Improve Service Delivery Research Articles

Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation

ObjectivesRisk stratification tools that predict healthcare utilisation are extensively integrated into primary care systems worldwide, forming a key component of anticipatory care pathways, where high-risk individuals are targeted by preventative...

საჯარო-კერძო პარტნიორობის შესაძლებლობები და გამოწვევები საქართველოს მაგალითზე

In the modern world, public-private partnerships (PPPs) are becoming an increasingly popular tool for infrastructure and public service delivery worldwide. As an innovative approach to public procurement, PPPs, the possibilities of public-private partnerships in public administration have also attracted significant attention from academic circles, which makes the study of the issue even more interesting and relevant. In general, the governance literature emphasizes the role of markets, networks, and non-state actors. In doing so, it weakens the distinction between states and other spheres of social order. All social and political regimes seem to depend on a model or form of government, however informal it may be. Global support for public-private partnerships (PPPs) in infrastructure appears stronger than ever. Discussions at a number of summits over the past few years have increasingly focused on the need for massive infrastructure investment in developing countries, particularly low-income countries. Governments in developing countries face enormous challenges in financing, implementing and maintaining the infrastructure to provide and maintain basic services for their citizens and promote economic growth. Despite significant strides in recent years in emerging markets, many people still lack access to reliable and secure basic services. PPPs have shown that they can, under the right circumstances, promote growth and improve service delivery, clearly indicating the importance of PublicPrivate Partnerships (PPPs) for Georgia.

Development of a Clinical Pathway for Acute Coronary Syndrome at Philippine General Hospital

BACKGROUND: Acute coronary syndrome (ACS) is a leading cause of admission and mortality in a tertiary care hospital in the Philippines. The significant burden of the disease necessitates that evidence-based care set by international and local guidelines be met to improve service delivery and quality of care (QOC). Institution-specific QOC studies showed gaps between guideline recommendations and compliance. Development and utilization of a clinical pathway are among the identified strategies to improve compliance. It is also crucial for implementation of standard-of-care set specific to a hospital setting based on its needs and resources. METHODS: This is a descriptive research on the development of a clinical pathway for ACS appropriate for the emergency room setting of a tertiary care hospital from March 2021 to August 2022. Local QOC studies and evidence behind the latest international guideline recommendations on the management of ACS were reviewed to create the interim ACS Pathway. Two-level content validation of the interim pathway was done: internal validation with the consultants and fellows of the Division of Cardiovascular Medicine and external validation through focused group discussions with different hospital units and stakeholders to assess applicability and feasibility based on the resources of the setting, identify hindrances, and propose solutions in its implementation. RESULTS: An evidence-based clinical pathway for ACS that encompasses identification and management of ST-segment elevation myocardial infarction and non–ST-segment elevation acute coronary syndrome with judicious use of locally available and feasible resources applicable for local emergency room hospital setting was created. CONCLUSION: Review of local QOC studies and interdepartmental collaboration are necessary components in developing institution-specific clinical pathway for ACS. KEYWORDS: acute coronary syndrome, clinical pathway, quality of care

Resistance to decentralised natural resource governance: Taiwan's Chiku wildlife refuge

Natural resource governance regimes are increasingly engaging various actors at multiple levels to address sustainability challenges. In this context, as a governance strategy, decentralisation – or the transfer of power from central to local authorities – is expected to improve service delivery, accountability, and participation. The paper examines whether decentralisation in wildlife refuge politics in Taiwan delivers these outcomes; what factors influence local governments’ capacities and powers to manage Chiku wildlife refuge in Taiwan; and what accountability mechanisms decentralisation policies enable. Multiple levels of governance are resistant to decentralisation, due to lack of ability and resources, evolving incentive structures, and conflicting regulations in a fragmented jurisdictional context. According to the findings, local authorities are becoming less engaged, agencies involved lack coordination, and accountability mechanisms are inadequate. The potential benefits of decentralisation are therefore hard to achieve.

A Comprehensive Survey on ServiceNow for IT Service Management

This paper presents a comprehensive survey on the utilization of ServiceNow in IT Service Management (ITSM), fo- cusing on its adoption, benefits, challenges, and future directions. The study employs a systematic literature review and industry reports to analyze the impact of ServiceNow on ITSM practices across various sectors. Key findings reveal that ServiceNow sig- nificantly enhances ITSM processes through automation, stream- lining workflows, and improving service delivery. The survey also identifies common challenges in implementing ServiceNow, such as resistance to change and integration difficulties with legacy systems, and proposes strategies for overcoming these obstacles. Furthermore, the paper explores emerging trends in ITSM, including the integration of artificial intelligence (AI) and machine learning (ML), and discusses how ServiceNow is positioned to leverage these technologies for future growth. The study concludes by emphasizing the critical role of ServiceNow in facilitating digital transformation and enhancing organizational efficiency in ITSM. Keywords —ITSM, ServiceNow, ITIL, Cloud Computing, Dig- ital Transformation, IT Operations Management.

Innovative performance-based remuneration model for oncologists: Balancing productivity with quality of care in a Brazilian healthcare setting.

e23089 Background: Traditional fee-for-service (FFS) models in oncology often lead to biased healthcare delivery, prioritizing quantity over quality of care. Our objective was to develop and implement a comprehensive remuneration model for oncologists in Brazil that emphasizes both productivity and quality in patient care. Methods: The '4E' model forms the basis of our remuneration strategy. 'Effectiveness' measures clinical productivity through patient consultations, treatments, and participation in multidisciplinary activities. 'Structure' evaluates academic credentials and scientific contributions, 'Efficiency' examines adherence to clinical and administrative protocols, and 'Excellence' assesses quality interactions with patients and healthcare systems. These elements provide nuanced bonus adjustments to the effectiveness score, facilitating a balanced and comprehensive compensation approach. Adapted to various healthcare settings, the model accommodates different budgeting methodologies. Results: Implemented in February 2020, the model has led to significant improvements in service delivery. Between May 2020 and August 2023, consultations in private services increased by 36.8%, and patient numbers grew by 42.2%. The financial impact was notable, with more than a doubling of revenue, reflecting the model's success in enhancing both the volume and quality of healthcare provision. Conclusions: This multi-level remuneration model offers a comprehensive, ethical approach, aligning physician compensation with a broad range of professional activities and responsibilities. It demonstrates potential for enhancing healthcare delivery quality while ensuring financial sustainability. However, a limitation of our study is the lack of longitudinal quality measurement, an aspect we aim to address in future research. This suggests the model's replicability in diverse global oncology settings and underscores its relevance in the current healthcare landscape.

Exploring the Influence of Cloud Computing on Workflow Efficiency in Public Administration

This review examines the impact of cloud computing on public administration workflow efficiency, highlighting its potential to improve service delivery, optimize costs, and promote innovation. It provides a comprehensive evaluation framework for assessing efficiency, highlighting case studies of the UK Government Digital Service and Estonia's e-government initiatives. Despite challenges like security and data privacy, the study suggests promising future prospects, including hybrid cloud solutions and AI integration.

Time-to-treatment for metastatic non-small cell lung cancer in the era of biomarker testing.

e20623 Background: In 2011, the National Comprehensive Cancer Network (NCCN) recommended biomarker testing in patients with metastatic non-small cell lung cancer (mNSCLC) based on improved survival with targeted therapies and immunotherapy reported in clinical trials. The requirement for biomarker testing before the commencement of treatment could inadvertently contribute to delays in treatment initiation. We investigated the time to treatment for mNSCLC in the US general population in the era of advanced therapies for lung cancer. Methods: We obtained data from 32,518 adults with mNSCLC between 2004 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. We categorized time to treatment to < 1 month or ≥ 1 month, and period of diagnosis to 2004-2011 and 2012-2020. We used separate logistic regression models to investigate the relationship between time to treatment, period of diagnosis, and year of diagnosis, adjusting for age, sex, household income, residence, and race. Results: The mean age of the study population was 66 (SD 10) years, 41% Female and 76% White. The majority (84%) were Metropolitan dwellers. A total of 23,322 (76%) were diagnosed between 2004 and 2011, and 9,186 (28%) from 2012 to 2019. Overall, 40% of patients initiated cancer therapy within a month of diagnosis, with no significant difference between patients who commenced treatment between 2004-2011 (40.2%) and 2012-2019 (39.9) (chi2 = 0.3492 P = 0.555). In both logistic regression analyses, there was no significant relationship between time to treatment and period or year of diagnosis. However, race/ethnicity and age independently predicted the time to treatment. Compared to Whites, Blacks (Odds ratio (OR) 1.08, 95% CI 1.01- 1.16, p = 0.04) and Hispanics (OR 1.26, 95% CI 1.03-1.24, p 0.01) were more likely to initiate treatment ≥ 1 month from the time of diagnosis. The odds of initiating treatment ≥ 1 month also increased with age (Age/year OR 1.01 (95% CI 1.01-1.01). Conclusions: We did not identify delays in treatment initiation for mNSCLC in the current era of biomarker testing. Biomarker testing has become an essential diagnostic tool for mNSCLC, guiding targeted therapies that have been shown to improve treatment outcomes. However, some vulnerable populations continue to experience delays in treatment initiation, which could lead to poorer survival. Improvements in cancer therapeutics must be complemented by service delivery improvements to optimize treatment outcomes.

Towards a Framework for Accelerating E-Government Readiness for Public Service Delivery Improvement in Zimbabwe

Towards a Framework for Accelerating E-Government Readiness for Public Service Delivery Improvement in Zimbabwe

Organizational Learning Culture and Firm Performance: The Mediating Role of Learning Agility

This article delves into the critical role of learning agility in the Indian context. It specifically explores how an organizational learning culture (OLCu) fosters an employee’s ability to learn and adapt—their learning agility—which ultimately translates into improved firm performance. Employing a cross-sectional research design, the study gathers data through self-administered surveys from over 313 employees working in hardware service firms within the Indian IT sector. Path analysis is then utilized to analyse the collected data and unveil the underlying relationships. The findings unveil a fascinating interplay between OLCu, learning agility and firm performance. The study suggests that OLCu acts as a catalyst, fostering a work environment that encourages continuous learning and development. This, in turn, fosters employee learning agility. However, the research also reveals that learning agility plays a mediating role, meaning it partially explains the effect of OLCu on firm performance. In simpler terms, while a strong OLCu is crucial, it is the employee’s enhanced learning agility that truly unlocks the door to improved firm performance. This research offers valuable insights that can empower organizations in the Indian IT landscape. By nurturing a vibrant OLCu, companies can equip their employees with the tools and support they need to become more learning agile. This agility translates into a workforce that can readily adapt to new technologies, evolving customer demands, and a dynamic business environment. Consequently, firms can expect greater innovation, improved service delivery, and, ultimately, a significant boost in overall performance. This research also contributes significantly to the existing body of knowledge. It adds a fresh perspective to organizational learning theory by highlighting the crucial role of learning agility as a bridge between OLCu and firm performance, particularly in the Indian IT sector.

Quality of Service in Sustainable Development: A QoS-based Analysis of the United Nations Sustainable Development Goals

This paper explores the innovative application of Quality of Service (QoS) principles, traditionally rooted in network and telecommunications, across various sectors to enhance the achievement of the United Nations Sustainable Development Goals (SDGs). By establishing a parallel between QoS in technological systems and sectors such as healthcare, education, energy, and urban development, we examine how these principles can be adapted to improve service delivery and efficiency in critical areas of sustainable development. The core premise is that methodologies used to optimize data flow and service reliability in networks can similarly enhance the quality, accessibility, and sustainability of essential services. This study conducts a comprehensive comparative analysis to illustrate the potential of QoS frameworks in promoting efficiency, effectiveness, and equity across multiple domains of the SDGs. Key areas of focus include enhancing healthcare outcomes, increasing educational accessibility, ensuring sustainable energy use, and improving urban infrastructure. The findings advocate for a cross-disciplinary approach to applying QoS principles, suggesting that such integration can lead to substantial improvements in service delivery and contribute significantly to global sustainable development efforts.

Lessons for tomorrow: The role of relationships and mindfulness in sustaining services during a crisis.

The COVID-19 pandemic placed unprecedented demands on hospitals around the globe, making timely crisis response critical for organizational success. One mechanism that has played an effective role in health care service management during large-scale crises is the Hospital Incident Command System. The aim of this article was to understand the role of HICS in the management of a large academic medical center and its impact on relationships and communication among providers in the delivery of services during a crisis. This mixed methods study was based on meeting observations, document reviews, semistructured interviews, and two measures of team performance within an academic medical center in the Northeast during the COVID-19 pandemic. Descriptive and bivariate analyses were applied, and qualitative data were coded and analyzed for themes. HICS provided a systematic information-sharing and decision-making process that increased communication and coordination among team members. Analyses indicate a correlation between dimensions of relational coordination and organizational mindfulness. Qualitative data revealed the importance of shared meetings and huddles and the evolution of HICS across multiple waves of the crisis. HICS facilitated organizational improvements during the crisis response and generated opportunities to maintain specific coordination practices beyond the crisis. The prolonged implementation of HICS during the COVID-19 pandemic created challenges, including the disruption of the routine leadership structure. Applying relational coordination and organizational mindfulness frameworks may allow hospitals to leverage communications and relationships within a high-stakes environment to improve service delivery.

Applications of natural language processing tools in the surgical journey.

Natural language processing tools are becoming increasingly adopted in multiple industries worldwide. They have shown promising results however their use in the field of surgery is under-recognised. Many trials have assessed these benefits in small settings with promising results before large scale adoption can be considered in surgery. This study aims to review the current research and insights into the potential for implementation of natural language processing tools into surgery. A narrative review was conducted following a computer-assisted literature search on Medline, EMBASE and Google Scholar databases. Papers related to natural language processing tools and consideration into their use for surgery were considered. Current applications of natural language processing tools within surgery are limited. From the literature, there is evidence of potential improvement in surgical capability and service delivery, such as through the use of these technologies to streamline processes including surgical triaging, data collection and auditing, surgical communication and documentation. Additionally, there is potential to extend these capabilities to surgical academia to improve processes in surgical research and allow innovation in the development of educational resources. Despite these outcomes, the evidence to support these findings are challenged by small sample sizes with limited applicability to broader settings. With the increasing adoption of natural language processing technology, such as in popular forms like ChatGPT, there has been increasing research in the use of these tools within surgery to improve surgical workflow and efficiency. This review highlights multifaceted applications of natural language processing within surgery, albeit with clear limitations due to the infancy of the infrastructure available to leverage these technologies. There remains room for more rigorous research into broader capability of natural language processing technology within the field of surgery and the need for cross-sectoral collaboration to understand the ways in which these algorithms can best be integrated.

Strengthening district health management and planning: an evaluation of a multi-country initiative in Eastern and Southern Africa

Background District health management and leadership capacity is increasingly recognised as critical to health system performance. District health managers play a central role in effective implementation and tailoring of national health policies, and they need adequate skills and support. The District Health System Strengthening Initiative (DHSSi) was implemented over 2019-22 in Malawi, Kenya, Tanzania and Uganda to strengthen sub-national capacity for evidence-based planning and a broader set of management competencies needed to operationalize district plans. To support learning and adaptation, a three-year evaluation was conducted to assess progress against outcomes and to inform ongoing implementation and future investment. Methods The evaluation used a mixed-methods theory-based approach. Evaluation questions were structured using criteria of relevance, coherence, efficiency, effectiveness, sustainability and impact, and corresponded to outputs, outcomes and impacts in the DHSSi Theory of Change. The evaluation was conducted over three annual rounds, and combined data from document review, observation, interviews and group discussions with cross-country, national and district stakeholders, and analysis of secondary quantitative data. Results Experience of DHSSi implementation indicated the relevance of supporting district management and planning, with gaps in current capacity, government interest, and indications of the potential to improve district practice. DHSSi experience also highlighted challenges to effective achievement of stronger capacity, and to translation of skills to improved management practice and, ultimately, to improved service delivery. A range of factors beyond skills affected district capacities, motivation and opportunities for effective planning and management, including areas such as funding, planning templates, health information systems, staff turnover, partner alignment and political structures. Conclusions Strengthening sub-national health management is an important agenda in efforts to expand high-quality primary health care. Future initiatives should prioritize detailed understanding of the range of influences on district management, and work to strengthen the enabling environment for effective district practice.

Citizen Charter as Governance Reform Initiative for Quality Services

The Citizen Charter (CC) is implemented to enhance the capabilities of local government in delivering services to people. It represents the official commitment to providing quality services to the public, and all service recipients need to have clear and concise information about the services and goods being provided. At the heart of the discussion on governance reform and the CC lies the question of whether public institutions foster the creation, dissemination, and processing of knowledge on the CC, which could ultimately lead to improved service delivery quality. Thus, this study examines the role of institutional factors such as procedural transparency and clarity, timely service delivery, and grievance handling systems in municipal service delivery post-implementation of the CC. The philosophical underpinning of this study adopts a pragmatic approach, utilizing a sequential explanatory mixed method. The findings reveal that there is increasing procedural transparency, and timely service delivery is gradually improving. However, the grievance handling system within the municipality still appears to be weak. It is evident from the study that the implementation of the Citizen Charter as a governance reform practice must address issues of reliability, responsiveness, and accuracy (RRA) to ensure quality service delivery (QSD) at the local level.

Adaptive Methods for Revenue Model Learning of a Slice Broker in the Presence of Adversaries

AbstractIn the fifth-generation (5G) of mobile networks, Multi-Access Edge Computing (MEC) refers to the deployment of computing resources closer to the end-users for improved service delivery. In the context of 5G MEC, the slice broker plays a crucial role in managing the allocation of resources among the different network slices, which are logical networks on top of a shared infrastructure. The slice broker is a business entity that acts as an intermediary between the slice tenants and the infrastructure provider and is responsible for allocating resources (such as CPU, memory, and network bandwidth) required to set up the network. The slice broker must ensure that resources are allocated in a way that the revenue is maximized. In a dynamic environment, the slice broker must learn the revenue model adaptively and online. Adversaries can significantly reduce the revenue by misleading the system about the resources pretending to be selfish nodes, or creating noise. The slice broker should learn the revenue model in the presence of adversaries. We apply cooperative deep reinforcement learning with consensus mechanism and consensus deep learning to learn the revenue model adaptively. We also compare our proposed methods with the reference solution. Simulation results show that our proposed methods, especially the cooperative version, outperform the reference solution.

Identifying Physician Public Health Competencies to Address Healthcare Needs in Underserved, Border, and Outer Island Areas of Indonesia: A Rapid Assessment

Phenomenon: Most medical schools in Indonesia have developed innovations to integrate public health content into the curricula. However, ensuring that all schools meet appropriate standards regarding the quality of subjects, content relevancy, and course delivery takes time and effort. Approach: This study employed a rapid assessment procedure to identify the current knowledge and competencies required to practice medicine effectively in underserved, border, and outer island areas of Indonesia. Ninety-three participants from six remote districts were involved in 12 focus group discussions. Qualitative data were analyzed using content analysis using the social determinants of health as a guiding framework. Findings: Under decentralized health system governance, the local socio-geographical context is critical to understanding the current public health landscape. Medical education with respect to public health must emphasize physicians’ ability to advocate and encourage the coordination of healthcare services in responding to disasters, as well as community-based surveillance and other relevant data for synergistic disease control. As part of a healthcare facility management team, prospective doctors should be able to apply systems thinking and provide critical input to improve service delivery at local health facilities. Also, recognizing underlying factors is essential to realizing effective interprofessional collaboration practices and aligning them with leadership skills. Insights: This study outlines recommendations for medical schools and relevant colleges in formulating compulsory block or integrated public health curricula. It also provides a public health learning topic that may aid medical schools in training their students to be competent for practice in underserved, border, and outer island areas. Medical schools should offer initiatives for students to acquire the necessary public health competencies merited by the population’s health needs.

"The perfect storm": community worker perspectives on the impact of COVID-19 on New York City immigrants and migrant-serving organizations.

Immigrants in New York City (NYC) have higher COVID-19 mortality than the general population. While migrant-serving organizations (MSOs) provide access to a breadth of services, they are disproportionately impacted by the COVID-19 pandemic due to staffing limitations, funding cuts, and resource limitations of communities served. Six focus-group discussions were conducted to explore the experiences of MSOs in NYC during the COVID-19 pandemic from November 2021 to March 2022. Study participants csomprised a subsample of survey respondents from a larger study identified via lists of MSOs. Twenty-seven organizational representatives from 11 MSOs across NYC participated in the discussions. In addition to providing information on communities served, services offered, and organizational characteristics, the following themes emerged from the convenings: mental health challenges and resources needed for immigrants; immigration-related challenges; factors exacerbating hardships for immigrants during COVID-19; interorganizational collaborations and partnerships; policy change; and needs/requests of MSOs. MSOs provide a wide range of services as non-profit organizations and use interorganizational collaboration to improve service delivery. The proximity of MSOs to immigrant communities helps providers understand the needs of immigrants relating to the COVID-19 pandemic and factors that shape telehealth services. MSOs are important providers and advocates for immigration policy in the US given their relationship with the populations they serve. These findings have implications for how to support MSOs that serve immigrants in NYC. Strategies to achieve this include timelier availability and exchange of information, policies, and research as well as strengthening the experience-based advocacy of these groups.

Utilizing comprehensive data dashboards to improve service delivery: Insights from U.S. case studies

In an era driven by data, the efficient utilization of comprehensive data dashboards has emerged as a crucial tool for enhancing service delivery across various sectors. This review provides insights into the impact and effectiveness of employing such dashboards, drawing from case studies conducted in the United States. Effective service delivery requires a deep understanding of operations, client needs, and performance metrics. Comprehensive data dashboards offer a solution by aggregating, visualizing, and analyzing vast amounts of data in real-time, providing decision-makers with actionable insights. Through a synthesis of case studies, this review elucidates how organizations in the U.S. leverage data dashboards to optimize service delivery. Firstly, the review examines the healthcare sector, where data dashboards play a pivotal role in improving patient care. Case studies highlight how hospitals utilize dashboards to monitor patient outcomes, manage resources efficiently, and identify areas for quality improvement. By tracking key performance indicators such as patient wait times, readmission rates, and medication errors, healthcare providers can implement targeted interventions to enhance service quality and patient satisfaction. Furthermore, the review delves into the realm of education, showcasing how schools and educational institutions leverage data dashboards to personalize learning experiences and improve student outcomes. Through the analysis of student performance data, attendance records, and demographic information, educators can identify at-risk students, tailor instructional strategies, and allocate resources effectively, thereby fostering academic success and equitable education opportunities. Additionally, this review explores the utilization of data dashboards in government agencies to enhance public service delivery. Case studies demonstrate how municipalities employ dashboards to track infrastructure projects, manage budgets, and address citizen concerns promptly. By fostering transparency and accountability, these dashboards facilitate citizen engagement and enable governments to deliver services that align with community needs and priorities. In conclusion, the review underscores the transformative potential of comprehensive data dashboards in optimizing service delivery across diverse sectors. By leveraging real-time data analytics, organizations can enhance efficiency, accountability, and client satisfaction, ultimately driving positive outcomes and fostering continuous improvement in service delivery practices.

Double-Compressed Artificial Neural Network for Efficient Model Storage in Customer Churn Prediction

In the rapidly evolving field of Artificial Intelligence (AI), efficiently storing and managing AI models is crucial, particularly as their complexity and size increase. This paper explores the strategic importance of AI model storage, focusing on performance, cost-efficiency, and scalability within the realm of customer churn prediction, utilizing model compression technologies. Deep learning networks, integral to AI models, have become increasingly large, necessitating millions of parameters. These parameters make the models computationally expensive and voluminous in storage requirements. Addressing these issues, the paper discusses the application of model compression techniques—specifically pruning and quantization—to mitigate the storage and computational challenges. The experimental results demonstrated the effectiveness of the proposed method. These techniques reduce the physical footprint of AI models and enhance their processing efficiency, making them suitable for deployment on resource-constrained devices. Using these models in customer churn prediction in telecommunications illustrates their potential to improve service delivery and decision-making processes. By compressing models, telecom companies can better manage and analyze large datasets, enabling more effective customer retention strategies and maintaining a competitive edge in a dynamic market.