Medical data integration using HL7 standards for patient’s early identification

Integration between information systems is critical, especially in the healthcare domain, since interoperability requirements are related to patients’ data confidentiality, safety, and satisfaction. The goal of this study is to propose a solution based on the integration between queue management solution (QMS) and the electronic medical records (EMR), using Health Level Seven (HL7) protocols and Extensible Markup Language (XML). The proposed solution facilitates the patient’s self-check-in within a healthcare organization in UAE. The solution aims to help in minimizing the waiting times within the outpatient department through early identification of patients who hold the Emirates national ID cards, i.e., whether an Emirati or expatriates. The integration components, solution design, and the custom-designed XML and HL7 messages were clarified in this paper. In addition, the study includes a simulation experiment through control and intervention weeks with 517 valid appointments. The experiment goal was to evaluate the patient’s total journey and each related clinical stage by comparing the “routine-based identification” with the “patient’s self-check-in” processes in case of booked appointments. As a key finding, the proposed solution is efficient and could reduce the “patient’s journey time” by more than 14 minutes and “time to identify” patients by 10 minutes. There was also a significant drop in the waiting time to triage and the time to finish the triage process. In conclusion, the proposed solution is considered innovative and can provide a positive added value for the patient’s whole journey.

Plant Factory: A New Playground of Industrial Communication and Computing

Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, today’s plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.

Key Success Factors for Smart City Construction

The Smart City is not a new concept. In fact, the digital city appeared in the information era and the wireless city emerged in the Internet era, but the Smart City had not been clearly defined until the digital era. Unlike traditional informatization, a Smart City is not simply the combination of informatization in all industries. Not only is a smart city a top-leadership project, it reshapes the digital capabilities of all industries in a city, while also addressing systematic challenges. This paper presents Huawei perspective on Smart City development, including the conceptual framework, governance, type, connectivity, structural enablers. The paper also describes the strategic vision and a Smart City construction path, from the strategic planning, solution design and implementation.

Over-Actuated Underwater Robots: Configuration Matrix Design and Perspectives

In general, for the configuration designs of underwater robots, the positions and directions of actuators (i.e., thrusters) are given and installed in conventional ways (known points, vertically, horizontally). This yields limitations for the capability of robots and does not optimize the robot’s resources such as energy, reactivity, and versatility, especially when the robots operate in confined environments. In order to optimize the configuration designs in the underwater robot field focusing on over-actuated systems, in the paper, performance indices (manipulability, energetic, reactive, and robustness indices) are introduced. The multi-objective optimization problem was formulated and analyzed. To deal with different objectives with different units, the goal-attainment method, which can avoid the difficulty of choosing a weighting vector to obtain a good balance among these objectives, was selected to solve the problem. A solution design procedure is proposed and discussed. The efficiency of the proposed method was proven by simulations and experimental results.

Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach

Purpose of Review A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard. Recent Findings Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and transplant healthcare. A systems approach leverages techniques for visualizing the system architecture to support solution design from multiple perspectives. Summary Developing a systems-based approach to AI decision support involves engaging in a cycle of documenting the system architecture, identifying pain points, developing prototypes, and validating the system. Early efforts have focused on describing process issues to prioritize tasks that would benefit from AI support.

Risk Assessment of the Door‐In‐Door‐Out Process at Primary Stroke Centers for Patients With Acute Stroke Requiring Transfer to Comprehensive Stroke Centers

Background Patients with acute stroke at non‐ or primary stroke centers (PSCs) are transferred to comprehensive stroke centers for advanced treatments that reduce disability but experience significant delays in treatment and increased adjusted mortality. This study reports the results of a proactive, systematic, risk assessment of the door‐in‐door‐out process and its application to solution design. Methods and Results A learning collaborative (clinicians, patients, and caregivers) at 2 PSCs and 3 comprehensive stroke centers in Chicago, Illinois participated in a failure modes, effects, and criticality analysis to identify steps in the process; failures of each step, underlying causes; and to characterize each failure’s frequency, impact, and safeguards using standardized scores to calculate risk priority and criticality numbers for ranking. Targets for solution design were selected among the highest‐ranked failures. The failure modes, effects, and criticality analysis process map and risk table were completed during in‐person and virtual sessions. Failure to detect severe stroke/large‐vessel occlusion on arrival at the PSC is the highest‐ranked failure and can lead to a 45‐minute door‐in‐door‐out delay caused by failure to obtain a head computed tomography and computed tomography angiogram together. Lower risk failures include communication problems and delays within the PSC team and across the PSC comprehensive stroke center and paramedic teams. Seven solution prototypes were iteratively designed and address 4 of the 10 highest‐ranked failures. Conclusions The failure modes, effects, and criticality analysis identified and characterized previously unrecognized failures of the door‐in‐door‐out process. Use of a risk‐informed approach for solution design is novel for stroke and should mitigate or eliminate the failures.

Modular Interorganizational Network Governance: A Conceptual Framework for Addressing Complex Social Problems

We develop a conceptual governance framework to guide creating and managing a modular interorganizational network to address complex social problems. Drawing on theoretical foundations in modularity and interorganizational networks, we propose that modularizing complex social problems is a dialectic, emergent process that blends a convener-led network formation with a consultative problem definition and solution design. We also posit that social systems are imperfectly modular and need purposefully designed interface governance to integrate the modules. Finally, we advance how leveraging modularity may simultaneously advance the interests of participating actors and deliver societal value. Together, the propositions advance a governance framework for a modular, multi-actor adaptive system suited to tackle the scale, diversity, and dynamics of complex social problems.