Relevant bibliographies by topics / Healthcare Workflow Optimization

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Academic literature on the topic 'Healthcare Workflow Optimization'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Healthcare Workflow Optimization"

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Reshma Vemula. "Optimizing Healthcare Delivery: A Comprehensive Guide to Workflow Models and Digital Transformation." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 1828–37. https://doi.org/10.32628/cseit251112180.

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This comprehensive article explores the transformation of healthcare delivery through advanced workflow models and digital solutions, emphasizing the critical role of technology integration in modern healthcare systems. The article examines various aspects of healthcare workflow optimization, including clinical processes, administrative workflows, patient engagement systems, and cross-departmental coordination. It shows the implementation of digital healthcare solutions, focusing on Electronic Health Records (EHR) interoperability, telemedicine advancements, mobile health applications, and pat
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Researcher. "HOW WORKFLOW OPTIMIZATION IMPROVES PATIENT CARE." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 1192–206. https://doi.org/10.5281/zenodo.14162809.

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This study examines how workflow optimization systems transform healthcare delivery through advanced technologies and AI integration. Research across multiple healthcare facilities demonstrates significant improvements: a 45% reduction in documentation time, 37.8% decrease in critical care response times, and average cost savings of $428 per patient encounter. Implementation of these systems, while challenging, shows consistent benefits: 42.8% reduction in scheduling conflicts, 47.2% decrease in hospital readmission rates, and 41.3% reduction in equipment downtime. The findings provide a roadm
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ALObaid, Saleh Khalil, Ahmed Mohsen Mohamed Alzahrani, Fayez Salem Alsharif, et al. "Enhancing Patient-Centered Care Through Process Improvement: A Systematic Review of patient Satisfaction Outcomes." Journal of Ecohumanism 3, no. 8 (2024): 975–82. http://dx.doi.org/10.62754/joe.v3i8.4791.

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Patient-centered care has become a cornerstone in modern healthcare, focusing on personalized, respectful, and effective treatment that meets patients' unique needs and preferences. Process improvement methodologies, such as Lean, Six Sigma, and workflow optimization, have been increasingly adopted to streamline healthcare operations, reduce inefficiencies, and improve the quality of care. However, the specific impact of these methodologies on patient satisfaction within patient-centered care frameworks remains to be systematically evaluated. This systematic review aims to examine the effects
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T Alshammari, Zaid Kalaf, ‏. Faisal Khashman‏ M Alosimi, Turki Mohsen M Aldawssari, et al. "The Contribution of Medical Assistants to Healthcare Workflow Optimization: A Systematic Review." Cuestiones de Fisioterapia 54, no. 5 (2025): 159–67. https://doi.org/10.48047/wkz3r069.

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Background: Healthcare systems worldwide are under increasing pressure to improve efficiency and patient flow without compromising care quality. Medical assistants (MAs), as versatile healthcare workers, are increasingly integrated into care teams to support workflow optimization. However, the extent and impact of their contributions remain underexplored. Objective: To systematically review existing literature on the role of medical assistants in optimizing healthcare workflow, with a focus on improving clinical efficiency, reducing provider workload, and enhancing patient throughput. Methods:
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Venkateswara Reddi Cheruku. "AI-orchestrated workflow automation in cloud-based hospital information systems: Enhancing efficiency and patient outcomes." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1544–54. https://doi.org/10.30574/wjarr.2025.26.2.1763.

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This technical article explores the integration of artificial intelligence technologies into enterprise-grade Hospital Information Systems and Electronic Medical Record platforms to automate clinical and administrative workflows. As healthcare organizations face increasing pressure to improve operational efficiency while enhancing patient care quality, AI-orchestrated workflow automation emerges as a transformative approach. The article examines the technical architecture, implementation challenges, and measurable benefits of these systems, highlighting successful deployments across various he
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Researcher. "HEALTHCARE INBOX MANAGEMENT: AUTOMATING COMMUNICATION WORKFLOWS FOR CLINICAL EFFICIENCY." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 2038–46. https://doi.org/10.5281/zenodo.14288038.

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This comprehensive article examines the transformation of healthcare communication through automated inbox management systems, focusing on their impact on clinical efficiency and patient care. The article examines core components, automated organizational features, workflow optimization, security measures, and implementation strategies in healthcare settings. The article analyzes how centralized communication hubs, message categorization systems, priority-based routing, and EHR integration work together to streamline healthcare communications. It explores the evolution of automated features in
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Kalisa G., Mugabo. "Interdisciplinary Collaboration: Advancing Healthcare through Engineering." Research Output Journal of Engineering and Scientific Research 4, no. 2 (2025): 59–65. https://doi.org/10.59298/rojesr/2025/4.2.5965.

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The complexity of modern healthcare demands collaborative efforts that bridge disciplinary divides. This paper examines the critical role of interdisciplinary collaboration, particularly between engineering and healthcare professionals, in designing and implementing innovative, human-centered technological solutions. Through a five-year interdisciplinary project, the paper investigates the dynamics, benefits, and challenges of collaboration between engineering students and clinical practitioners. From prototyping safety technologies in hospitals to integrating computational methods in diagnost
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HARI SURESH BABU GUMMADI. "AI-driven multimodal workflow optimization for personalized patient-centered care." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 555–63. https://doi.org/10.30574/wjaets.2025.15.2.0604.

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This research presents a novel multimodal artificial intelligence framework designed to optimize healthcare workflows and enhance personalized patient-centered care. The approach integrates four critical data streams: Electronic Health Records, patient-reported outcomes, genomic and molecular data, and real-time physiological information from wearable sensors. Unlike traditional healthcare AI applications that operate in isolated data silos, our system creates a comprehensive patient profile that enables more holistic and personalized care decisions. Case studies in chronic disease management,
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Sriram Sitaraman. "AI-Driven Diagnostics and Imaging: Transforming Early Detection and Precision in Healthcare." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1258–67. https://doi.org/10.32628/cseit241061167.

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Artificial intelligence is revolutionizing medical imaging and diagnostics, marking a transformative era in healthcare delivery. This comprehensive article explores the evolution from early computer-aided diagnosis systems to sophisticated deep-learning architectures, examining their impact across radiology, pathology, and clinical workflows. The article covers breakthrough technologies, including vision transformers, multi-modal integration, and explainable AI frameworks, highlighting their contributions to improved diagnostic accuracy and efficiency. The article encompasses the clinical bene
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Nurulhuda, Uun, and Bara Mira Dwiyana. "Systematic Literature Review: Health Technology in Nursing." West Science Interdisciplinary Studies 2, no. 10 (2024): 2114–23. http://dx.doi.org/10.58812/wsis.v2i10.1399.

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Digital health technologies such as telehealth, electronic health records (EHR), and artificial intelligence (AI) have transformed nursing by enhancing patient care, improving workflow efficiency, and expanding healthcare accessibility. This systematic literature review examines the current role of these technologies in nursing practice, focusing on their impact on patient outcomes, workflow optimization, and accessibility of healthcare services. Findings indicate that telehealth increases healthcare access for underserved populations, EHRs improve care coordination and documentation accuracy,
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Books on the topic "Healthcare Workflow Optimization"

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Fox, Colleen J., and Reshma Munbodh. Workflow Optimization in Radiation Oncology. Medical Physics Publishing, 2024. http://dx.doi.org/10.54947/9781951134303.

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Technological advances in radiation oncology that promise improvements in workflow efficiency are frequently adopted in response to pressure to do things faster and to get more done with fewer resources. The results of such improvements hinge not only on the technology but on how they are integrated into the overall clinical system as a whole. Throughout history, other industries have developed theories related to production optimization, and we can learn from their experiences. Workflow Optimization in Radiation Oncology: From Theory to Clinical Implementation applies these lessons to radiati
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Book chapters on the topic "Healthcare Workflow Optimization"

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Sunkara, Jaswanth, and Anitha D. "Optimization Methods in Healthcare Machine Learning." In Integrative Machine Learning and Optimization Algorithms for Disease Prediction. IGI Global Scientific Publishing, 2025. https://doi.org/10.4018/979-8-3373-1087-9.ch004.

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This comprehensive examination of optimization methodologies in healthcare machine learning addresses unique challenges in this critical domain. The content investigates approaches including gradient-based methods, evolutionary algorithms, metaheuristics, and Bayesian optimization, highlighting healthcare-specific adaptations through case studies spanning diagnostic modeling, treatment planning, medical imaging, and resource allocation. Extending beyond algorithms, the discussion addresses implementation considerations including workflow integration, privacy preservation, fairness, and multi-stakeholder engagement. Emerging techniques such as federated optimization, differential privacy, and quantum approaches are evaluated alongside regulatory barriers and governance frameworks. Through this integrative approach, readers gain insight into how optimization techniques enhance healthcare delivery while navigating the complex ethical, operational, and regulatory landscape unique to medical applications.
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Siddadapu Venkata, Anusha, and Vandanapu Shashank. "Workflow optimization and resource allocation in healthcare: The role of necrobotics." In Necrobotics for Healthcare Applications and Management. Elsevier, 2025. https://doi.org/10.1016/b978-0-443-24832-0.00010-6.

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Baporikar, Neeta. "Role of Information Technology in Enhancing Healthcare Services." In Digital Technologies for a Resource Efficient Economy. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2750-0.ch004.

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The purpose of this study was to investigate the role of information technology (IT) in enhancing healthcare services. It aimed to evaluate the status of health information technology (HIT), factors influencing HIT usage, and strategic aspects contributing to its effective utilization. Adopting a mixed-methods research design using open-ended interviews and quantitative elements through structured surveys, and thematic analysis for qualitative data, while descriptive statistics were used for quantitative data. The findings revealed the need for infrastructure upgrades and extensive training programs and factors affecting HIT usage reveal notable impacts on administrative processes and patient care outcomes, with challenges increasing the administrative workload and influencing coordination processes. Collaborative efforts between healthcare professionals and IT staff can act as the impetus for successful HIT implementation, integration, workflow optimization, and the development of user-friendly systems.
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Pramanik, Sabyasachi. "Overcoming the Digital Frontier." In Advances in Healthcare Information Systems and Administration. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1463-0.ch013.

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In order to traverse the digital frontier, a socio-technical review of Indonesia's NHS e-health strategy identifies important obstacles and suggests a cutting-edge socio-technical model to direct future initiatives. The research examined technological interoperability issues and socio-organizational hurdles while analyzing the NHS's e-health plan within pre-existing frameworks and international best practices. Significant obstacles were identified by the findings, including budgetary limitations, cybersecurity risks, and clinical opposition. A new socio-technical paradigm was put out that advocates a change in emphasis from EHRs to inter-organizational clinical and social care workflow optimization. The model incorporates elements of “lifecycle” and “purpose.” The approach advocated developing national standards and infrastructure in conjunction with government budgetary support, with a focus on interoperability and cybersecurity.
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Gattnar Eva, Ekinci Okan, and Detschew Vesselin. "A Novel Way of Standardized and Automized Retrieval of Timing Information along Clinical Pathways." In Studies in Health Technology and Informatics. IOS Press, 2011. https://doi.org/10.3233/978-1-60750-806-9-507.

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Improving the effectiveness and efficiency of acute healthcare is very important nowadays. Optimization of clinical pathways regarding quality, time and costs is one of the key management strategies of critical diseases such as heart attack and stroke. To identify workflow bottlenecks requires a thorough understanding about both the hospital environment (e.g. IT-systems) and processes (e.g. clinical pathways). Having in mind the interoperability issues in hospitals, the standardized division- and system-crossing time measurement is still a challenge. Therefore this paper presents a novel way of structured and standardized retrieval of timing information along the clinical pathway of time-critical diseases in the context of hospital IT-systems, which represents a promising opportunity to identify workflow bottlenecks over several departmental and system borders.
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Harriet Linda, C., Muthu Kumaran T, and Sathishkumar Ravichandran. "Smart Hospital Infrastructure with AI Driven Workflow Automation and Resource Optimization for Efficient Healthcare Management." In IoT-Enabled Smart Health Care Systems, 2025th ed. RADemics Research Institute, 2025. https://doi.org/10.71443/9789349552548-04.

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The rapid integration of artificial intelligence into clinical environments has redefined the landscape of medical decision-making by enabling real-time, data-driven insights across diagnostic, therapeutic, and operational domains. While AI augments clinical capabilities, its presence also introduces critical cognitive and systemic challenges—most notably, automation bias, wherein human decision-makers tend to over-rely on AI recommendations, even in the presence of contradictory evidence or clinical context. This chapter explores the emergence, causes, and consequences of automation bias within high-stakes medical scenarios, where clinical decisions bear significant consequences for patient safety and outcomes. A comprehensive examination is presented on the interplay between cognitive trust, system design, user interface architecture, and institutional policy that shapes human interaction with AI systems. Drawing from empirical evidence and theoretical models, the chapter outlines effective strategies to mitigate automation bias, including the implementation of explainable AI, uncertainty-aware interfaces, clinician-in-the-loop feedback mechanisms, and AI literacy programs. Furthermore, it emphasizes the importance of designing human-AI collaboration frameworks that preserve clinical autonomy while leveraging algorithmic efficiency. Governance, accountability, and ethical alignment are also discussed as foundational pillars to ensure transparent, equitable, and trustworthy AI deployment in healthcare. The integration of these strategies forms a critical pathway toward sustainable, responsible innovation that enhances rather than diminishes human judgment in clinical settings. By addressing automation bias proactively, healthcare systems can ensure that AI technologies become true partners in improving diagnostic accuracy, patient safety, and system resilience.
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Ben Khalifa, Romdhane. "Process Planning and Preparation for 3D Printing From Design to Execution." In Modeling, Analysis, and Control of 3D Printing Processes. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0533-2.ch007.

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The pace of innovation in 3D printing, or additive manufacturing, has changed the product design and fabrication process in many sectors, including healthcare, aerospace, and general manufacturing. However, turning a digital design into a physical object even high-quality requires a comprehensive workflow that covers all activities from planning to production. This paper attempts to give an overall view of the main milestones in process planning and preparation for 3D printing while emphasizing the significance of each stage toward achieving the best results. The survey starts with the first step of developing a digital model where several issues are listed that relate to designing efficiency optimization, file type such as STL or OBJ and correction of mistakes identified so as to make the model printable. From here, the workflow proceeds to model orientation and slicing wherein for slicing parameters like layer thickness, infill density and support structures are chosen parameter specifically for the printing technology and material used.
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Netzband, Steffen, Johann Frei, Florian Weber, et al. "Introducing a FHIR-Based Toolset for Analyzing Nursing-Related Data." In Studies in Health Technology and Informatics. IOS Press, 2025. https://doi.org/10.3233/shti250719.

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Data analytics is a promising strategy to improve both the decision-making of nursing management and supporting nursing research, often constrained by the lack of standardized data sets. The HL7© Fast Healthcare Interoperability Resources (FHIR) standard offers a structured approach to addressing this issue, yet accessible software solutions for nursing-related FHIR data analysis are limited. This paper introduces an open-design framework to facilitate data-driven innovations in nursing research and practice, based on current developments in the German healthcare sector, such as the development of nursing-related FHIR specifications and the telematics infrastructure for secure data exchange. We present software implementations developed within this work for secure data exchange (Kommunikation im Medizinwesen Care) and the evaluation and visualization of nursing-related FHIR resources (FHIR QR Vis and FHIR Nursing Dashboard). The feasibility of this approach was validated through two case studies at a German nursing home and a university hospital, demonstrating its potential to enhance data-driven decision-making and workflow optimization in nursing.
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Kumar, Dr Dheeraj. "THE ROLE OF ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND DEEP LEARNING IN THE RADIOLOGY DEPARTMENT." In Futuristic Trends in Artificial Intelligence Volume 3 Book 3. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bkai3p3ch2.

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The radiology department contributes significantly to modern healthcare by using a variety of imaging techniques to help with illness diagnosis, observation, and therapy. It is incharge of taking and analyzing medical pictures, working with other medical specialists, and assuring precise and prompt diagnosis. The radiology department's duties and responsibilities include a diverse variety of tasks. The department's primary function is the performance of diagnostic imaging techniques such as X-rays, CT scans, MRIs, ultrasounds, and nuclear medicine studies. With the use of these imaging techniques, radiologists may see inside organs, tissues, and structures, which aids in the diagnosis and classification of disorders. Second, picture interpretation and reporting are the responsibility of the radiology department. In conclusion, AI has already significantly improved image analysis, workflow optimization, and decision-making assistance in the field of radiology. The future of AI in the radiology department offers even more innovations and improvements in patient care as research and development proceed.
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Veeraiah, Vivek, Dharmesh Dhabliya, Sukhvinder Singh Dari, et al. "Overcoming the Digital Frontier." In Advances in Medical Technologies and Clinical Practice. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2141-6.ch008.

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In order to traverse the digital frontier, a socio-technical review of Indonesia's NHS e-health strategy identifies important obstacles and suggests a cutting-edge socio-technical model to direct future initiatives. The research examined technological interoperability issues and socio-organizational hurdles while analyzing the NHS's e-health plan within pre-existing frameworks and international best practices. Significant obstacles were identified by the findings, including budgetary limitations, cybersecurity risks, and clinical opposition. A new socio-technical paradigm was put out that advocates a change in emphasis from EHRs to inter-organizational clinical and social care workflow optimization. The model incorporates elements of “lifecycle” and “purpose.” The approach advocated developing national standards and infrastructure in conjunction with government budgetary support, with a focus on interoperability and cybersecurity. This calculated reorientation ensures a comprehensive and long-lasting change in the healthcare environment by offering a path forward for upcoming e-health projects in Indonesia.
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