income countries including Africa. In this review paper, we summarized the available evidence and provide comprehensive evidence on the level of HIE adoption in Africa. We found that many African countries outlined several initiatives to develop and integrate digital health systems in their strategic documents. They have also proposed the development, improvement, adoption, and implementation of HIE architecture, interoperability, and standards for HIE. Based on the summary of this evidence, the team worked with Africa CDC to develop an African Union (AU) HIE Policy and Standards document to guide the development of HIE in Africa. In the future, we aim to publish the AU HIE Policy and Standards recommendation document as a follow-up paper that can be used by policymakers as well as researchers.
... Further below are three key data-centric activities that include computer simulations, various forms of research (including some forms of instrumentation that is datadense, e.g., X-ray based tomographic imaging) and data analytics (including artificial intelligence and machine learning). Between the application layer and the data layer is the explicit planning and implementation of interoperability, which includes data interoperability, ICT interoperability and cross-domain interoperability (Hosseini and Dixon, 2016; e.g., for geographical information systems data, see ESRI 2020). This layer exists as an explicit consideration in our modern model to ensure that the data is usable by data consumers and that the systems are cross-usable between top-level and low-level functions. ...
The world continues to experience a surge in data generation and digital transformation. Historic data is increasingly being replaced by modernized data, such as big data, which is regarded as data that exhibits the 5Vs: volume, variety, velocity, veracity and value. The capacity to optimally use and comprehend value from big data has become an indispensable aptitude for modern companies. In contrast to commercial and technology firms, usage, management and governance of data, including big data is a novel and evolving trend for mining and mineral industries. Although the mining industry can be unenthusiastic to change, embracing modernized data and big data is evolutionarily unavoidable, given many industry-wide challenges (i.e., fluctuation in commodity prices, geotechnical and harsh ground conditions, and ore grade), which corrode revenues and increase business risks, including the possibility of regulatory non-compliance. The minerals industry holds a genuine gold mine of data that were collected for scientific, engineering, operational and other purposes. Data and data-centric workspaces that are targeted towards innovation and experimentation, which if combined with in-discipline expertise are two harmonious ingredients that can provide many practical solutions for the mining and mineral industries. In this paper, the concept, the opportunity and the necessity for a move towards a technology-and innovation-based, data-centric 'dry laboratories' (common workspaces that facilitates data-centric experimentation and innovation) in the minerals industry are assessed. We contend that the dry laboratory environment maximizes the value of data for the minerals industry. Toward the establishment of dry laboratories, we propose several essential components of a framework that would enable the functionality of dry laboratories in the minerals industry, while concomitantly examining the components from both academia and industry perspectives.
... There should be coordination around a standardized data format to reduce duplication among implementing partners, especially for individualized data-based solutions. Data-intensive digital health solutions should improve the feedback loop and data use, especially at health facility levels [13]. License-free individualized data sharing standards such as the Fast Healthcare Interoperability Resource should be explored [14]. ...
Background:
The government and partners have invested heavily in the health information system (HIS) for service delivery, surveillance, reporting, and monitoring. Sierra Leone’s government launched its first digital health strategy in 2018. In 2019, a broader national innovation and digital strategy was launched. The health pillar direction will use big data and artificial intelligence (AI) to improve health care in general and maternal and child health in particular. Understanding the number, distribution, and interoperability of digital health solutions is crucial for successful implementation strategies.
Objective:
This paper presents the state of digital health solutions in Sierra Leone and how these solutions currently interoperate. This study further presents opportunities for big data and AI applications.
Methods:
All the district health management teams, all digital health implementing organizations, and a stratified sample of 72 (out of 1284) health facilities were purposefully selected from all health districts and surveyed.
Results:
The National Health Management Information System’s (NHMIS’s) aggregate reporting solution populated by health facility forms HF1 to HF9 was, by far, the most used tool. A health facility–based weekly aggregate electronic integrated disease surveillance and response solution was also widely used. Half of the health facilities had more than 2 digital health solutions in use. The different digital health software solutions do not share data among one another, though aggregate reporting data were sent as necessary. None of the respondents use any of the health care registries for patient, provider, health facility, or terminology identification.
Conclusions:
Many digital health solutions are currently used at health facilities in Sierra Leone. The government can leverage current investment in HIS from surveillance and reporting for using big data and AI for care. The vision of using big data for health care is achievable if stakeholders prioritize individualized and longitudinal patient data exchange using agreed use cases from national strategies. This study has shown evidence of distribution, types, and scale of digital health solutions in health facilities and opportunities for leveraging big data to fill critical gaps necessary to achieve the national digital health vision.
... Other times HIE involves querying (or pulling) information from another system, such as the transmission of a summary of care record using the HL7 Consolidated Document Architecture (CDA) standard outlined in meaningful use (now referred to as Promoting Interoperability) criteria for Medicare and Medicaid providers. [7][8][9] Event notification is a form of HIE involving the electronic reporting (or pushing) of information pertaining to a clinical event from 1 provider to another facilitated by a messaging standard. Notification usually pertains to acute care events (eg, hospitalization, emergency care), and the notifications are typically sent to primary care providers responsible for coordination of care. ...
Objective
To examine the effectiveness of event notification service (ENS) alerts on health care delivery processes and outcomes for older adults.
Materials and methods
We deployed ENS alerts in 2 Veterans Affairs (VA) medical centers using regional health information exchange (HIE) networks from March 2016 to December 2019. Alerts targeted VA-based primary care teams when older patients (aged 65+ years) were hospitalized or attended emergency departments (ED) outside the VA system. We employed a concurrent cohort study to compare postdischarge outcomes between patients whose providers received ENS alerts and those that did not (usual care). Outcome measures included: timely follow-up postdischarge (actual phone call within 7 days or an in-person primary care visit within 30 days) and all-cause inpatient or ED readmission within 30 days. Generalized linear mixed models, accounting for clustering by primary care team, were used to compare outcomes between groups.
Results
Compared to usual care, veterans whose primary care team received notification of non-VA acute care encounters were 4 times more likely to have phone contact within 7 days (AOR = 4.10, P < .001) and 2 times more likely to have an in-person visit within 30 days (AOR = 1.98, P = .007). There were no significant differences between groups in hospital or ED utilization within 30 days of index discharge (P = .057).
Discussion
ENS was associated with increased timely follow-up following non-VA acute care events, but there was no associated change in 30-day readmission rates. Optimization of ENS processes may be required to scale use and impact across health systems.
Conclusion
Given the importance of ENS to the VA and other health systems, this study provides guidance for future research on ENS for improving care coordination and population outcomes.
Trial Registration
ClinicalTrials.gov NCT02689076. “Regional Data Exchange to Improve Care for Veterans After Non-VA Hospitalization.” Registered February 23, 2016.
... Digital Imaging and Communication in Medicine (DICOM) [1] is a standard to exchange medical images and their information in the hospital's picture archiving and communication system (PACS), which is used in querying, storing, printing, and transmitting information in imaging. Therefore, digital images can be generated by different medical devices and can also be integrated into the PACS [2][3]. Each DICOM file contains patient profiles (privacy information and clinical diagnosis records), origin site, and image attribute (pixel size) [4]. ...
Medical images can be constructed in two-dimensional (2D) or three-dimensional (3D) view imaging to be applied in disease detection and diagnosis inside the body, such as cancer/tumor, heart, or lung-related diseases. These images may contain patients’ privacy information and clinical diagnosis records. Hence, these images need to ensure authorization demands among hospitals, medical service organizations, or physicians in a picture archiving and communication system. This study presents an intelligent symmetric cryptography with a chaotic map and quantum-based key generator (KG) for medical image encryption and decryption. Overall scheme processes include (1) random cipher code generation, (2) training gray relational analysis (GRA)-based encryptor and decryptor, and (3) decrypted image evaluation. The hybrid chaotic map and quantum-based KG are used to increase the chaotic complexity and unpredictable levels to produce cipher codes for changing pixel values (substitution method) in a 2D image by 256 key-space cipher codes. The first and second GRA models are used to train the cipher codes to achieve an encryptor and a decryptor, respectively. Through the methodology validation using a chest X-ray database, the structural similarity index measurement is employed to evaluate the decryption quality between the plain image and decrypted image. The encrypted images show a visual uncorrelation with the plain images, and experimental results indicate higher confidences against the passive eavesdropper.
... • Semantic Interoperability [55]: This criterion shows if the platform supports can exchange data with shared meaning. ...
Internet of Things (IoT) is a set of technologies that aim at fitting together smart devices and applications to build an IoT ecosystem. The target of this kind of ecosystem is to enhance interaction between machines and humans through hardware to software binding while reducing cost and resource consumption. On the application level, IoT ecosystems were implemented by various technologies that all seek better interconnection, monitoring, and controlling of IoT smart devices. Among recent technologies, Microservices, which are a variant of the service-oriented architecture, are subject to great excitement. In fact, Microservices are an emerging technology built around Microservice paradigm which goal is to offer services with a small granularity, which exactly meets the distributed nature of IoT devices while maintaining a loosely coupled architecture between IoT components among other advantages. Efforts to build Microservice-based IoT platforms sooner emerged to take advantage of the numerous benefits of the Microservice paradigm to build scalable, interoperable, and dynamic ecosystems. The goal of this paper is to list these approaches, classify them and compare them using a Weighted Scoring Model (WSM) method. This involves, studying these platforms, establishing relevant criteria for comparison, assigning weights for each criterion, and finally calculating scores. The obtained results reveal the weaknesses and strengths of each of the studied platforms.
The last decade has seen the rise of innovations such as smart computers, wearable devices, smartphones, digital cameras, robots, social media networks, and ICT advancements in day-to-day life, leading to the digitization of numerous activities. Advances in trending technologies have contributed to their adaptation in every part of human’s daily routine. Almost all healthcare-associated domains are now adapting to eHealth. Health professionals have been able to collect medical records, exchange medical data through a network of professionals and patients, provide healthcare through digital media, and track various health-related events, diseases, and disease outbreaks through a range of technologies, such as social media sites, applications, smartphones, and smart objects. This has resulted in an ample amount of knowledge related to patients that is created and needs to be handled effectively for better results. Although big data is the obvious option to handle this vast data collection, data protection and security for public health data is a prime concern. A blockchain is known as a record database located in a distributed personal computer network called nodes. In particular, it is a mutual, permanent record of peer-to-peer transactions constructed from linked blocks of transactions and stored in a digital ledger. No single person owns it, i.e., it is decentralized. The healthcare sector is one of the sectors looking to embrace the blockchain. This chapter aims to reflect the numerous facts leading to the introduction of blockchain technology in general and electronic medical record management of healthcare in particular. The chapter will study the various blockchain implementation frameworks.
Purchases are concurrently safe and secure as well as credible because of making use of cryptographic guidelines. Recently, blockchain technology has become extremely cool and trendy and infiltrated various domain names, usually as a result of the appeal of cryptocurrencies. One field where blockchain technology possesses significant ability is medical care, because of the requirement for an extra patient-centric method to medical care systems and to link inconsonant devices and also boost the reliability of digital medical care files (EHRs). In this organized review, an analysis of cutting edge blockchain research study in the field of health care is carried out. It's own' prospective in the multi-stakeholder operated market like health and wellness has been responsible for several expenditures, researches, and executions. Electronic Health Records (EHR) devices typically made use of for the swap of wellness details amongst healthcare stakeholders have been criticised for centralising energy, failures and attack-points along with exchange records protectors. EHRs have battled when faced with multi-stakeholder as well as unit criteria while adhering to safety and security, privacy, reliable as well as other regulative constraints. Blockchain is promising among others to attend to the many EHR challenges, largely trustless and also protected swap of health-relevant information among stakeholders. This paper provides the demand for blockchain in medical care and also blockchain-based EHR device architecture.
Blockchain, a form of distributed ledger technology has attracted the interests of stakeholders across several sectors including healthcare. Its’ potential in the multi-stakeholder operated sector like health has been responsible for several investments, studies, and implementations. Electronic Health Records (EHR) systems traditionally used for the exchange of health information amongst healthcare stakeholders have been criticised for centralising power, failures and attack-points with exchange data custodians. EHRs have struggled in the face of multi-stakeholder and system requirements while adhering to security, privacy, ethical and other regulatory constraints. Blockchain is promising amongst others to address the many EHR challenges, primarily trustless and secure exchange of health information amongst stakeholders. Many blockchain-in-healthcare frameworks have been proposed; some prototyped and/or implemented. This study leveraged the PRISMA framework to systematically search and evaluate the different models proposed; prototyped and/or implemented. The bibliometric and functional distribution of all 143 articles from this study were presented. This study evaluated 61 articles that discussed either prototypes or pilot or implementations. The technical and architectural analysis of these 61 articles for privacy, security, cost, and performance were detailed. Blockchain was found to solve the trust, security and privacy constraints of traditional EHRs often at significant performance, storage and cost trade-offs.
Interoperability between public administrations was recognized by the European Commission (EC) with the launch of the Interchange of Data between Administrations (IDA). In 2004 the first version of the European Interoperability Framework for pan-European eGovernment Services EIF V1.0 was published followed by EIF V2.0 in 2010 and in 2017 the New EIF. This paper initially presents a summary in the landscape of interoperability, specifically a brief study on the EIF, NIFs (National Interoperability Frameworks), ISA and ISA ² (interoperability solutions for public administrations, businesses and citizens) programmes with focus on the EIF and its implementation in MS’ (member states) NIFs. How NIFs are currently utilized and what is beyond after the alignment or implementation with EIF. The description starts with some basic definitions and a review on the status of current EIF and NIFs in European countries and in several non-European countries. According to the New EIF’s principles, layers, recommendations and model a comparison is made so as to recognize major commonalities and significant differences between EIFs and principles in the NIFs. The contribution after comparison and identification of gaps provides a short summary of outcomes, recommendations and new directions mainly in relation to the outburst of current trends.
The aims and scope of the second edition are unchanged from the first edition. The major market is in health informatics education. The three part format, which covers principles of health interoperability, HL7 and interchange formats, and SNOMED CT and clinical terminology, works well. In the US, The ONC (Office of the National Coordinator for Health Information Technology) has estimated that the HITECH stimulus will create more than 50,000 new jobs for health informatics professionals, who need to be educated.