The measure of impact: Proposal of quality metrics for solid organ transplant pharmacy practice.

As healthcare continues its transition toward value-based care, it is increasingly important for transplant pharmacists to demonstrate their impact on patient care, health-related outcomes, and healthcare costs. Evidence-based quality and performance metrics are recognized as crucial tools for measuring the value of service. Yet, there is a lack of well-developed and agreed-upon specific metrics for many clinical pharmacy specialties, including solid organ transplantation. To address this need, a panel of transplant pharmacy specialists conducted a detailed literature review and engaged in several panel discussions to identify quality metrics to be considered for assessing the value of clinical pharmacy services provided to solid organ transplant recipients and living donors. The proposed metrics are based on the Donabedian model and are categorized to coincide with the typical phases of transplant care. The measures focus on key issues that arise in transplant recipients related to medication therapy, including adverse drug events, nonadherence, and clinical outcomes attributable to medication therapy management. This article proposes a comprehensive set of measures, any number of which transplant pharmacists can adopt and measure over time to objectively gauge the value of services they are providing to transplant recipients, the transplant center, and the overall healthcare system.

A comprehensive approach to continuous quality improvement of massive transfusion by developing key performance indicators.

BACKGROUND AND OBJECTIVES: To develop key performance indicators (KPI) for use in quality assessment of our institutional goal-directed massive transfusion (GDMT). MATERIALS AND METHODS: A team comprising our transfusion and emergency medicine departments carried out a cross-sectional data analysis of GDMT in adult patients from January 2021 to December 2022. The study was rooted in the Define, Measure, Analyse, Improve, Control (DMAIC) approach. Features of KPIs were (a) importance, (b) scientific soundness and (c) feasibility. Study parameters were defined and analysed using measures of central tendencies and benchmark comparison. RESULTS: Ninety-two massive transfusion events occurred and 1405 blood components were used. Trauma was the leading cause, followed by postpartum haemorrhage and upper gastrointestinal bleeding. Appropriate GDMT activation was observed only in 43.47% of events. The turnaround time (TAT) was within the benchmark in 85.8% of events with an average of 16 ± 10 min. The average utilization of blood components was 20.5 (interquartile range [IQR] = 11.3) in the appropriate group and 5.5 (IQR = 4.25) in the inappropriate group with a wastage rate of 3.5%. Duration of activation was 6.19 ± 4.59 h, and the adherence to thromboelastography was 66.3%. Overall mortality was 45.65%, and the average duration of hospital stay was 6.1 ± 5.9 days. CONCLUSION: The KPIs developed were easy to capture, and the analysis provided a comprehensive approach to the quality improvement of the GDMT protocol.

Patient-perceived barriers to early initiation of prenatal care at a large, urban federally qualified health center: a mixed-methods study.

BACKGROUND: Early initiation of prenatal care is widely accepted to improve the health outcomes of pregnancy for both mothers and their infants. Identification of the various barriers to entry into care that patients experience may inform and improve health care provision and, in turn, improve the patient's ability to receive necessary care. AIM: This study implements a mixed-methods approach to establish methods and procedures for identifying barriers to early entry to prenatal care in a medically-vulnerable patient population and areas for future quality improvement initiatives. METHODS: An initial chart review was conducted on obstetrics patients that initiated prenatal care after their first trimester at a large federally qualified health center in Brooklyn, NY, to determine patient-specified reasons for delay. A thematic analysis of these data was implemented in combination with both parametric and non-parametric analyses to characterize the population of interest, and to identify the primary determinants of delayed entry. RESULTS: The age of patients in the population of interest (n = 169) was bimodal, with a range of 15 - 43 years and a mean of 28 years. The mean gestational age of entry into prenatal care was 19 weeks. The chart review revealed that 8% recently moved to Brooklyn from outside of NYC or the USA. Nine percent had difficulty scheduling an initial prenatal visit within their first trimester. Teenage pregnancy accounted for 7%. Provider challenges with documentation (21%) were noted. The most common themes identified (n = 155) were the patient being in transition (21%), the pregnancy being unplanned (17%), and issues with linkage to care (15%), including no shows or patient cancellations. Patients who were late to prenatal care also differed from their peers dramatically, as they were more likely to be Spanish-speaking, to be young, and to experience a relatively long delay between pregnancy confirmation and entry into care. Moreover, the greatest determinant of delayed entry into care was patient age. CONCLUSION: Our study provides a process for other like clinics to identify patients who are at risk for delayed entry to prenatal care and highlight common barriers to entry. Future initiatives include the introduction of a smart data element to document reasons for delay and use of community health workers for dedicated outreach after no show appointments or patient cancellations.

Decoding the persistence of delayed hospital discharge: An in-depth scoping review and insights from two decades.

OBJECTIVE: This article addresses the persistent challenge of Delayed Hospital Discharge (DHD) and aims to provide a comprehensive overview, synthesis, and actionable, sustainable plan based on the synthesis of the systematic review articles spanning the past 24 years. Our research aims to comprehensively examine DHD, identifying its primary causes and emphasizing the significance of effective communication and management in healthcare settings. METHODS: We conducted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) method for synthesizing findings from 23 review papers published over the last two decades, encompassing over 700 studies. In addition, we employed a practical and comprehensive framework to tackle DHD. Rooted in Linderman's model, our approach focused on continuous process improvement (CPI), which highlights senior management commitment, technical/administrative support, and social/transitional care. Our proposed CPI method comprised several stages: planning, implementation, data analysis, and adaptation, all contributing to continuous improvement in healthcare delivery. This method provided valuable insights and recommendations for addressing DHD challenges. FINDINGS: Our DHD analysis revealed crucial insights across multiple dimensions. Firstly, examining causes and interventions uncovered issues such as limited discharge destinations, signaling unsustainable solutions, and inefficient care coordination. The second aspect explored the patient and caregiver experience, emphasizing challenges linked to staff uncertainty and negative physical environments, with notable attention to the underexplored area of caregiver experience. The third theme explored organizational and individual factors, including cognitive impairment and socioeconomic influences. The findings emphasized the importance of incorporating patients' data, recognizing its complexity and current avoidance. Finally, the role of transitional and social care and financial strategies was scrutinized, emphasizing the need for multicomponent, context-specific interventions to address DHD effectively. CONCLUSION: This study addresses gaps in the literature, challenges prevailing solutions, and offers practical pathways for reducing DHD, contributing significantly to healthcare quality and patient outcomes. The synthesis introduces the vital CPI stage, enhancing Linderman's work and providing a pragmatic framework to eradicate delayed discharge. Future efforts will address practitioner consultations to enhance perspectives and further enrich the study. PATIENT OR PUBLIC CONTRIBUTION: Our scoping review synthesizes and analyzes existing systematic review articles and emphasizes offering practical, actionable solutions. While our approach does not directly engage patients, it strategically focuses on extracting insights from the literature to create a CPI framework. This unique aspect is intentionally designed to yield tangible benefits for patients, service users, caregivers, and the public. Our actionable recommendations aim to improve hospital discharge processes for better healthcare outcomes and experiences. This detailed analysis goes beyond theoretical considerations and provides a practical guide to improve healthcare practices and policies.

Exploring the use of social network analysis methods in process improvement within healthcare organizations: a scoping review.

BACKGROUND: Communication breakdowns among healthcare providers have been identified as a significant cause of preventable adverse events, including harm to patients. A large proportion of studies investigating communication in healthcare organizations lack the necessary understanding of social networks to make meaningful improvements. Process Improvement in healthcare (systematic approach of identifying, analyzing, and enhancing workflows) is needed to improve quality and patient safety. This review aimed to characterize the use of SNA methods in Process Improvement within healthcare organizations. METHODS: Relevant studies were identified through a systematic search of seven databases from inception - October 2022. No limits were placed on study design or language. The reviewers independently charted data from eligible full-text studies using a standardized data abstraction form and resolved discrepancies by consensus. The abstracted information was synthesized quantitatively and narratively. RESULTS: Upon full-text review, 38 unique articles were included. Most studies were published between 2015 and 2021 (26, 68%). Studies focused primarily on physicians and nursing staff. The majority of identified studies were descriptive and cross-sectional, with 5 studies using longitudinal experimental study designs. SNA studies in healthcare focusing on process improvement spanned three themes: Organizational structure (e.g., hierarchical structures, professional boundaries, geographical dispersion, technology limitations that impact communication and collaboration), team performance (e.g., communication patterns and information flow among providers., and influential actors (e.g., key individuals or roles within healthcare teams who serve as central connectors or influencers in communication and decision-making processes). CONCLUSIONS: SNA methods can characterize Process Improvement through mapping, quantifying, and visualizing social relations, revealing inefficiencies, which can then be targeted to develop interventions to enhance communication, foster collaboration, and improve patient safety.

Increasing and sustaining discharges by noon - a multi-year process improvement project.

High hospital occupancy degrades emergency department performance by increasing wait times, decreasing patient satisfaction, and increasing patient morbidity and mortality. Late discharges contribute to high hospital occupancy by increasing emergency department (ED) patient length of stay (LOS). We share our experience with increasing and sustaining early discharges at a 650-bed academic medical center in the United States. Our process improvement project followed the Institute of Medicine Model for Improvement of successive Plan‒Do‒Study‒Act cycles. We implemented multiple iterative interventions over 41 months. As a result, the proportion of discharge orders before 10 am increased from 8.7% at baseline to 22.2% (p < 0.001), and the proportion of discharges by noon (DBN) increased from 9.5% to 26.8% (p < 0.001). There was no increase in balancing metrics because of our interventions. RA-LOS (Risk Adjusted Length Of Stay) decreased from 1.16 to 1.09 (p = 0.01), RA-Mortality decreased from 0.65 to 0.61 (p = 0.62) and RA-Readmissions decreased from 0.92 to 0.74 (p < 0.001). Our study provides a roadmap to large academic facilities to increase and sustain the proportion of patients discharged by noon without negatively impacting LOS, 30-day readmissions, and mortality. Continuous performance evaluation, adaptability to changing resources, multidisciplinary engagement, and institutional buy-in were crucial drivers of our success.

Community-engaged Systems for Population Health Improvement: A Novel Approach to Improve Diabetes Outcomes in Rural Communities.

BACKGROUND: Approaches to prevent and manage diabetes at a community population level are hindered because current strategies are not aligned with the structure and function of a community system. We describe a community-driven process based on local data and rapid prototyping as an alternative approach to create diabetes prevention and care management solutions appropriate for each community. We report on the process and provide baseline data for a 3-year case study initiative to improve diabetes outcomes in two rural Nebraska communities. METHODS: We developed an iterative design process based on the assumption that decentralized decision-making using local data feedback and monitoring will lead to the innovation of local sustainable solutions. Coalitions act as community innovation hubs and meet monthly to work through a facilitated design process. Six core diabetes measures will be tracked over the course of the project using the electronic health record from community clinics as a proxy for the entire community. RESULTS: Baseline data indicate two-thirds of the population in both communities are at risk for prediabetes based on age and body mass index. However, only a fraction (35% and 12%) of those at risk have been screened. This information led both coalitions to focus on improving screening rates in their communities. DISCUSSION: In order to move a complex system towards an optimal state (e.g., improved diabetes outcomes), stakeholders must have access to continuous feedback of accurate, pertinent information in order to make informed decisions. Conventional approaches of implementing evidence-based interventions do not facilitate this process.

Modeling-based Approach Towards Quality by Design for a Telescoped Process.

A telescoped, two-step synthesis was investigated by applying Quality by Design principles. A kinetic model consisting of 12 individual reactions was successfully established to describe the synthesis and side reactions. The resulting model predicts the effects of changes in process parameters on total yield and quality. Contour plots were created by varying process parameters and displaying the model predicted process response. The areas in which the process response fulfils predetermined quality requirements are called design spaces. New ranges for process parameters were explored within these design spaces. New conditions were found that increased the robustness of the process and allowed for a considerable reduction of the used amounts of a reagent. Further optimizations, based on the newly generated knowledge, are expected. Improvements can either be direct process improvements or enhancements to control strategies. The developed strategies can also be applied to other processes, enhancing upcoming and preexisting research and development efforts.

Assessing trends in breast care surveillance metrics after implementing surgeon-specific tracking and performance reporting in a large, integrated cancer network.

BACKGROUND: There are few quality metrics and benchmarks specific to surgical oncology. Development of a surgeon-level performance metrics system based on peer comparisons is hypothesized to positively influence surgical decision-making. This study established a tracking and reporting system comprised of evidence and consensus-based metrics to assess breast care delivered by individual surgeons. METHODS: Surgeons' performance is assessed by a surveillance tracking system of metrics pertaining to referrals and surgical elements. This retrospective analysis of prospectively collected breast care data reports on recurring 6-month and cumulative data from nine care locations from 2015 to 2021. RESULTS: Breast care was provided to 6659 patients by 41 surgeons. A total of 27 breast care metrics were evaluated over 7 years. Metrics with consistent, proficient results were retired after 18 months, including the rate of core biopsy, specimen orientation, and referrals to medical oncology, genetics, and fertility, among others. In clinically node-negative, hormone receptor-positive patients 70 years of age or older, the cumulative rate of sentinel lymph node (SLN) biopsy significantly decreased by 40% over 5.5 years (p < .001). The overall breast conservation rate for T0-T2 cancer increased 10% over 7 years. At the surgeon level, improvements were made in the median number of SLNs removed and in operative note documentation. CONCLUSIONS: Implementation of a surgeon-specific, peer comparison-based metric and tracking system has yielded substantive changes in breast care management. This process and governance structure can serve as a model for quantification of breast care at other institutions and for other disease sites.

A systematic review of the evidence of how hospitals capture financial benefits of process improvement and the impact on hospital financial performance.

BACKGROUND: Governments, funders and hospital managers around the world are looking for ways to address the continual growth in expenditure by reducing the level of waste in the healthcare delivery system and improving the value of care provided to patients. Process improvement methods are applied to increase high value care, reduce low value care and remove waste from care processes. The purpose of this study is to review the literature to identify the methods used by hospitals to measure and capture financial benefits from PI initiatives to identify best practice. The review also pursues the way hospitals collate these benefits at the enterprise level to achieve improved financial performance. METHODS: A systematic review was undertaken in line with the PRISMA process and employed qualitative research methods. Databases searched were Medline, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINHAL), Web of Science and SCOPUS. The initial search was conducted in in July 2021 with a follow up search conducted in February 2023 using the same search terms and databases to identify additional studies published in the intervening period. The search terms were identified through the PICO (Participants, Interventions, Comparisons and Outcomes) method. RESULTS: Seven papers were identified that reported reduction in care process waste or improvement of the value of care using an evidence-based PI approach and included financial benefits analysis. Positive financial impact was measured for the PI initiatives but none of the studies reported how these financial benefits were captured or applied at the enterprise level. Three of the studies suggested that sophisticated cost accounting systems were required to enable this. CONCLUSION: The study demonstrates the paucity of literature in the field of PI and financial benefits measurement in healthcare. Where financial benefits are documented, they vary in terms of cost inclusions and the 'level' at which the costs were measured. Further research on best practice financial measurement methods is needed to enable other hospitals to measure and capture financial benefits arising from their PI programs.

Business-centric data solutions for safeguarding animal agriculture in the United States of America.

Business-centric solutions to data-related problems often yield the greatest positive impacts and improvements for private enterprises but are challenging to design and implement at scale within government agencies. The core mission of the Veterinary Services of the United States Department of Agriculture (USDA) Animal Plant Health Inspection Service is to safeguard animal agriculture in the United States of America, and effective data management underpins these efforts. As this agency works to assist data-driven decision-making in animal health management, it continues to use a blend of best practices from Federal Data Strategy initiatives and the International Data Management Association framework. This paper describes three case studies that focus on strategies to improve animal health data collection, integration, reporting and governance for animal health authorities. These strategies have enhanced the way USDA's Veterinary Services execute their mission and core operational activities for prevention, detection and early response to support disease containment and control.

S'agissant des problèmes en lien avec les données, les solutions centrées sur l'activité sont souvent celles qui génèrent le plus d'effets positifs et d'améliorations pour les entreprises du secteur privé, mais elles sont difficiles à concevoir et à mettre en oeuvre à grande échelle au sein des agences gouvernementales. Les Services vétérinaires du Service d'inspection de la santé animale et végétale du département américain de l'Agriculture (USDA) ont pour mission centrale de préserver les productions animales états-uniennes ; une gestion efficace des données vient soutenir cet effort. Dans leur action d'appui aux processus décisionnels de gestion de la santé animale fondés sur les données, ces Services recourent à une combinaison de bonnes pratiques mises en oeuvre aussi bien par les initiatives de la Stratégie fédérale sur les données que dans le cadre de l'Association internationale de gestion des données. Les auteurs décrivent trois études de cas sur des stratégies visant à améliorer la collecte, l'intégration, la notification et la gouvernance des données de santé animale afin de répondre aux besoins des autorités compétentes dans ce domaine. Ces stratégies ont permis aux Services vétérinaires de l'USDA de mieux s'acquitter de leur mission et d'améliorer leurs activités opérationnelles de prévention, de détection et de réaction rapide afin d'endiguer et contrôler les maladies.

Las soluciones eminentemente empresariales a problemas relacionados con los datos deparan con frecuencia los mejores frutos y resultados a la empresa privada, pero son difíciles de diseñar y aplicar a escala dentro de las administraciones públicas. Los Servicios Veterinarios adscritos al Servicio de Inspección Sanitaria de Animales y Plantas del Departamento de Agricultura de los Estados Unidos (USDA) tienen por principal cometido salvaguardar la producción animal estadounidense, labor que pasa en parte por una eficaz gestión de los datos. En su función de apoyo a la adopción de decisiones de gestión zoosanitaria basadas en los datos, este organismo sigue empleando una combinación de prácticas óptimas tomadas de iniciativas de la Estrategia Federal de Datos y de las pautas marcadas por la Asociación Internacional de Gestión de Datos. Los autores presentan y analizan tres ejemplos de estrategias para mejorar la obtención, integración, notificación y administración de datos zoosanitarios para las autoridades del ramo. Estas estrategias han conferido mayor eficacia a los Servicios Veterinarios del USDA en el cumplimiento de su misión y en la ejecución de sus principales actividades operativas de prevención, detección y pronta respuesta para ayudar a contener y combatir enfermedades.

Improving the resident assessment process: application of App-based e-training platform and lean thinking.

BACKGROUND: The assessment system for standardized resident training is crucial for developing competent doctors. However, it is complex, making it difficult to manage. The COVID-19 pandemic has also aggravated the difficulty of assessment. We, therefore, integrated lean thinking with App-based e-training platform to improve the assessment process through Define-Measure-Analyze-Improve-Control (DMAIC) cycles. This was designed to avoid unnecessary activities that generate waste. METHODS: Panels and online surveys were conducted in 2021-2022 to find the main issues that affect resident assessment and the root causes under the frame of waste. An online app was developed. Activities within the process were improved by brainstorming. Online surveys were used to improve the issues, satisfaction, and time spent on assessment using the app. RESULTS: A total of 290 clinical educators in 36 departments responded to the survey, and 153 clinical educators used the online app for assessment. Unplanned delay or cancellation was defined as the main issue. Eleven leading causes accounted for 87.5% of the issues. These were examiner time conflict, student time conflict, insufficient examiners, supervisor time conflict, grade statistics, insufficient exam assistants, reporting results, material archiving, unfamiliarity with the process, uncooperative patients, and feedback. The median rate of unplanned delay or cancellation was lower with use of the app (5% vs 0%, P < 0.001), and satisfaction increased (P < 0.001). The median time saved by the app across the whole assessment process was 60 (interquartile range 60-120) minutes. CONCLUSIONS: Lean thinking integrated with an App-based e-training platform could optimize the process of resident assessment. This could reduce waste and promote teaching and learning in medical education.

Evaluation of patient transport service in hospitals using process mining methods: Patients' perspective.

Designing healthcare facilities and their processes is a complex task which influences the quality and efficiency of healthcare services. The ongoing demand for healthcare services and cost burdens necessitate the application of analytical methods to enhance the overall service efficiency in hospitals. However, the variability in healthcare processes makes it highly complicated to accomplish this aim. This study addresses the complexity in the patient transport service process at a German hospital, and proposes a method based on process mining to obtain a holistic approach to recognise bottlenecks and main reasons for delays and resulting high costs associated with idle resources. To this aim, the event log data from the patient transport software system is collected and processed to discover the sequences and the timeline of the activities for the different cases of the transport process. The comparison between the actual and planned processes from the data set of the year 2020 shows that, for example, around 36% of the cases were 10 or more minutes delayed. To find delay issues in the process flow and their root causes the data traces of certain routes are intensively assessed. Additionally, the compliance with the predefined Key Performance Indicators concerning travel time and delay thresholds for individual cases was investigated. The efficiency of assignment of the transport requests to the transportation staff are also evaluated which gives useful understanding regarding staffing potential improvements. The research shows that process mining is an efficient method to provide comprehensive knowledge through process models that serve as Interactive Process Indicators and to extract significant transport pathways. It also suggests a more efficient patient transport concept and provides the decision makers with useful managerial insights to come up with efficient patient-centred analysis of transportation services through data from supporting information systems.

Transferring critical pediatric patients from emergency department to intensive care: A quality improvement initiative.

BACKGROUND: Transfer of care, moving hospitalized patients between care areas, is a critical point of vulnerability for healthcare organizations. Patient information handoff is an essential activity occurring frequently in hospital environments. Poor communication has been linked with adverse events and poor patient outcomes. This evidence-based quality project aimed to enhance the handoff process between the Emergency Department (ED) and Pediatric Intensive Care Unit (PICU) by standardizing transfer of care steps. This was accomplished through customizing a reporting tool to contain all the information the receiving department deemed necessary for safe patient care. METHODS: A customized situation, background, assessment, recommendation (SBAR) form handoff tool was developed for ED to PICU transfers. This SBAR tool included information that PICU nurses identified as critical to transfer of care. Nurse perceptions were surveyed pre- and post-implementation. Patient safety event reports were tracked to evaluate events related to transfer of care before and after the practice change. FINDINGS: An increased number of PICU nurses agreed the customized handoff tool was complete and organized. Additionally, more nurses agreed that handoff gave all information needed to safely care for critically ill patients transferred from the ED. Lastly, bedside patient checks increased, and patient safety events related to transfer of care decreased. DISCUSSION: This project demonstrated that implementation of a standardized transfer of care process coupled with a customized handoff tool increased PICU nurse perceptions that handoff was organized, and all information needed to safely care for critically ill patients was conveyed. APPLICATION TO PRACTICE: Transfer of care processes between the ED and PICU should be standardized. The use of customized tools may improve information exchange between nurses and ensure that all vital patient information is communicated.

Blockchain applicability in the management of urban water supply and sanitation systems in Spain.

Blockchain constitutes a disruptive technology that is currently changing business models and the way organizations operate. This paper explores the applicability of blockchain technology, and of distributed ledger technologies in general, to urban water supply and sanitation services in Spain. The potential of this technology for improving processes in this sector is assessed through a specific methodology of strategic analysis developed for this purpose. First, the technical, legal and managerial factors that condition the potential use of this technology to address the global, operational and governance challenges faced by urban water management are explored. Second, strategic analysis tools (e.g. value chain, factors of competition, and benchmarking) are used to model a water utility organization as a set of processes and characterize blockchain as an enabling technology with both benefits (traceability, immutability, and disintermediation) and limitations. Based on cost-benefit analysis, use cases in which the implementation of a blockchain could improve the organization's performance can be discerned. The results identify the processes and sub-processes of urban water utility management for which the use of a blockchain could improve performance: comprehensive maintenance, the management of serious incidents, and supplier management. Essentially, the methodology developed identifies management processes whose requirements are efficiently met through automation derived from blockchain solutions. Regardless of the management models currently in place in Spain, the traceability and disintermediation benefits of blockchain solutions can help to overcome governance and efficiency challenges associated with the management of urban water supply and sanitation services.

The Optimization of the Synthesis Process and the Identification of Levobupivacaine Hydrochloride.

In this study, we not only optimized and improved the synthesis process of levobupivacaine hydrochloride (21) but also conducted a comprehensive exploration of critical industrial-scale production details, and a novel high-performance liquid chromatography (HPLC) analysis method was developed. Starting with the readily available and cost-effective (R,S)-N-(2,6-dimethylphenyl)piperidine-2-carboxamide (28) as the initial material and utilizing l-(-)-dibenzoyl tartaric acid (29) for chiral separation, and then through substitution and a salting reaction, levobupivacaine hydrochloride (21) was obtained with high purity (chemical purity of 99.90% and enantiomeric excess (ee) values of 99.30%). The total yield of the three steps was 45%. Structures of intermediates and the final product were confirmed using nuclear magnetic resonance (NMR) (1H NMR, 13C NMR), mass spectrometry (MS), and elemental analysis. The crystal structure of the final product was determined through differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and X-ray diffraction (XRD). Furthermore, we evaluated the risk of the substitution reaction using a reaction calorimeter and accelerating rate calorimetry (ARC). This process offers the advantages of simple operation, greenness, safety, controllable quality, and cost-effectiveness. It provides reliable technical support for the industrial-scale production of levobupivacaine hydrochloride (21), which is of significant importance in meeting clinical demands. Pilot-scale production has already been successfully completed by China National Medicines Guorui Pharmaceutical Co., Ltd., with a production scale of 20 kg.

[Lean strategy for data mining and continuous improvement of Chinese pharmaceutical process: a case study of sporoderm-removal Ganoderma lucidum spore powder].

In the digital transformation of Chinese pharmaceutical industry, how to efficiently govern and analyze industrial data and excavate the valuable information contained therein to guide the production of drug products has always been a research hotspot and application difficulty. Generally, the Chinese pharmaceutical technique is relatively extensive, and the consistency of drug quality needs to be improved. To address this problem, we proposed an optimization method combining advanced calculation tools(e.g., Bayesian network, convolutional neural network, and Pareto multi-objective optimization algorithm) with lean six sigma tools(e.g., Shewhart control chart and process performance index) to dig deeply into historical industrial data and guide the continuous improvement of pharmaceutical processes. Further, we employed this strategy to optimize the manufacturing process of sporoderm-removal Ganoderma lucidum spore powder. After optimization, we preliminarily obtained the possible interval combination of critical parameters to ensure the P_(pk) values of the critical quality properties including moisture, fineness, crude polysaccharide, and total triterpenes of the sporoderm-removal G. lucidum spore powder to be no less than 1.33. The results indicate that the proposed strategy has an industrial application value.

If Time is Neuron, What Are We Waiting for?

How to cite this article: Samavedam S. If Time is Neuron, What Are We Waiting for? Indian J Crit Care Med 2023;27(2):87-88.

X-ray tomography for the advancement of laser powder bed fusion additive manufacturing.

X-ray computed tomography is a powerful tool to nondestructively inspect additively manufactured parts. Additive manufacturing of metals, especially laser powder bed fusion, is increasingly being adopted for serial production of critical components in aerospace, automotive and various other industries. The technology holds huge potential for more efficient material usage and light weighting of components, among the many advantages. As this new production method is being ramped up and refined in various industry sectors, X-ray tomography is critical to the advancement of the quality of the produced components. X-ray tomography allows the nondestructive evaluation of the structural integrity of the parts produced, which in turn provides confidence in the expected performance of the parts. Besides final inspection of parts for porosity/defects and dimensional tolerances for a pass/fail decision, X-ray tomography also has a critical role to play in advancing and improving the additive manufacturing processes. This process improvement refers to the inspection of small representative coupon samples on a microscopic scale, in order to optimize the process parameters such as laser power, speed, scan strategy and various others. In this work, we describe the evaluation of small solid cube coupon samples and lattice structure coupon samples. These examples are meant to improve the understanding of the potential of X-ray tomography in advancing additive manufacturing processes (in contrast to its usual use for nondestructive testing of final parts), thereby providing support towards qualification of these processes and the parts produced in these processes. X-ray tomography, therefore, plays a key role in the adoption and qualification of high-quality metal additive manufacturing.

The role of implementation science in improving epilepsy surgery utilization.

Randomized controlled studies demonstrated that patients with intractable epilepsy could benefit significantly more from epilepsy surgery than from continuing medical therapy. Unfortunately, robust efforts over the last few decades, including the formation and dissemination of guidelines and practice parameters, did not improve the utilization of epilepsy surgery. Epilepsy surgery remains one of the most underutilized evidence-based interventions in modern medicine. A new scientific study of methods has emerged to improve uptake of evidence-based practices, named implementation science (IS). Despite its tremendous rise in popularity in various domains, its usage to mitigate epilepsy surgery underutilization is very limited. In fact, the application of principles and methods of IS are somewhat restricted in the entire neuroscience field, where quality improvement (QI) efforts primarily drive the provision of high-quality health care. Although both QI efforts and IS have a similar goal of improving healthcare quality, they differ significantly in associated terminologies, concepts, and approaches. For implementing high-quality, evidence-based practices in routine clinical settings, we need a better understanding of IS methods and closer integration between QI and IS fields. Recognizing a dearth of awareness of IS in the neuroscience community, the first part of the review addresses the fundamentals of IS, focusing on multifaceted implementation strategies that neurologists can apply in their clinical practice. In the second part of the review, an entire illustrative case is presented to familiarize neurologists with the practical application of diverse implementation strategies to mitigate the underutilization of epilepsy surgery.