Workflow Optimization Research Articles

Artificial Intelligence in Emergency Medicine: A Literature Review

IntroductionArtificial intelligence (AI) is rapidly transforming medical fields, particularly emergency medicine (EM), where timely decision-making is crucial. AI offers potential benefits in diagnostic accuracy, patient care optimization, and workflow efficiency within emergency departments (EDs). Purpose of WorkThis review aims to synthesize recent advancements in AI applications within emergency medicine, focusing on diagnostic support, patient triage, clinical decision support systems (CDSS), and workflow optimization. Additionally, we highlight the potential benefits, challenges, and future directions for AI in EM. Material and MethodsA comprehensive literature search was conducted using PubMed and Google Scholar databases. We reviewed peer-reviewed articles from 2008 to 2024, focusing on AI-driven solutions in EDs. Keywords included "artificial intelligence," "emergency medicine," "machine learning," and "clinical decision support." Studies were selected based on their relevance to AI applications in EM, diagnostic improvements, and operational efficiency. The results highlight the promising role of AI in improving diagnostic accuracy, reducing overcrowding, optimizing triage processes, and addressing clinician workload. However, challenges like ethical concerns, data bias, and the need for clinical validation remain. Further research is necessary to integrate AI more effectively in clinical practice.

Digital Workflow Optimization for Endocrown Restorations on Root- Treated Teeth

Endocrown restorations have become a popular solution for endodontically treated teeth, offering both functional and esthetic benefits. These restorations are particularly effective for molars due to the larger surface area of the pulp chamber, which enhances retention and stability. This article presents a clinical case of a zirconia endocrown restoration for a highly damaged mandibular molar. Utilizing a fully digital workflow, the preparation, design, and fabrication of the restoration were performed with precision, ensuring minimal tooth structure removal. Zirconia was chosen for its superior mechanical properties, including fracture resistance and durability. The challenges associated with zirconia, such as bonding reliability, were addressed through surface treatments like air abrasion and the use of 10-MDP-based chemical promoters. The patient’s outcome was both esthetically pleasing and functionally successful. This case highlights the advantages of integrating digital workflows and advanced materials in modern prosthodontic practice, while also acknowledging the need for careful selection of materials and techniques based on the individual case.

Optimizing the Smart Pump Drug Library Update Process: An Ongoing Effort at an Academic Medical Center

Smart infusion pumps with dose-error reduction software and customizable drug libraries have increased the safety of intravenous infusion delivery; however, maintaining the most updated drug library is a multistep process for most infusion pumps, which requires effort and engagement by the end user to activate the latest drug library. Delays in updating the drug library have been shown to impact patient safety. This article reviews steps taken at an academic medical center to improve the drug library update process. Multidisciplinary efforts resulted in improved drug library activation rates; however, despite workflow optimizations and improvements, achieving complete pump fleet library activation in a timely manner after scheduled updates remains challenging.

Optimization of Space Data Development and Distribution and Capacity Building in the Philippines through the PhilSA Integrated Network for Space Enabled Actions towards Sustainability (PINAS) Project

Abstract. The Philippine Space Agency (PhilSA) implemented the PhilSA Integrated Network for Space Enabled Actions towards Sustainability (PINAS) to establish an active network of institutions and citizen scientists that will work together to utilize space data and information in support of the sustainable development agenda. The project was conceptualized to address the inherent challenge in gathering feedback, disseminating space data and information, and conducting capacity building initiatives in an archipelagic nation. The project will be conducted in three (3) phases, Phase 1: Network Building, Phase 2: Capacity Building, and Phase 3: Build Up and Expansion. This paper highlights the initial activities and preliminary assessment of the PINAS Project. The results of the initial activities illustrate the potential of the project in optimizing data products and its distribution processes, and in strengthening local capacity to use space data and information. This contributes to the development of effective capacity building initiatives and efficient space data optimization and data-sharing workflows in the country.

QLTI-19. PEDIATRIC NEURO-ONCOLOGISTS NAVIGATING AN ADULT WORLD: A TALE OF TWO CENTERS

Abstract BACKGROUND Adolescent and Young Adult Neuro-Oncology(AYA-NO) patients are a distinct cohort with an overlap of tumors found in childhood and adulthood. For adult patients with pediatric-type Central Nervous System tumors, optimal work-flow to manage these patients is unclear. METHODS We examine the work-flow of pediatric neuro-oncologists starting AYA-NO clinics within two high volume adult institutions: the University of Miami(Florida, USA) and the Princess Margaret Cancer Centre(Toronto, Canada). RESULTS Over 18 months, the AYA-NO clinics managed 167 patients total with several key differences emerging in both institutions between the pediatric and adult work-flows. Adult providers commonly have neurology backgrounds, while pediatric providers mostly have hematology/oncology backgrounds. In pediatrics, providers typically meet the patient inpatient before pathology results, adult providers meet their patients in outpatient settings once histopathology results are available. Outpatient management in pediatric oncology centers typically includes labs, infusion centers, provider rooms, and social workers in one area while adults, due to the larger volume, have these services on separate units. Chemotherapy related differences included the primary provider for inpatient admissions and the emphasis of adult institutions on outpatient administration when feasible. Psychosocial factors such as the variety of caregivers, increased opportunity for patient autonomy in decision-making, and the increased fragmentation in care magnifies the importance of providers forming a strong rapport with AYA-NO patients. End of life care is vastly different including the inability for adult patients to receive palliative treatment in hospice care and the availability medically-assisted death. CONCLUSION Pediatric neuro-oncologists building AYA-NO workflows within adult settings can provide unique expertise for AYA-NO patients with pediatric-type tumors. Growing AYA-NO clinics can benefit from allocating AYA CNS specific resources such as chemotherapy/targeted therapy provider education, a dedicated hospital/clinic space, chemotherapy nursing, a care coordinator, and a social worker with experience treating this patient population.

AI-Driven end-to-end workflow optimization and automation system for SMEs

AI-Driven end-to-end workflow optimization and automation system for SMEs

Patient-Centered Care and Process Improvement: A Systematic Review of Impacts on Satisfaction Outcomes

Patient-centered care (PCC) has emerged as a crucial approach in enhancing healthcare delivery, focusing on the needs and preferences of patients. This systematic review explores the impact of process improvement strategies on patient satisfaction outcomes within PCC frameworks. Databases including PubMed, Scopus, and Web of Science were searched for relevant studies published between 2016 and 2024, analyzing the effectiveness of process improvement interventions such as Lean, Six Sigma, and workflow optimization in various healthcare settings. Inclusion criteria focused on studies that specifically measured patient satisfaction as an outcome. The review found that process improvement initiatives positively influence patient satisfaction by streamlining care delivery, reducing wait times, and improving communication between healthcare providers and patients. However, variations in intervention types and healthcare settings highlight the need for context-specific applications. This review underscores the importance of integrating process improvement tools into PCC practices to achieve better satisfaction outcomes and improve overall care quality. Future research should focus on long-term effects and broader applications of these interventions in diverse healthcare environments.

Façade Design Pattern Optimization Workflow Through Visual Spatial Frequency Analysis and Structural Safety Assessment

As the demand for highly efficient yet aesthetically pleasing, complex building envelope structures is rising worldwide, computational analysis and generative design tools are becoming ever so relevant. Previous methods for achieving a natural distribution of structural or shading elements in non-uniform façades are mostly based either on computer-generated pseudo-randomness or a literal biomorphic approach where a naturally occurring pattern is directly projected on the façade surface. As an alternative, this research introduces a novel technique for optimisation that utilises a two-dimensional Power Spectrum Analysis, suitable for numerically assessing the alignment of designed geometry with natural patterns. By integrating this optimisation method into the design process, the façade pattern generation can be automated and optimal design can be selected by evaluating multiple design solutions. Instead of using repetitive geometrical patterns or generated pseudo-randomness, patterns objectively similar to those occurring in nature can be created without directly copying natural structures. The distribution of the structural and shading elements controls the way natural light permeates the building and, considering the data gathered from images of natural scenes, this method can be used to design structures not only with optimal structural and energy performance but also with visual and psychological occupant comfort in mind.

A paper-based analytical device for the on-site multiplexed monitoring of soil nutrients extracted with a cafetière

Sustainable agricultural production has the aim to maximise the yield and quality of harvests. For that, farmers need to monitor nutrient levels within soils to apply fertilizers accordingly and to prevent land degradation and soil exhaustion. Current methods involve time-consuming sampling and transport to a laboratory; and most farmers do not have the resources to measure frequently at multiple locations, limiting their sustainable production. In order to address this challenge, a paper-based analytical device (PAD) for the multiplexed detection of soil nutrients, i.e. phosphate, nitrate and pH, extracted with a cafetière-based method, is developed in this work. The compact and easy-to-use platform enables an accurate soil analysis in less than 20min; 3min for extraction and 15min for readout. Two detection channels for nitrate and phosphate analysis, and one circular detection area for pH, including the selective reagents to each analyte, are defined within the PAD. Upon contact with the specific nutrients, the platform produces a colorimetric response that is easily readable by naked eye and smartphone camera. The detection reactions were optimized in the range 1 − 22.5mgL-1, 10 −100mgL-1 and 5.0 – 8.5 for phosphate, nitrate and pH, respectively, in agreement with the relevant levels in soils. The volume of water, the number of pushes of the plunger, the extraction time and the mass of soil were also optimized for the nutrient extraction method with the cafetière. The optimal workflow was validated with commercial soils and compared with the conventional UV-Vis method and the labels from the soil package, showing excellent agreement. This paper-based platform provides the possibility of a cheap, sensitive and specific monitoring of soil nutrients by minimally trained operators, such as farmers, enabling in-the-field analyses of multiple key soil nutrients in resource-limited settings and therefore addressing the challenge of routine monitoring for sustainable agriculture.

Systematic Literature Review: Health Technology in Nursing

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, and AI supports predictive care and clinical decision-making. However, challenges such as data security, usability, and ethical considerations remain. Addressing these issues through training, system improvements, and ethical guidelines is essential for optimizing the benefits of digital health technologies in nursing. This review provides insights for healthcare providers and policymakers, emphasizing the importance of technology integration and support in advancing nursing practices.

Analysis of the Use of IoT in Attendance Management and Productivity Monitoring on Employee Performance and Operational Efficiency in Central Java Manufacturing Industry

This study investigates the impact of Internet of Things (IoT) usage in attendance management and productivity monitoring on employee performance and operational efficiency in the manufacturing industry of Central Java. Using a quantitative approach, data were collected from 270 respondents and analyzed with Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The results indicate that IoT-driven systems in both attendance management and productivity monitoring have a significant positive effect on employee performance and operational efficiency. Specifically, IoT-enabled attendance management improves workforce accountability and discipline, while productivity monitoring enhances real-time feedback and workflow optimization. These findings highlight the critical role of IoT technology in transforming workforce and operational management in manufacturing, contributing to improved performance and efficiency. The study provides valuable insights for decision-makers in the manufacturing industry regarding the adoption of IoT technologies to enhance competitiveness and operational outcomes.

Simulation-Based Optimization Workflow of CO2-EOR for Hydraulic Fractured Wells in Wolfcamp A Formation

Hydraulic fracturing has enabled production from unconventional reservoirs in the U.S., but production rates often decline sharply, limiting recovery factors to under 10%. This study proposes an optimization workflow for the CO2 huff-n-puff process for multistage-fractured horizontal wells in the Wolfcamp A formation in the Delaware Basin. The potential for enhanced oil recovery and CO2 sequestration simultaneously was addressed using a coupled geomechanics–reservoir simulation. Geomechanical properties were derived from a 1D mechanical earth model and integrated into reservoir simulation to replicate hydraulic fracture geometries. The fracture model was validated using a robust production history matching. A fluid phase behavior analysis refined the equation of state, and 1D slim tube simulations determined a minimum miscibility pressure of 4300 psi for CO2 injection. After the primary production phase, various CO2 injection rates were tested from 1 to 25 MMSCFD/well, resulting in incremental oil recovery ranging from 6.3% to 69.3%. Different injection, soaking and production cycles were analyzed to determine the ideal operating condition. The optimal scenario improved cumulative oil recovery by 68.8% while keeping the highest CO2 storage efficiency. The simulation approach proposed by this study provides a comprehensive and systematic workflow for evaluating and optimizing CO2 huff-n-puff in hydraulically fractured wells, enhancing the recovery factor of unconventional reservoirs.

Valorization of Historical Natural History Collections Through Digitization: The Algarium Vatova-Schiffner.

Digitization of Natural History Collections (NHCs) and mobilization of their data are pivotal for their study, preservation, and accessibility. Furthermore, thanks to digitization and mobilization, Natural History Museums can better showcase their collections, potentially attracting more visitors. However, the optimization of digitization workflows, especially when addressing small and/or historical NHCs, remains a challenge. Starting from a practical example, this contribution aims at providing a general guideline for the digitization of historical NHCs, with a particular focus on pre-digitization planning, during which some decisions should be made for ensuring a smooth, cost- and time-effective digitization process. The digitization of the algarium by Aristocle Vatova and Victor Schiffner was carried out following an image-to-data workflow, which allowed for reducing the handling of the specimens. The metadata were organized according to the Darwin Core standard scheme, and, together with the digital images of the specimens, have been made available to the scientific community and to the general public via an online portal. Thanks to the application of digital technologies and standardized methods, the accessibility of the collection has been enhanced, and its integration with historical data is possible, highlighting the relevance of shared experiences and protocols in advancing the digital transformation of natural history heritage.

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Multicancer Early Detection Tests: A State-of-the-Art Review for Otolaryngologists.

To provide a review of the science and applicability of current multi-cancer early detection (MCED) tests for otolaryngologists. PubMed, clinicaltrials.gov, company websites. Using PRISMA methodology, primary literature regarding MCED tests was queried from April 26 to May 12, 2024 using MCED search terms. Ongoing clinical trials incorporating MCED screens were identified via the National Institutes of Health clinicaltrials.gov website. Company websites for available or upcoming MCED tests were reviewed. Long-term robust data regarding the performance characteristics, effects on clinical outcomes, and cost-utility of MCED tests for head and neck cancer are currently lacking. Otolaryngologists should be aware of the implications of MCED tests as these assays become more widely used. Although not FDA-approved or covered by insurances at the time of writing of this manuscript, MCED testing is rapidly gaining interest, and patients with positive tests are presenting to otolaryngologists for evaluation. While MCED technologies hold great promise for early detection of disease and potential reduction of morbidity and mortality, more study is needed about their utility for head and neck cancer and optimal diagnostic workflows.

Unsung Hero: Artificial Lift Boosts Production Without Breaking the Bank

_ In the quest to cost-effectively boost production, operators are experimenting with artificial lift methods and how digital tech can boost its performance. Artificial lift experts are increasingly adding artificial intelligence (AI), machine learning (ML), and autonomous operations into their workflows because these data-driven technologies are demonstrating they can generate uplift when they are thoughtfully developed and deployed. Operators are also looking at the performance of high-pressure gas lift (HPGL) wells compared to wells using electrical submersible pumps (ESPs) for artificial lift. Finally, operators sometimes have to decide whether to risk replacing equipment that seems to be functioning, even if at subpar levels, in a bid to increase production. Digital Boost Optimized gas lift workflows and autonomously implemented ESP set points are helping ExxonMobil and Vital Energy produce more oil. Gas lift is a popular artificial lift method partly because the system is simple, robust, and inexpensive to operate, but optimizing it has historically been time-consuming. SPE 219553 outlines ExxonMobil’s approach to automating gas lift optimization for wells in the Permian Basin. The resulting workflow, which relies on AI and ML, generated a 2.2% uplift in production at the more than 1,300 wells where it was deployed, without requiring changes to surface or downhole equipment or generating additional work for personnel. Derek Burmaster, production optimization engineer for ExxonMobil Upstream Integrated Solutions, said during SPE’s Artificial Lift Conference and Exhibition (ALCE) in August that one of the big benefits of applying the closed-loop iterative well-by-well gas lift optimization workflow is that it removes the need for an engineer or specialist to have to go into the field repeatedly to change injection rates and analyze the well’s data. “For each well, that might take a few hours, at least,” he said. “We’ve done this on hundreds and hundreds of wells, and it happens every month without anybody, any manpower, or anything. So that’s one of the huge benefits of doing this in a data-driven manner.” Gas lift is so robust that it can be challenging to diagnose if the system is operating in a suboptimal state, the paper noted. Changes in a well’s water cut or productivity can cause a previously optimized system to lose efficiency, which may not otherwise be known for years. ExxonMobil was seeking a method to optimize gas lift that would continuously monitor the state of the system and respond immediately. The resulting closed-loop software iteratively performs multirate tests, analyzes the results, and remotely implements set-point changes to optimize the wells. “The optimization process is most effective in an iterative form, in which each multirate test produces a model that suggests a given change,” the paper stated. While each model produces its own optimal injection rate, subsequent models may point to the same injection rate, and thus changes are not always made, Burmaster noted. Even if an initially suggested set point is not optimal, it will “push the well in the right direction,” which improves the starting point for the next test and helps the well reach an optimal set point over the course of a few iterations, according to the paper. The workflow was tested in two different stages, with the first 3-month stage requiring manual approval of the recommended set points.

DevOps workflow optimization: Enhancing deployment and efficiency for cloud application

DevOps has quickly become an essential process for cloud software in the contemporary world of utilizing software. However, questions regarding the efficiency of the work flow and speed of application deployment still prevails especially when implemented under cloud environment. This paper focuses on the workflow optimization techniques of DevOps including automation of work, integration and deployment processes CI/CD, Infrastructure to code IaC, and monitoring. The aim is to give guidance on how to increase the velocity of deployment and operation when it comes to applications hosted in the cloud. The information presented from the evaluation of the main optimization strategies can help organizations to enhance the overall cycle time and improve the quality of the products at the same time.

Emergency department discharges directly to hospice: Longitudinal assessment of a streamlined referral program

Introduction80 % of Americans wish to die somewhere other than a hospital, and hospice is an essential resource for providing such care. The emergency department (ED) is an important location for identifying patients with end-of-life care needs and providing access to hospice. The objective of this study was to analyze a quality improvement (QI) program designed to increase the number of patients referred directly to hospice from the ED, without the need for an observation stay and without access to in-hospital hospice. MethodsWe implemented a QI program in September 2021 consisting of three components: (1) clarification and streamlining of referral workflows, (2) staff/provider education on hospice and workflows, and (3) electronic medical record (EMR) tools to facilitate hospice transitions. The primary outcome was the change in monthly ED-to-hospice cases pre- and post-implementation. We also calculated the monthly incidence rate of ED-to-hospice transfers. The secondary outcome was ED length of stay (LOS). Results202 patients completed ED-to-hospice transfers from January 1, 2019 to February 29, 2024. 98 patients transitioned from the ED to hospice before QI implementation, and 104 patients transitioned after implementation. We observed a slight but insignificant increase in the mean monthly ED-to-hospice cases from 3.16 patients per month pre-implementation to 3.47 patients per month post-implementation (P = 0.46). We found no significant difference in the monthly incidence rate of ED-to-hospice cases before and after implementation (P = 0.78). ED LOS was unaffected (P = 0.21). ConclusionIn this largest study to date on direct ED-to-hospice discharges, a QI program focused on workflow optimization, education, and EMR modification was insufficient to significantly impact ED-to-hospice discharges. Future efforts to increase hospice transitions from the ED should investigate methods to improve patient identification, the impact of in-hospital hospice programs, and coordination with hospital and community teams to support home-based care for those desiring to remain there.

Artificial intelligence in cardiology: a peek at the future and the role of ChatGPT in cardiology practice.

Artificial intelligence has increasingly become an integral part of our daily activities. ChatGPT, a natural language processing technology developed by OpenAI, is widely used in various industries, including healthcare. The application of ChatGPT in healthcare is still evolving, with studies exploring its potential in clinical decision-making, patient education, workflow optimization, and scientific literature. ChatGPT could be exploited in the medical field to improve patient education and information, thus increasing compliance. ChatGPT could facilitate information exchange on major cardiovascular diseases, provide clinical decision support, and improve patient communication and education. It could assist the clinician in differential diagnosis, suggest appropriate imaging modalities, and optimize treatment plans based on evidence-based guidelines. However, it is unclear whether it will be possible to use ChatGPT for the management of patients who require rapid decisions. Indeed, many drawbacks are associated with the daily use of these technologies in the medical field, such as insufficient expertise in specialized fields and a lack of comprehension of the context in which it works. The pros and cons of its use have been explored in this review, which was not written with the help of ChatGPT.

Benchmarking whole exome sequencing in the German network for personalized medicine

IntroductionWhole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. MethodsTo assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics. Somatic and germline variants, copy-number alterations (CNAs), and complex biomarkers were investigated. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. The raw data were collected and re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. ResultsThe mean positive percentage agreement (PPA) of somatic variant calling was 76 % while the positive predictive value (PPV) was 89 % in relation to a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88 % for all and 97 % for the clinically relevant variants. CNA calls were concordant for 82 % of genomic regions. Homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94 %, 93 %, and 93 % of calls, respectively. Variability of CNAs and complex biomarkers did not decrease considerably after harmonization of the bioinformatic processing and was hence attributed mainly to wet-lab differences. ConclusionContinuous optimization of bioinformatic workflows and participating in round robin tests are recommended.