Implementation Of System Research Articles

Maturity Assessment of District Health Information System Version 2 Implementation in Ethiopia: Current Status and Improvement Pathways.

Although Ethiopia has made remarkable progress in the uptake of the District Health Information System version 2 (DHIS2) for national aggregate data reporting, there has been no comprehensive assessment of the maturity level of the system. This study aims to assess the maturity level of DHIS2 implementation in Ethiopia and propose a road map that could guide the progress toward a higher level of maturity. We also aim to assess the current maturity status, implementation gaps, and future directions of DHIS2 implementation in Ethiopia. The assessment focused on digital health system governance, skilled human resources, information and communication technology (ICT) infrastructure, interoperability, and data quality and use. A collaborative assessment was conducted with the engagement of key stakeholders through consultative workshops using the Stages of Continuous Improvement tool to measure maturity levels in 5 core domains, 13 components, and 39 subcomponents. A 5-point scale (1=emerging, 2=repeatable, 3=defined, 4=managed, and 5=optimized) was used to measure the DHIS2 implementation maturity level. The national DHIS2 implementation's maturity level is currently at the defined stage (score=2.81) and planned to move to the manageable stage (score=4.09) by 2025. The domain-wise maturity score indicated that except for ICT infrastructure, which is at the repeatable stage (score=2.14), the remaining 4 domains are at the defined stage (score=3). The development of a standardized and basic DHIS2 process at the national level, the development of a 10-year strategic plan to guide the implementation of digital health systems including DHIS2, and the presence of the required competencies at the facility level to accomplish specific DHIS2-related tasks are the major strength of the Ministry of Health of Ethiopia so far. The lack of workforce competency guidelines to support the implementation of DHIS2; the unavailability of core competencies (knowledge, skills, and abilities) required to accomplish DHIS2 tasks at all levels of the health system; and ICT infrastructures such as communication network and internet connectivity at the district, zonal, and regional levels are the major hindrances to effective DHIS2 implementation in the country. On the basis of the Stages of Continuous Improvement maturity model toolkit, the implementation status of DHIS2 in Ethiopia is at the defined stage, with the ICT infrastructure domain being at the lowest stage as compared to the other 4 domains. By 2025, the maturity status is planned to move from the defined stage to the managed stage by improving the identified gaps. Various action points are suggested to address the identified gaps and reach the stated maturity level. The responsible body, necessary resources, and methods of verification required to reach the specified maturity level are also listed.

The Use of Online Consultation Systems and Patient Experience of Primary Care: Cross-Sectional Analysis Using the General Practice Patient Survey.

NHS England encourages the use of online consultation (OC) systems alongside traditional access methods for patients to contact their general practice online and for practices to manage workflow. Access is a key driver of patients' primary care experience. The use of online technology and patient experience vary by sociodemographic characteristics. This study aims to assess the association between OC system use and patient experience of primary care in English general practice and how that varies by OC system model and practice sociodemographic characteristics (rurality, deprivation, age, and ethnicity). We categorized practices as "low-use" or "high-use" according to the volume of patient-initiated contacts made via the OC system. We considered practices using one of 2 OC systems with distinct designs and implementation models-shorter "free text" input with an embedded single workflow OC system (FT practices) and longer "mixed text" input with variation in implemented workflow OC system (MT practices). We used 2022 General Practice Patient Survey data to capture 4 dimensions of patient experience-overall experience, experience of making an appointment, continuity of care, and use of self-care before making an appointment. We used logistic regression at the practice level to explore the association between OC system use and patient experience, including interaction terms to assess sociodemographic variation. We included 287,194 responses from 2423 MT and 170 FT practices. The proportions of patients reporting positive experiences at MT and FT practices were similar or better than practices nationally, except at high-use MT practices. At high-use MT practices, patients were 19.8% (odds ratio [OR] 0.802, 95% CI 0.782-0.823) less likely to report a good overall experience; 24.5% (OR 0.755, 95% CI 0.738-0.773) less likely to report a good experience of making an appointment; and 18.9% (OR 0.811, 95% CI 0.792-0.83) less likely to see their preferred general practitioner; but 27.8% (OR 1.278, 95% CI 1.249-1.308) more likely to use self-care, compared with low-use MT practices. Opposite trends were seen at FT practices. Sociodemographic inequalities in patient experience were generally lower at high-use than low-use practices; for example, gaps in overall experience between practices with the most and fewest White patients decreased by 2.7 percentage points at MT practices and 6.4 percentage points at FT practices. Trends suggested greater improvements in experience for traditionally underserved groups-patients from urban and deprived areas, younger patients, and non-White patients. An OC system with shorter free text input and an integrated single workflow can enhance patient experience and reduce sociodemographic inequalities. Variation in patient experience between practices with different sociodemographic characteristics and OC systems underscores the importance of tailored design and implementation. Generalizing results across different OC systems is difficult due to variations in how they are integrated into practice workflows and communicated to patients.

“It's like a guessing game”: Implementation of multiple sign systems in EFL Reading curriculum for undergraduates in Taiwan

“It's like a guessing game”: Implementation of multiple sign systems in <scp>EFL</scp> Reading curriculum for undergraduates in Taiwan

Differences in Patient Secure Message Volume Among Otolaryngologists: A Retrospective Cohort Study.

To identify differences in inbox and secure message burden among otolaryngologists based on demographics and subspecialty over 4 years. Inbox data were queried from January 2019 until December 2022. Otolaryngologists were categorized into cohorts by area of practice and gender. All inbox tasks, secure messages, and clinical encounters were collected and compared by gender, practice type, and years in practice. Means were compared using t-tests and chi-squared tests. Of the 128 physicians, 45.7% were comprehensive otolaryngologists and 61.3% were male. The most common subspecialties were facial plastics (15.6%), oncology (8.6%), and otology (7.8%). Otolaryngologists had an average of 143.5 inbox tasks per month, with 97.2 (67.7%) of them being secure messages, resulting in an average of 1.14 inbox tasks and 0.80 secure messages per clinical encounter. The ratio of secure messages per clinical encounter was consistent across all specialties except oncology (1.10, P = .003). Otology (0.86, P = .032) and facial plastics (0.95, P = .028) had significantly lower ratios of inbox tasks to clinical encounters when compared to their colleagues, while oncology had a higher ratio (1.70, P < .001). No significant differences in inbox burden were observed between genders, years in practice, or languages spoken. Secure messages steadily increased over the study period. Inbox burden for otolaryngologists primarily stems from patient secure messages and varies across subspecialties. Considerations should be made to the inbox burden of head and neck oncologists. The implementation of support systems for inbox management could improve the imbalance between clinical and non-clinical responsibilities in otolaryngology. Level III, Retrospective Cohort Study.

Research and simulation of an office lighting

This research thoroughly examines the evaluation and optimization methods of office lighting aimed at improving energy efficiency and the working environment through the implementation of advanced lighting technologies. Including a comprehensive technical survey of existing lighting conditions, the development of scientifically substantiated recommendations takes into account regulatory requirements and contemporary practices in the field of lighting technology. An analysis of lighting efficiency, selection of optimal light sources, calculation of their placement for maximum efficiency, and assessment of the impact on energy savings are performed, with the goal of achieving better working conditions and reducing energy consumption. The study includes the following steps: illuminance as a critical factor affecting employee productivity and comfort; technical survey of the lighting system in the office space; methodology for conducting the technical survey – measurements of illuminance in different areas of the space using a lux meter; assesment of the need for luminous flux according to norms and standards for office spaces; selection of the type and power of LED lamps for the new lighting system; calculation of the number and placement of LED lamps to provide the necessary level of illuminance in the automated system DIALux Evo Pro; assessment of the expected results in the context of energy savings and improvement of working conditions; calculation of energy expenditures for the new lighting system; potential impact of the research results on energy management and energy audit in the construction sector. The research conclusions suggest strategies for the implementation of an innovative lighting system, which leads to the optimization of energy consumption and significant improvement of lighting quality. These strategies are expected not only to improve the working environment but also to lead to substantial energy resource savings in offices, thereby promoting ecological sustainability and financial efficiency.

Development of an electro-thermo-mechanical 4D printed multi-shape smart actuator: Experiments and simulation

This investigation presents an experimental and numerical approach to developing 4D printed multi-shape actuators with an integrated electrical self-triggering system. It employs a multifunctional shape memory carbon black Polylactic Acid (PLA) layer embedded within rubbery thermoplastic polyurethane (TPU). Notably, these thermo-responsive actuators are programmed and triggered using Joule’s effect, eliminating the need for an external heat source and enabling precise control of temperature gradients. Two distinct motion mechanisms are employed: the differences in thermal expansion coefficient between the PLA/TPU polymers below the glass transition temperature, and the shape memory effect of the PLA layer above the glass transition temperature. As a result, a diverse range of motion responses can be achieved by adjusting the potential differences. A coupled electro-thermo-mechanical finite element model is used to gain further insight into the motion mechanisms, offering predictive capabilities beyond the ones reported by previous models. The developed technology provides enhanced actuation capabilities to conventional bi-shape SMP actuators, offering a versatile range of bending cycles. Furthermore, Joule’s effect enables the implementation of closed-loop control systems, which is essential for developing autonomous robotic systems.

Smart manufacturing implementation: identifying barriers and their related stakeholders and components of technology

Purpose One of the achievements of the fourth industrial revolution is smart manufacturing, a manufacturing system based on Industry 4.0 technologies that will increase systems' reliability, efficiency and productivity. Despite the many benefits, some barriers obstruct the implementation of this manufacturing system. This study aims to analyze these barriers. Design/methodology/approach One of the measures that must be taken is to identify and try to remove these barriers, which involves identifying the stakeholders and components of technology associated with each barrier. As such, the primary purpose of this paper is to present a systematic literature review in the field of smart manufacturing with a focus on barriers to implementation related to the stakeholders and components of technology. Findings This research conducted a systematic literature review in Scopus and Web of Science databases and considered the studies published until 2021 were examined. The central question of this paper is answered based on this literature review, in which 133 related studies and 15 barriers were identified. Practical implications The significant gap observed in the literature review is that no research has been conducted to determine the stakeholders and components of technology related to the barriers, making it a potentially worthwhile subject for future research. In addition, the results of this study may help managers to implement smart manufacturing. Originality/value This study provides two main originalities. The former is helpful information for managers to make effective decisions when they face smart manufacturing barriers. The latter is related to identifying critical research gaps through systematic literature review.

Decarbonization of Heating and Cooling Systems of Buildings Located Nearby Surface Water Sources: Case Study

The study was carried out to evaluate theoretically and in laboratory conditions the capacity of a hybrid heating and cooling system that sustainably uses thermal energy extracted from surface waters in order to decarbonize buildings located near water sources. The novelty of the research consists in the realization of two experimental systems, one for the rapid evaluation of the performance of the water–water heat pump heating system and one for the evaluation of the operating behavior of a cooling system with fan coil units. Starting with the heating and cooling demand, and the climatic and hydrological local characteristics, a hybrid system model for the heating and cooling of the analyzed building was established and implemented. The forecasted energy consumption and CO2 emissions for the operation of the new equipment were compared with the historical values of the old systems with which the building was equipped (thermal energy supply from the district heating and cooling system with an air conditioning unit). Also, the results were extrapolated for forecasting the energy potential of the surface waters. The study highlights a percentage reduction in annual energy consumption of 67.71% and CO2 emissions of 80.13% through the implementation of the hybrid system.

Mengoptimalkan Implementasi Sistem Keuangan Desa untuk Alokasi Dana Desa yang Efektif di Desa Gunungsari Kecamatan Dawarblandong Kabupaten Mojokerto

The implementation of the Village Financial System in Gunungsari village has been very effective, this can be seen from the process of preparing the Village Revenue and Expenditure Budget through Siskeudes which is more easily accessible because of the complete features available in the application. As in Permendagri No. 113 of 2014 concerning villages, namely Planning, Implementation, Administration, Reporting, Accountability, reporting process. The type of research used is qualitative research. Data was obtained by conducting direct interviews, observation and documentation in Gunungsari village by obtaining primary data through interviews with resource persons and secondary data obtained from existing documentation in Gunungsari village, village history, general description and financial reports. The research results show that the implementation of the village financial system plays an important role in the efficiency and transparency of the use of village funds. This system requires strict procedures in financial management, including better reporting and accountability.

Key updates and interpretation of the ninth version of AJCC staging system for neuroendocrine tumors of the stomach

The cancer staging system of the American Joint Committee on Cancer (AJCC) is the most widely used clinical basis for tumor staging. In October 2023, AJCC released the staging system (ninth version) for the neuroendocrine tumors of stomach (NET), which has been implemented in January 2024. The ninth version of NET staging system mainly updated the histopathologic classification, diagnosis and staging methods, clinical and pathological staging, prognosis grade, tumor and non-tumor prognostic features. The update and implementation of the staging system provide a more detailed reference for the accurate diagnosis, staging and precise treatment of gastric neuroendocrine tumors. Moreover, it is convenient for clinicians to carry out clinical practice. The purpose of our article is to provide a high-level overview of the major changes in AJCC staging system (version 9) for gastric NET based on the latest evidence-based medical research.

Hybrid dynamical systems logic and its refinements

Hybrid dynamical systems describe the mixed discrete dynamics and continuous dynamics of cyber-physical systems such as aircraft, cars, trains, and robots. To justify correctness properties of the safety-critical control algorithms for their physical models, differential dynamic logic (▪) provides deductive specification and verification techniques implemented in the theorem prover ▪. The logic ▪ is useful for proving, e.g., that all runs of a hybrid dynamical system α satisfy safety property φ (i.e., ▪), or that there is a run of the hybrid dynamical system α ultimately reaching the desired goal φ (i.e., ▪). Logical combinations of ▪'s operators naturally represent safety, liveness, stability and other properties. Variations of ▪ serve additional purposes. Differential refinement logic (▪) adds an operator α≤β expressing that hybrid system α refines hybrid system β, which is useful, e.g., for relating concrete system implementations α to their abstract verification models β. Just like ▪, ▪ is a logic closed under all operators, which opens up systematic ways of simultaneously relating systems and their properties, of reducing system properties to system relations or, vice versa, reducing system relations to system properties. A second variant of ▪, differential game logic (▪), adds the ability of referring to winning strategies of players in hybrid games, which is useful for establishing correctness properties where the actions of different agents may interfere either because they literally compete with one another or because they may interact accidentally. In the theorem prover ▪, ▪ and its variations have been used for verifying ground robot obstacle avoidance, the Federal Aviation Administration's Next-Generation Airborne Collision Avoidance System ACAS X, and the Federal Railroad Administration's train control model.

Effectiveness of Implementing an Electronic Information System for Room-in Postpartum Care.

Best practices in postpartum care encourage rooming-in to promote early breastfeeding and mother-newborn bonding. However, when the medical records of mothers and newborns are stored separately in the postpartum ward and the neonatal nursery, respectively, nurses encounter difficulties in accessing complete information about the mother-infant dyad, which results in suboptimal care quality. Accordingly, the authors designed an integrated electronic information (e-information) system linking the medical records of newborns and their mothers and implemented it in April 2022 at a medical center in Taiwan. System effectiveness assessment results indicated that before the implementation of the e-information system, the nursing care completion scored 72.4 out of 100, and the nurse satisfaction scored 80.9 out of 100. After the implementation of the system, the nursing care completion increased to 97.8 (p < .001), while the nurse satisfaction rose to 95.8 (p < .001), demonstrating significant improvements.

Healthcare leaders’ experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study

BackgroundArtificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation of AI systems for these purposes, particularly in the context of healthcare leadership. This study explores the experiences of healthcare leaders regarding the barriers to implementing an AI application for automating medical history-taking and triage in Swedish primary care, as well as the actions they took to overcome these barriers. Furthermore, the study seeks to provide insights that can inform the development of AI implementation strategies for healthcare.MethodsWe adopted an inductive qualitative approach, conducting semi-structured interviews with 13 healthcare leaders representing seven primary care units across three regions in Sweden. The collected data were subsequently analysed utilizing thematic analysis. Our study adhered to the Consolidated Criteria for Reporting Qualitative Research to ensure transparent and comprehensive reporting.ResultsThe study identified implementation barriers encountered by healthcare leaders across three domains: (1) healthcare professionals, (2) organization, and (3) technology. The first domain involved professional scepticism and resistance, the second involved adapting traditional units for digital care, and the third inadequacies in AI application functionality and system integration. To navigate around these barriers, the leaders took steps to (1) address inexperience and fear and reduce professional scepticism, (2) align implementation with digital maturity and guide patients towards digital care, and (3) refine and improve the AI application and adapt to the current state of AI application development.ConclusionThe study provides valuable empirical insights into the implementation of AI for automating medical history-taking and triage in primary care as experienced by healthcare leaders. It identifies the barriers to this implementation and how healthcare leaders aligned their actions to overcome them. While progress was evident in overcoming professional-related and organizational-related barriers, unresolved technical complexities highlight the importance of AI implementation strategies that consider how leaders handle AI implementation in situ based on practical wisdom and tacit understanding. This underscores the necessity of a holistic approach for the successful implementation of AI in healthcare.

Optimizing Data-Centric Healthcare: A Novel Monitoring Framework for High-Risk General Ward Patients.

The digital transformation of healthcare in South Korea, accelerated by COVID-19, has led to increased focus on critically ill patients in large hospitals. To address this, a monitoring system was developed to ensure safe inpatient treatment and improve staff efficiency. This aligns with the Medical Data-Centric Hospitals initiative, which leverages data for healthcare innovation. The case study highlights the implementation of a ward critical care monitoring system, which has improved patient safety, work efficiency, and expanded patient monitoring scope. Key lessons include the importance of addressing technical and user challenges, aligning innovations with national policies, and the potential of data-driven solutions to tackle healthcare challenges.

Implementation of Interactive System with Millimeter Wave and Wavelet Transform

Implementation of Interactive System with Millimeter Wave and Wavelet Transform

Factors Affecting ERP System Implementation Among Selected Organizations: A Proposed Operational Strategies

The successful implementation of Enterprise Resource Planning (ERP) systems relies heavily on the interplay between management-specific factors and operational-specific factors. This study investigates these critical success factors, focusing on their impact on organizational performance. Management-specific factors, including top management support, package selection, and organizational fit, provide strategic direction and resources, ensuring alignment with operational goals. The research employed a quantitative approach to gather data from employees of selected organizations that have implemented ERP systems. The survey targeted employees from selected organizations who use ERP systems. The responses were analyzed using statistical techniques such as frequency analysis, mean, standard deviation, Spearman’s rank correlation, and multiple regression to identify the relationships and impacts of various CSFs on ERP implementation success. The study reveals that effective project management significantly enhances package selection, while comprehensive training improves organizational fit. Communication emerges as a pivotal element, influencing all aspects of ERP implementation. These findings underscore the necessity for a balanced approach that integrates both management and operational strategies to achieve optimal ERP outcomes and organizational efficiency.

Implementation of the Versius robotic surgical system for thoracic surgery: first clinical evaluation of feasibility and performance.

The aim of this study is to demonstrate the ability of the Versius surgical system to successfully and safely complete a range of thoracic procedures aligned with Stage 2a (Development) of the Idea, Development, Exploration, Assessment and Long-term follow-up framework for surgical innovation. This prospective study included the first 30 consecutive patients who underwent robotic surgery with Versius by 2 surgeons without prior robotic experience between 1 April 2023 and 30 December 2023 [25 lung resections (wedge, segmentectomy and lobectomy) and 5 thymectomies]. There were no specific predetermined selection criteria for each case. The primary outcome was safe completion of the procedure without unplanned conversion. Secondary outcomes included intraoperative and postoperative complications, intraoperative device-related outcomes and pathology results. Twenty-eight (93.3%) cases were completed without conversion. Both conversions were to thoracoscopy, one due to a 'console alarm' and the other due to pulmonary artery bleeding. In lung resections, median console time was 103 (90-129) min. Five (20%) patients experienced postoperative complications, most frequent was persistent air leak (16%). Median length-of-stay was 3 (2-4) days. Neither readmissions nor mortality was observed. In thymectomies, no intraoperative or postoperative complications, readmissions, reinterventions or mortality were observed. Median console time was 77 (75-89) min and median length of stay was 1 (1-1) day. This phase 2a IDEAL-D study confirms lung resections and thymectomies are feasible with the use of Versius system, laying the foundation for larger phase 2b and 3 clinical studies within the IDEAL-D framework.

Strategies of the countries’ innovative activity in development of intelligent systems

Development of intelligent systems based on artificial intelligence in the area of research and development of technical systems is a new competitive advantage and a growth driver for a country. The authors of the article present the indicators of innovative activity of the countries in development of intelligent systems: the share of the country’s patents in the number of patents for all countries, the number of national strategies in the area of intelligent systems in the country, the geography of implementation of the intelligent systems developed by a country. The authors introduce a term of “index of a country specialization in the sphere of intelligent technology”. Index of specialization is a correlation of factual number of types of patents registered in the country in the sphere of intelligent technology to 10 potentially possible types of patents. These include the patents on advanced manufacturing technologies, robotics, advanced materials, artificial intelligence, big data, the Internet of things, mobility, photonics, security, and digital twins. Using a cluster method, the authors classify 43 countries by the level of innovative activity in the sphere of development of intelligent systems, on the basis of the data provided by the World Intellectual Property Organization and the European Commission in 2023. This allowed developing a classification of 11 strategies of innovative activity in the sphere of development of intelligent systems (based on the scoring assessment). The proposed strategy classification makes it possible to perform benchmarking to study the country’s experience and evaluate the investment risks for the projects in development of intelligent systems.

Что удалось сделать в сельском Татарстане за десять лет реализации системы самообложения населения

The budget deficit in municipalities of the Republic of Tatarstan forces local authorities to search for additional sources of funding to solve the problems of rural settlements. One of the ways was the participation of rural municipalities in the development of a system of self-taxation for citizens. It has been implemented in Tatarstan since 2013. The article sets the task of assessing the effects of the self-taxation system in rural settlements of the republic, accumulated over 10 years of its operation. By analyzing the legislative framework of the Russian Federation and the Republic of Tatarstan, the author reveals the basic concepts and provisions used in the system of self-taxation of citizens. Using interviews he conducted in municipalities of the Republic of Tatarstan with heads, deputies, and activists of rural settlements, the experience of using and features of public participation in the self-taxation system over the past ten years was examined. It was revealed that the results of the implementation of the self-taxation system are expressed in an increased level of trust in it on the part of villagers, in almost one hundred percent collection of contributions, in the involvement of village residents in the formation of municipal budget plans, in increasing the civic responsibility of representatives of rural communities of Tatarstan. The “external” effect of the self-taxation system is expressed in the number of solved problems of local importance: repair and construction of rural roads, water supply, street lighting, improvement of cemeteries, monuments and obelisks, sites for garbage containers, sidewalks, embankments, springs, parks and public gardens. This list of work of conducted works, which is far from complete, using the villagers’ self-taxation system and through co-financing from the government bodies of Tatarstan, has significantly increased the level and quality of rural life in the republic.

A novel system for the classification of zinc-plated components by benchmarking deep neural networks

Artificial intelligence (AI) has become the new technique for solving the most complicated challenges related to big data, image recognition, object detection, and prediction issues due to the fourth industrial revolution. This article introduces the development and implementation of a zinc-plated component recognition system within a manufacturing process using deep learning (DL) techniques. This paper aims to train and evaluate different DL algorithms to recognize five zinc-plated components and one assembly tray under different ambient light conditions and finishing. The proposed method begins with creating a custom dataset of 5.5K images, with six classes that match the assembly components. However, before the training stage starts, a subset between 5% and 10% is created. Eight deep neural networks have been benchmarked: Swing Transformer, Convnextv2, Xception41, Data-efficient image Transformer, Inception_v4, ViT, Resnet50 and Efficientnet_b0. The training stage is performed with the k-fold method using k = 6 and a progressive data size between different runs with an average of data utilized during training of 8%. In this study, convnextv2_tiny exhibits the highest F1-Score with 99.177%, followed by swin_tiny_patch4_window7_224 with 99.175%, while resnet50 achieved the lowest F1-Score at 95.886%. Therefore, the new generation of convolutional architectures is still better for classifying images. Thus, these algorithms can be adopted as good classifier models for zinc-plated component classification in the industrial manufacturing environment.