Interoperable Information Research Articles

Development and implementation of a guideline-based decision support system for etiological diagnosis of Sustained Monomorphic Ventricular Tachycardia (SMVT)

Abstract Background Guideline (GL)-based decision support systems (DSSs) play a significant role in supporting physicians in their decision-making processes by providing structured clinical guidance. While these systems have shown significant success in enhancing practitioner performance and patient outcomes in general practice, their application in the context of ventricular arrhythmias remains limited. Moreover, the clinical etiological diagnosis of ventricular arrhythmias presents various challenges for healthcare professionals, such as adherence to updated diagnostic criteria and understanding of complex arrhythmia mechanisms. Purpose In this study, we aim to design, implement, and evaluate a guideline-based decision support systems for etiological diagnosis of sustained monomorphic ventricular tachycardia (SMVT), which could potentially address critical challenges associated with the disease diagnosis and management. Methods To comprehensively capture the semantics embedded in clinical guidelines, we first developed a dedicated knowledge graph tailored to the clinical decision-making. This involved extracting entities and relationships pertinent to key decision procedures from ESC guidelines for ventricular arrhythmias, clinical textbooks or literatures. Subsequently, we translated instances within the knowledge graph into archetypes within openEHR, amplifying the interoperability of clinical information. To enhance the interpretability of the DSS, we established executable diagnostic and treatment processes to offer visual representation of clinical steps in diagnosis and treatment. Ultimately, we constructed a decision support engine to implement the GL-DSS, and its effectiveness was evaluated with anonymous real-world data. Results The proposed GL-DSS was found to be quite feasible and could provide etiological diagnosis for SMVT. The knowledge base for the constructed GL-DDS included more than 2000 entities and relations, which played a vital role in representing disease pathogenesis. The proposed system can map the clinical entities to a set of openEHR archetypes, thus mitigate the interoperability issues of the hospital information systems and CDSS data integration. Also, this module improved system usability and ensured that guidelines could be easily translated and updated into decision support tools. Real-word medical records from 20 patient were collected for model evaluation, the results showed that the GL-DSS covered most of the entities and relations between diseases and diagnostic evidence recorded in clinical texts and achieved a diagnosis accuracy of 80%. Conclusions The results demonstrated that our proposed GL-DSS could completely and accurately capture the diagnostic information under the concrete EHR data. Thus, the implement decision support system could have the potential to improve clinical decision-making, patient care, and outcomes in this specialized medical domain.

Barriers to obtaining and using interoperable information among non-federal acute care hospitals.

To understand barriers to obtaining and using interoperable information at US hospitals. Using 2023 nationally representative survey data on US hospitals (N = 2420), we examined major and minor barriers to exchanging information with other organizations, and how barriers vary by hospital characteristics and methods used to obtain information. Using a series of regression models, we examined how hospital experiences with barriers relate to routine use of information at responding hospitals. In 2023, most hospitals experienced at least one minor (81%) or major (62%) barrier to exchange, with the most common major barriers relating to different vendors and exchange partners' capabilities. Higher-resourced hospitals and those often using network-based exchange tended to experience more minor barriers whereas lower-resourced hospitals and those often using mail/fax or direct access to outside electronic health records experienced more major barriers. In multivariate regression, hospitals indicating "Patient matching" and "Costs to exchange" were a major or minor barrier had the strongest independent negative association with the likelihood of reporting providers at their hospital frequently use information from outside organizations. Despite progress in interoperable exchange, various barriers remain. The prevalence of barriers varied by hospital type and methods used, with barriers more often preventing exchange for lower-resourced hospitals and those using outdated exchange methods. While several technical and policy efforts are underway to address prevalent barriers, it will be important to monitor whether efforts are successful in ensuring information from outside organizations can be seamlessly exchanged and used to inform patient care.

An Information Ecosystem Map of Resources Supporting the Mobilization and Discovery of Paleontological Specimen Data

Over the last decade, the United States paleontological collections community has invested heavily in the digitization of specimen-based data, including over 10 million USD funded through the National Science Foundation’s Advancing Digitization of Biodiversity Collections program. Fossil specimen data—9.0 million records and counting (Global Biodiversity Information Facility 2024)—are now accessible on open science platforms such as the Global Biodiversity Information Facility (GBIF). However, the full potential of this data is far from realized due to fundamental challenges associated with mobilization, discoverability, and interoperability of paleontological information within the existing cyberinfrastructure landscape and data pipelines. Additionally, it can be difficult for individuals with varying expertise to develop a comprehensive understanding of the existing landscape due to its breadth and complexity. Here, we present preliminary results from a project aiming to explore how we might address these problems. Funding from the US National Science Foundation (NSF) to the University of Colorado Museum of Natural History, Smithsonian National Museum of Natural History, and Arizona State University will result in, among other products, an “ecosystem map” for the paleontological collections community. This map will be an information-rich visualization of entities (e.g. concepts, systems, platforms, mechanisms, drivers, tools, documentation, data, standards, people, organizations) operating in, intersecting with, or existing in parallel to our domain. We are inspired and informed by similar efforts to map the biodiversity informatics landscape (Bingham et al. 2017) and the research infrastructure landscape (Distributed System of Scientific Collections 2024), as well as by many ongoing metadata cataloging projects, e.g. re3data and the Global Registry of Scientific Collections (GRSciColl). Our strategy for developing this ecosystem map is to model the existing information and systems landscape by characterizing entities, e.g. potentially in a graph database as nodes with relationships to other nodes. The ecosystem map will enable us to provide guidance for communities working across different sectors of the landscape, promoting a shared understanding of the ecosystem that everyone works in together. We can also use the map to identify points of entry and engagement at various stages of the paleontological data process, and to engage diverse members within the paleontological community. We see three primary user types for this map: people new(er) to the community, people with expertise in a subset of the community, and people working to integrate initiatives and systems across communities. Each of these user types needs tailored access to the ecosystem map and its community knowledge. By promoting shared knowledge with the map, users will be able to identify their own space within the ecosystem and the connections or partnerships that they can utilize to expand their knowledge or resources, relieving the burden on any single individual to hold a comprehensive understanding. For example, the flow of taxonomic information between publications, collections, digital resources, and biodiversity aggregators is not straightforward or easy to understand. A person with expertise in collections care may want to use the ecosystem map to understand why taxonomic identifications associated with their specimen occurrence records are showing up incorrectly when published to GBIF. We envision that our final ecosystem map will visualize the flow of taxonomic information and how it is used to interpret specimen occurrence data, thereby highlighting to this user where problems may be happening and whom to ask for help in addressing them (Fig. 1). Ultimately, development of this map will allow us to identify mobilization pathways for paleontological data, highlight core cyberinfrastructure resources, define cyberinfrastructure gaps, strategize future partnerships, promote shared knowledge, and engage a broader array of expertise in the process. Contributing domain-based evidence FAIRly*2 requires expertise that bridges the content (e.g. paleontology) and the mechanics (e.g. informatics). By centering the role of humans in open science cyberinfrastructure throughout our process, we hope to develop systems that create and sustain such expertise.

Telemedicine Alert API Engine System for Vital Signs.

Telemedicine is used to assist and support remote medical care for patients. Our objective was to build up a REST Webservices alert engine that receives clinical parameters from patients of vital signs and basic laboratories to monitor patients remotely. We built a REST API using FHIR, so it can interoperate with other applications, send data to be processed, and receive a response. If the API detects a health risk situation, it sends an alert about the medical parameters that are controlled. The results of the processed data, news and alert, can return synchronously or asynchronously, at the same time that the data to be processed is being sent. The alerts generated can be automatically sent to a web service, mail or WhatsApp of the physician. The alert message comes out as normal, low, medium and high risk. The presented approach establishes communication that enables timely health information exchange. We conducted an experiment (with fictitious data) where we sent several queries by Postman. Finally, we evaluated the communication to be successful by manual checking. The use of the API significantly improves the monitoring of chronic patients. Many works show the effectiveness of telemedicine to improve the control of certain chronic diseases. In addition, telemedicine interventions were also found to significantly improve other health outcomes. Our API enables us to transfer data and produce alerts successfully. This gives us hope that a future with ubiquitous healthcare information interoperability is possible using our system.

Information exchange and knowledge discovery for additive manufacturing digital thread: a comprehensive literature review

ABSTRACT With the information integration and intelligent embedding of Additive Manufacturing (AM) in intelligent industrial system applications, the information interoperability and knowledge discovery are becoming an infrangible trend that provide efficient data and knowledge-driven approaches for intelligent AM supports. STEP-NC standards in the specific AM digital thread are recognized as a potential means that can be used to explore multi-source data and knowledge analysis to support AM information exchange and knowledge discovery. As a comprehensive review of the related literatures, AM digital thread has deeply been discussed to analyse the information exchange and knowledge discovery for STEP-NC implementations. Furthermore, the STEP-NC for CNC has been reviewed to extend the possibility of STEP-NC for AM with ontology-based knowledge discovery by loads of literatures. In order to deeply explore the integration of STEP-compliant data transfer and knowledge discovery, ontology-based modelling approach and STEP-NC data transfer can be further discussed by combining the application of OntoSTEP-NC to review the literatures of data and knowledge-driven AM supports.

Heterogeneous and plaintext checkable signcryption for integrating IoT in healthcare system

Preserving the confidentiality and integrity of data transmission is paramount in the Internet of Things (IoT)-based healthcare systems. Current encryption techniques that allow plaintext checks primarily serve a specific cryptosystem, lacking the adaptability to work with a diverse system incorporating various cryptographic methods. To address this, we present a unique online/offline heterogeneous signcryption scheme with plaintext checkable encryption (HOOSC-PCE). This approach enables the transition of signcrypted messages from an identity-based cryptosystem (IBC) to a public key infrastructure (PKI) system, improving information interoperability. A key aspect of our scheme is its capacity to allow cloud servers to perform plaintext queries, facilitating efficient data searches using plaintext keywords over encrypted data. Furthermore, the signcryption process is divided into online and offline phases. The online phase handles tasks that require fewer resources, while the offline phase carries out more resource-intensive preparatory tasks. We rigorously tested the HOOSC-PCE scheme’s security by proving it secure under the Random Oracle Model (ROM). Meanwhile, compared to similar work, it effectively reduces computation costs by 46.39%, 19.45%, 18.73%, and 13.25% across offline encryption, online encryption, decryption, and search algorithms. The results indicate that the HOOSC-PCE is secure and efficient, confirming its feasibility for IoT-based healthcare systems.

FFO: Forest Fire Ontology and Reasoning System for Enhanced Alert and Management Services

Forest fires or wildfires pose a serious threat to property, lives, and the environment. Early detection and mitigation of such emergencies, therefore, play an important role in reducing the severity of the impact caused by wildfire. Unfortunately, there is often an improper or delayed mechanism for forest fire detection which leads to destruction and losses. These anomalies in detection can be due to defects in sensors or a lack of proper information interoperability among the sensors deployed in forests. This paper presents a lightweight ontological framework to address these challenges. Interoperability issues are caused due to heterogeneity in technologies used and heterogeneous data created by different sensors. Therefore, through the proposed Forest Fire Detection and Management Ontology (FFO), we introduce a standardized model to share and reuse knowledge and data across different sensors. The proposed ontology is validated using semantic reasoning and query processing. The reasoning and querying processes are performed on real-time data gathered from experiments conducted in a forest and stored as RDF triples based on the design of the ontology. The outcomes of queries and inferences from reasoning demonstrate that FFO is feasible for the early detection of wildfire and facilitates efficient process management subsequent to detection.

Construction and implementation of cross-border e-commerce supply chain system under the background of green and low-carbon

PurposeAs China’s e-commerce and cross-border e-commerce rapidly develop, the cross-border e-commerce supply chain exhibits characteristics of globalized development scale, collaborative multiparty participation, streamlined management processes, digitalized production and trade and flexible strategic choices. It tends toward data-driven intelligence, interoperable information collaboration, personalized order responses, sustainable supply chain management and secure blockchain technology. These characteristics and trends provide critical references for businesses, governments and investors.Design/methodology/approachIn response to issues such as inconsistent legal regulations, imbalanced logistics and transportation, imperfect payment settlements and opaque supply chains.FindingsIt is recommended to take measures to strengthen cooperation and communication, optimize logistics, reduce customs clearance difficulties, reinforce safeguard measures and promote sustainable development, collectively fostering the healthy growth of cross-border e-commerce.Originality/valueWith the rapid development of cross-border e-commerce, green and low-carbon initiatives have become a significant trend in this sector. The cross-border e-commerce supply chain refers to the mechanism that reduces environmental impacts and enhances resource efficiency from manufacturers to consumers. It primarily involves manufacturers, e-commerce platforms, logistics companies and payment and settlement processes. The cross-border e-commerce supply chain is gradually becoming a highlight in China’s foreign trade, supporting the concept of “buying globally and selling globally” and connecting the “world’s factory” with the “world’s market.”

A Survey of the Use of Modeling, Simulation, Visualization, and Mapping in Public Health Emergency Operations Centers during the COVID-19 Pandemic.

The COVID-19 pandemic has significantly changed life and work patterns and reshaped the healthcare industry and public health strategies. It posed considerable challenges to public health emergency operations centers (PHEOCs). In this period, digital technologies such as modeling, simulation, visualization, and mapping (MSVM) emerged as vital tools in these centers. Despite their perceived importance, the potential and adaptation of digital tools in PHEOCs remain underexplored. This study investigated the application of MSVM in the PHEOCs during the pandemic in Canada using a questionnaire survey. The results show that digital tools, particularly visualization and mapping, are frequently used in PHEOCs. However, critical gaps, including data management issues, technical and capacity issues, and limitations in the policy-making sphere, still hinder the effective use of these tools. Key areas identified in this study for future investigation include collaboration, interoperability, and various supports for information sharing and capacity building.

Challenges Meeting 21st Century Cures Act Patient Identity Interoperability and Information Blocking Rules.

Gather insights into healthcare organization (HCO) preparedness for new 21st Century Cures Act information blocking disincentives and challenges in achieving greater accuracy /interoperability of patient identity/data. Survey of 197 U.S. healthcare executives (54.7% response rate), included 46 health systems (23.4%), 141 hospitals (71.6%), and 10 payer organizations (5.1%), evaluated organizational gaps in patient identity data management/interoperability and preparation for information deblocking. Healthcare organizations are unprepared to meet information deblocking requirements and manage increased data influx/exchange. Although 61% have invested in meeting requirements, only 36% have capabilities in place. Majorities reported inability to comply with information blocking rules (59%), communicate electronic patient activity notifications to other organizations (56%), or share/receive patient-level information with patients and other HCOs (57%). Across 12 critical functionalities, 57% lacked key capabilities; 97% reported inadequate patient data/identity management/interoperability as data volume expands, adversely affecting care quality/safety and outcomes; and 57% envision patient data-matching errors precipitating a healthcare crisis in 5-10 years. Many HCOs are unprepared to meet new Cures Act information blocking requirements and resultant increase of internal/external patient data volumes. Next generation master data management, enterprise master patient index, and referential matching technologies can improve HCO patient identity and data management, and information interoperability.

Interoperable Information Flow as Enabler for Efficient Predictive Maintenance

Industry 4.0 enables the modernisation of machines and opens up the digitalisation of processes in the manufacturing industry. As a result, these machines are ready for predictive maintenance as part of Industry 4.0 services. The benefit of predictive maintenance is that it can significantly extend the life of machines. The integration of predictive maintenance into existing production environments faces challenges in terms of data understanding and data preparation for machines and legacy systems. Current AI frameworks lack adequate support for the ongoing task of data integration. In this context, adequate support means that the data analyst does not need to know the technical background of the pilot’s data sources in terms of data formats and schemas. It should be possible to perform data analyses without knowing the characteristics of the pilot’s specific data sources. The aim is to achieve a seamless integration of data as information for predictive maintenance. For this purpose, the developed data-sharing infrastructure enables automatic data acquisition and data integration for AI frameworks using interoperability methods. The evaluation, based on two pilot projects, shows that the step of data understanding and data preparation for predictive maintenance is simplified and that the solution is applicable for new pilot projects.

Connecting Producers and Recyclers: A Digital Product Passport Concept and Implementation Suitable for End-of-Life Management

To facilitate the shift from a Linear to a Circular Economy, it is essential to alter the manner in which we manufacture, use, and dispose of products. Interoperable information exchange among various stakeholders throughout the product lifecycle is crucial if we wish to encourage reuse, repair, remanufacturing, refurbishing, or recycling. The Digital Product Passport (DPP) is a concept for capturing product information. This paper presents an end-to-end process for sharing product-related information along the product lifecycle explicitly designed to cater to the needs of all stakeholders, including end-of-life actors. This process is based on a DPP concept and implementation called the Digital Lifecycle Passport and a multi-stakeholder platform. Technically, it relies on the Asset Administration Shell (AAS), which enables information to be shared in a structured way. We demonstrate how this process can improve waste sorting and how it can be used for life cycle assessment (LCA). LCA results are captured in an interoperable way based on DIN SPEC 91474, which will facilitate automatic documentation for regulatory purposes in the future. Our approach is a forerunner in the sense that it uses the DPP and the AAS for end-of-life management.

Allocation of Responsibilities in Interoperable Information Exchanges: Effective Review Compromised?

Allocation of Responsibilities in Interoperable Information Exchanges: Effective Review Compromised?

DEXPI process: Standardizing interoperable information for process design and analysis

DEXPI Process is a proposed standard for modelling information about process design, as it is presented on block flow and process flow diagrams. It was developed by the DEXPI+ working group and builds upon the DEXPI (Data Exchange in the Process Industry) standard for piping and instrumentation diagrams. Digitalization is making increasing demands on the exchange of information in the process facility lifecycle. Industry 4.0 methods require shared terminology and knowledge models to exchange information. Standards, such as ISO15926, CFIHOS and DEXPI, try to address this need. All these focus on the physical plant items, as shown on a PID or 3D model. There is a lack of standards for early-phase, top-down process design. DEXPI Process fills this gap. This paper presents the development of DEXPI Process in the context of knowledge modelling of process systems and previews how the model is a foundation for applications of automated reasoning and decision support for design and operations.

Deep learning enabled blockchain based electronic heathcare data attack detection for smart health systems

The idea of networked personal medical devices is a component of contemporary Smart Health Systems (SHS). These gadgets offer remote observing and the exchange of wellbeing information, which enormously further develop the patient's personal satisfaction while at the same time reducing treatment expenses for both the patient and the medical care suppliers (telemedicine). For individuals' wellbeing, a cutting edge individual wellbeing record framework is fundamental. Here, there are still difficulties with information mix from different EHRs, information interoperability, and guaranteeing that admittance to information is totally under the power of the patient. Some security issues are caused by the Network. To settle these issues, we propose a novel profound learning-based framework that circuits state of the art decentralized innovations like IPFS and blockchain with wellbeing information interoperability principles and advances like FHIR's APIs. In this review, we show that correspondence between private clinical gadgets is as a matter of fact powerless to different cyber attacks. We show how an outer assailant could involve man-in-the-center, replay, bogus information infusion, and refusal of-administration assaults to block delicate wellbeing information stream by capturing the correspondence of the individual clinical gadget. We likewise suggest an Interruption Recognition Framework (IDS), GAN, to additional screen traffic on private clinical gear and spot attacks against them. Our extensive investigation shows that GAN, with an F1-score of 98 % and an accuracy of 98.7 %, can successfully and accurately recognise numerous assaults on personal medical equipment.

Documentation of science and technology heritage: a collaboration case between the Federal University of Pará and the Evandro Chagas Institute Museum

It is nearly impossible to consider the management of cultural spaces without contemplating the potential implementation of informational benefits. The feasibility study and implementation of Tainacan is a solution adopted in the museum field by the Brazilian Institute of Museums, and using it allows the interoperability of museum information throughout the national cultural system. The objective is to report the adversities and institutional solutions experienced in order to present museological documentation solutions for scientific collections within the scope of the heritage of science and technology. The methodology used to achieve the objective was the implementation of the extension project Organization and Management of Museological Documentation of the collections present in the Museum of the Instituto Evandro Chagas. This creates a laboratory of museological documental practices based on research to support the organization and representation of information of the Evandro Chagas Institute's museological collection, also allowing semantic conceptual modeling according to international standards for digital collections. This university extension action provides a unique and essential professional experience for students and opportunities for the dissemination of the profession and the Museology Course at the Universidade Federal do Pará through the work carried out. KEYWORDS: Museum Documentation; University Extension; Heritage of Science and Technology

Knowledge-based OpenBIM data exchange for building design

Building design is highly complex as it involves numerous professionals and their interactions, hence with diverse tools used and multi-resources and different structured data and information required to be processed. Despite the existing efforts to develop multi-objective decision making tools to support complex design, most of the research face difficulties to provide holistic, dynamic and collaborative knowledge base due to the complexity of the information interoperability issues across different parties and throughout life cycle. This paper developed an automatic data exchange framework that combines only the necessary data from BIM models using semantic web technology to eliminate inefficiencies in data exchange and improve decision-making early in the design stage. The proposed data acquisition method can produce a dynamic knowledge base to connect both static and dynamic information. A multi-objective knowledge base was developed to assist engineers associated with sustainability and cost in comparing different design options based on the existing BIM data. The proposed ontology was developed using a machine-readable format, allowing the ability to add more concepts to it in the future and work with other automated tools. The validated framework could reduce human involvement and errors while providing more efficient ways to leverage diverse information sources together to support holistic decision-making for building design.

AI-Enabled Consensus Algorithm in Human-Centric Collaborative Computing for Internet of Vehicle

With the enhanced interoperability of information among vehicles, the demand for collaborative sharing among vehicles increases. Based on blockchain, the classical consensus algorithms in collaborative IoV (Internet of Vehicle), such as PoW (Proof of Work), PoS (Proof of Stake), and DPoS (Delegated Proof of Stake), only consider the node features, which is hard to adapt to the immediacy and flexibility of vehicles. On the other hand, classical consensus algorithms often require mass computing, which undoubtedly increases the communication overhead, resulting in the inability to achieve collaborative IoV under asymmetric networks. Therefore, proposing a low failure rate consensus algorithm that takes into account running time and energy consumption becomes a major challenge in IoV applications. This paper proposes an AI-enabled consensus algorithm with vehicle features, combining vehicle-based metrics and neural networks. First, we introduce vehicle-based metrics such as vehicle online time, performance, and behavior. Then, we propose an integral model and a hierarchical classification method, which combine with a BP neural network to obtain the optimal solution for interconnection. Among them, we also use Informer to predict the future online duration of vehicles, which effectively solves the situation that the primary node vehicle drops off in collaborative IoV. Finally, the experimentations show that the vehicle-based metrics eliminate the problem of the primary node vehicle being offline, which realizes the collaborative IoV considering vehicle features. Meanwhile, it reduces the vehicle network system delay and energy consumption.

Application of ecological architecture in architectural design based on information technology integration

Abstract With the development of China’s economy and society, along with the current situation of resource shortage and environmental deterioration, the traditional building production model has long failed to meet the actual requirements of architectural design, which has seriously restricted the development space of the construction industry. Green ecological building is one of the important initiatives to achieve energy saving and emission reduction in the construction industry and is also an important aspect of achieving sustainable social development. This paper proposes the application method of BIM technology in green buildings to solve the problems of green building in traditional design by studying the characteristics of building information model (BIM) technology and related standards, the principles and objectives of green ecological building design and green building design strategies and other related basic theories, combined with the advantages and characteristics of BIM such as visual design, collaborative design, information interoperability and performance simulation, The workflow of BIM technology in green building design is introduced. Based on ecological architecture and supported by the building information model, the application of ecological architecture in high-rise building design based on the integration of information technology is constructed, and the energy-saving efficiency of this method is increased by 16.7% compared with the traditional method. Building ecology design is a new concept based on integrating building information modeling (BIM) technology and green ecological architecture. With the development of building information modeling (BIM) technology, the green ecological building design concept will certainly play a positive role in promoting the diversification of architectural design and the efficient and rapid development of the architectural design. At the same time, to realize the effective saving of land resources, to promote the harmonious development of ecology, environmental protection, and residents, and to apply eco-architecture in the design of high-rise buildings is also an inevitable choice to realize the long-term as well as stable development of cities, and is the future trend of the development of the construction industry.

Identifying Key Themes of Care Coordination for Patients with Chronic Conditions in Singapore: A Scoping Review.

A projected rise in patients with complex health needs and a rapidly ageing population will place an increased burden on the healthcare system. Care coordination can bridge potential gaps during care transitions and across the care continuum to facilitate care integration and the delivery of personalised care. Despite having a national strategic vision of improving care integration across different levels of care and community partners, there is no consolidation of evidence specifically on the salient dimensions of care coordination in the Singapore healthcare context. Hence, this scoping review aims to uncover the key themes that facilitate care coordination for patients with chronic conditions in Singapore to be managed in the community while illuminating under-researched areas in care coordination requiring further exploration. The databases searched were PubMed, CINAHL, Scopus, Embase, and Cochrane Library. Results from Google Scholar were also included. Two independent reviewers screened articles in a two-stage screening process based on the Cochrane scoping review guidelines. Recommendation for inclusion was indicated on a three-point scale and rating conflicts were resolved through discussion. Of the 5792 articles identified, 28 were included in the final review. Key cross-cutting themes such as having standards and guidelines for care programmes, forging stronger partnerships across providers, an interoperable information system across care interfaces, strong programme leadership, financial and technical resource availabilities and patient and provider-specific factors emerged. This review also recommends leveraging these themes to align with Singapore's national healthcare vision to contain rising healthcare costs.