Infrastructure Variables Research Articles

A Relationship between Physical Infrastructure and Patient Satisfaction: A Case Study of Kantipur Dental Hospital

This study investigates the impact of physical infrastructure on patient satisfaction at Kantipur Dental Hospital, a prominent dental care facility in Nepal. With the increasing demand for high-quality healthcare services, understanding the factors influencing patient satisfaction is crucial for healthcare providers. The research aims to explore how various aspects of the hospital’s infrastructure—specifically, the use of state-of-the-art equipment, cleanliness and hygiene, sterilization practices, and convenient location—affect patients' perceptions of care quality. A quantitative research design was employed, utilizing a structured questionnaire distributed to 117 patients who had received treatment at Kantipur Dental Hospital within the last six months. The questionnaire measured patients' perceptions of the clinic's infrastructure and their overall satisfaction, with a focus on two key dimensions: confidence after treatment and the acceptability of service fees. Data analysis was conducted using Spearman’s rho correlation to assess the relationships between the perceived infrastructure variables and patient satisfaction outcomes. The findings reveal significant positive correlations between perceptions of the hospital's physical infrastructure and patient satisfaction. Specifically, the use of modern equipment and a clean, hygienic environment were strongly associated with increased patient confidence post-treatment. Furthermore, the accessibility of the hospital location was also found to influence perceptions of service fee acceptability. Notably, while sterilization practices contributed positively to patient confidence, they did not significantly impact fee perceptions, suggesting that patients prioritize cleanliness and modernity in their overall evaluation of care. These results underscore the critical role of physical infrastructure in enhancing patient satisfaction at Kantipur Dental Hospital. The study recommends that healthcare facilities continue to invest in modern technology and maintain high standards of cleanliness to foster patient confidence and satisfaction. This research provides valuable insights for clinic management and policy-makers, emphasizing that improving physical infrastructure is essential for delivering quality healthcare services and ensuring positive patient experiences.

Competence, Motivation And Facilities And Infrastructure As Determining Factors In Dpmptsp Employee Performance

This study aims to analyze and prove the influence of competence, motivation, facilities and infrastructure on employee performance to support the success of socialization at the Investment and One-Stop Integrated Service Office (DPMPTSP) in Ogan Komering Ilir Regency. This study is a quantitative study, the population in this study were 115 DPMPTSP employees and the sampling method was saturated sampling. The results of this study indicate that partially competence has a negative and significant effect on employee performance, while motivation, facilities and infrastructure have a significant positive effect on performance. Simultaneously, the variables of competence, motivation, facilities and infrastructure have a positive and significant effect on the performance of DMPTSP employees.

Phage communities in household-related biofilms correlate with bacterial hosts

The average American spends 93% of their time in built environments, almost 70% of that is in their place of residence. Human health and well-being are intrinsically tied to the quality of our personal environments and the microbiomes that populate them. Conversely, the built environment microbiome is seeded, formed, and re-shaped by occupant behavior, cleaning, personal hygiene and food choices, as well as geographic location and variability in infrastructure. Here, we focus on the presence of viruses in household biofilms, specifically in showerheads and on toothbrushes. Bacteriophage, viruses that infect bacteria with high host specificity, have been shown to drive microbial community structure and function through host infection and horizontal gene transfer in environmental systems. Due to the dynamic environment, with extreme temperature changes, periods of wetting/drying and exposure to hygiene/cleaning products, in addition to low biomass and transient nature of indoor microbiomes, we hypothesize that phage host infection in these unique built environments are different from environmental biofilm interactions. We approach the hypothesis using metagenomics, querying 34 toothbrush and 92 showerhead metagenomes. Representative of biofilms in the built environment, these interfaces demonstrate distinct levels of occupant interaction. We identified 22 complete, 232 high quality, and 362 medium quality viral OTUs. Viral community richness correlated with bacterial richness but not Shannon or Simpson indices. Of quality viral OTUs with sufficient coverage (614), 532 were connected with 32 bacterial families, of which only Sphingomonadaceae, Burkholderiaceae, and Caulobacteraceae are found in both toothbrushes and showerheads. Low average nucleotide identity to reference sequences and a high proportion of open reading frames annotated as hypothetical or unknown indicate that these environments harbor many novel and uncharacterized phage. The results of this study reveal the paucity of information available on bacteriophage in indoor environments and indicate a need for more virus-focused methods for DNA extraction and specific sequencing aimed at understanding viral impact on the microbiome in the built environment.

Association between greenness exposure and depression rate among Bangkok residents: An ecological longitudinal study

This ecological study aimed to examine the relationship between greenness exposure and depression among Bangkok residents, using the district as a unit of analysis. This study utilized data on depression (ICD-10 F32, F33), environmental parameters, and demographic and health infrastructure variables in 50 districts in Bangkok recorded from 2018 to 2020. The Excellence Center for Depressive Disorder provided information on the number of new depression cases, including only those who had registered permanent residence in Bangkok. Greenness was measured using the normalized difference vegetation index (NDVI), which was extracted from a Terra-MODIS sensor. Then, the association between greenness exposure and depression was evaluated using descriptive statistics, bivariate analysis, and generalized additive mixed models with adjustment for covariates. From 2018 to 2020, a mean of 4.57 ± 6.45 cases was recorded per 100,000 population annually, and the mean NDVI was 0.33 ± 0.09. Adjusted for all covariates, as well as considering the smooth terms basis, an increase in one unit of NDVI value would contribute to depression rate reduction by up to 77.7 % (risk ratio = 0.223, 95 % CI = 0.200 – 0.248). PM2.5 exhibited an insignificant positive association with depression incidence rate. Additionally, temperature and humidity were associated with depression rate in the final model (p < 0.05). Living in greener areas would contribute to a lower depression incidence rate in Bangkok. However, the study is subject to limitations, including the impact of the COVID-19 pandemic, which may have influenced both depression rates and access to green spaces during the study period. Policies that can increase environmental greenness should be promoted to enhance social interactions and physical activities.

Age-Friendly Urban Design for Older Pedestrian Road Safety: A Street Segment Level Analysis in Madrid

Walking benefits older pedestrians but exposes them to traffic crashes. With an aging population, designing age-friendly cities is crucial, yet research on older pedestrian safety at a micro-level is limited. This study aims to reduce older pedestrian–vehicle collisions and create more livable environments through infrastructure policies derived from statistical data analysis. Special attention is focused on collecting a holistic set of infrastructure variables to reflect most of the street built environment elements, which helps policymakers implement short-term safety measures. Using Bayesian Poisson regression, this study analyzes factors contributing to the occurrence of crashes involving older and non-older pedestrians on road segments in Madrid, Spain. The results indicate that different factors affect the occurrence of crashes for all pedestrians versus older pedestrians specifically. Traffic crashes involving all pedestrians are affected by leisure points of interest, bus stops, and crosswalk density. Older pedestrian traffic crashes are influenced by population density, the presence of trees and trash containers, and contour complexity. Proposed measures include relocating trees and trash containers, modifying bus stops, and adding crosswalks and traffic lights. This paper also shows that these countermeasures, aimed at creating age-friendly streets for older pedestrians, are not expected to worsen the road safety of other pedestrians.

Analysis of Public Facilities, Village Funds and Social Infrastructure on Community Welfare in Pematang Serai Village, Langkat Regency

This research is based on the analysis of public facilities, village funds and social infrastructure on the welfare of the community in Pematang Serai village. Pematang Serai village, Langkat Regency is dominated by people who earn a living as fruit and vegetable farmers, but with the location of the village far from the city, there is a need for attention to public facilities for the community, Good management of village funds and infrastructure to be a benchmark for community welfare and household productivity is important for the people who live in the village. This research was conducted in Pematang Serai Village. The thing being studied is the influence between the variables of public facilities, village funds, and social infrastructure, on community welfare and household productivity. The purpose of the research is to find out and analyze the welfare of the community in Cingkes Village, Dolok Silau District by analyzing through public facilities, management and villages for the community and social infrastructure to facilitate daily community activities. The number of samples used was 200 data families collected by distributing questionnaires and data management using SEM (Structural Equation Modeling) using Amos software version 20. Based on the results of the test conducted with a hypothesis test, social infrastructure variables have a significant effect on community productivity. Then the variables of public facilities, village funds and social infrastructure have an insignificant effect on the welfare of the community and the variables of facilities and village funds also have no significant effect on household productivity. In this study, it is hoped that the village government will pay more attention to the things that the community needs in the village.

Determinants of an extended metric of agricultural commercialization in Ghana

For smallholder farmers in sub-Saharan Africa, increasing productivity and agricultural commercialization are mooted as one of the pillars for agricultural development. However, the measurement of agricultural commercialization has been restricted to the household crop commercialization index (HCCI) that focuses on crops neglecting livestock. This study develops an extended metric of agricultural commercialization named household crop-livestock commercialization index (HCLCI), which combines crop and livestock commercialization with the argument that it is superior to the overly used HCCI. Fractional regression is used to estimate the determinants of the extended metric using secondary and primary data from Ghana. Results indicate that agricultural commercialization is low when examined with the HCCI and the HCLCI. However, the HCLCI (at 26.44 % and 29.76 %, respectively, for the GLSS7 and primary data) is much lower relative to the HCCI (at 35.20 % and 38.24, respectively) but higher than the livestock commercialization index (10.93 % and 8.21 %, respectively). The underlying simultaneous factors that boost agricultural commercialization are infrastructure variables (i.e., road, market, transport, and bank), institutional variable (i.e., agricultural cooperatives) and scale of production (i.e., land endowment and crop production diversity). These findings imply that Ghana needs to invest in infrastructure and farmer institutional development to boost agricultural commercialization.

COVID-19 전후 우리나라 지역 간 이동 네트워크의 특성 분석

The purpose of this study is to analyze the characteristics of the interregional mobility network in South Korea before and after COVID-19. South Korea has been experiencing a decline in population not only in the overall population, but also by region, which has become a major social problem. Under these circumstances, interregional travel can contribute to revitalizing local economies, and local governments are exploring various policies to increase the number of visitors. This study uses social, economic, tourism infrastructure, and public relations variables as factors that can explain interregional travel networks in South Korea, and utilizes social network analysis methods. In addition, to consider the COVID-19 pandemic as a variable that has had a significant impact on interregional travel networks in recent years, the study compares the pre- and post-COVID-19 periods in 2019 and 2021. We find that the use of social media before and after the COVID-19 outbreak is very useful in explaining interregional travel networks in South Korea. In particular, we find that social media is more useful than traditional tourism infrastructure in explaining intraregional visitor flows. While it is important for local governments to expand traditional tourism infrastructure, they need to better utilize social media as a medium to communicate this effectively.

Analyzing the impact of cultural accessibility and ICT infrastructure on economic growth in Kazakhstan

For this, the primary aim of this study was to analyze of the impact of cultural accessibility and ICT (information and communication technology) infrastructure on economic growth in Kazakhstan, employing regression models to asses a single country data from 2008 to 2022. The research focuses on two sets of variables: cultural development variables (e.g., number of theaters, museums, and others) and ICT infrastructure variables (e.g., number of fixed Internet subscribers, total costs of ICT, and others). Principal component analysis (PCA) as employed to reduce the dimensionality of the data and identify the most significant predictors for the regression models. The findings indicate that in the cultural development model (Model 1), the number of recreational parks and students are significant positive predictors of GDP per capita. In the ICT infrastructure model (Model 2), ICT costs are found to have a significant positive impact on GDP per capita. Conversely, traditional connectivity indicators, such as the number of fixed telephone lines, show a low dependence on economic growth, suggesting diminishing returns on investment in these outdated forms of ICT. These results suggest that investments in cultural and ICT infrastructure are crucial for economic development. The study provides valuable insights for policymakers, emphasizing the need for quality improvements in education and strategic modernization of communication technologies.

Public Satisfaction with Online Services: (Case Study on the JEPIN Application)

Purpose: This study aims to analyze the use of the JEPIN application for users, namely the community in Pontianak City. JEPIN stands for Jendela Pontianak Integration This application was launched by the Pontianak City Communication and Information Office. Measurement uses variables consisting of infrastructure, ICT, human resources, budgeting, and digital government implementation. Methods: The method used is a quantitative type, primary data in the form of a survey of 100 respondents who come from JEPIN application users in Pontianak City. Using the Likert Scale (1: strongly disagree, 2: disagree, 3: neutral, 4: agree, and 5: strongly agree). The analysis technique for this study uses SmartPLS 4. Result: The results of the study show that the infrastructure variables have a P-Value of (0.000), an ICT P-Value of (0.000), and a P-Value Budgeting of (0.002), respectively, which shows a positive and significant influence on the implementation of digital government in the implementation of the JEPIN application. On the other hand, the human resources variable has a P-Value of (0.998), which shows a positive and significant influence on the implementation of digital government in the implementation of the JEPIN application in Pontianak City. Novelty: This study is unique because it looks at users who use the JEPIN application with a measurement indicator, namely the online services index (OSI). Most previous research on this theory has focused only on measuring how satisfied people are with online services, but this study offers a new perspective on the use of OSI in the context of application-based online services.

Nexus of public organization, transparency, and accountability in Indonesia's digital governance

This study examined uniting public organization, transparency, and accountability theories for a holistic understanding of digital government service implementation in Indonesia. This study used a survey data collection method with 424 respondents for employees in four local governments. Questionnaires were generated using a Likert scale. Structural equation modeling‐partial least squares was used to assess the validity and reliability of the data and to test hypotheses and regression models. Following the testing of hypotheses and regression analysis, this study found that variables of employee skills, leadership, regulation, infrastructure, information and communication technology, transparency, and accountability had a positive and significant effect on the variable of digital government service implementation with p‐values of 0.034, 0.025, 0.014, 0.031, 0.009, 0.005, and 0.010, respectively. In contrast, variables of budgeting and bureaucratic structure do not positively and significantly impact the variable of digital government service implementation with p‐values of 0.210 and 0.311, respectively. The influence of the independent variables on the dependent variable was strong (R‐square = 0.834). The limitations and implications of these findings are discussed in the conclusion.

MIXED GEOGRAPHICALLY WEIGHTED REGRESSION (MGWR) WITH ADAPTIVE WEIGHTING FUNCTION IN POVERTY MODELING IN NTT PROVINCE

Poverty modeling is a crucial economic and social development issue in various regions, including in East Nusa Tenggara (NTT) Province. This research proposes using the Mixed Geographically Weighted Regression (MGWR) model with an adaptive Bisquare weighting function to analyze variables influencing poverty levels in NTT Province. The MGWR model is an extension of the Geographically Weighted Regression (GWR), which allows some variables in the model to have local effects while others have global effects. The adaptive weighting function in the MGWR model enhances the analysis by providing different weights at each location according to its local characteristics, thus making the results more accurate and representative for each area. The data includes economic, social, and infrastructure variables from 22 districts/cities in NTT Province for 2023. The MGWR model with an adaptive weighting function is applied to model the relationship between these variables and poverty levels. The analysis integrates statistical software to manage and analyze spatial data. The study findings show that the MGWR model with an adaptive weighting function offers better estimates than the global regression and GWR models. The results revealed the smallest AIC value for the MGWR model at 104.1888, compared to the global regression model at 140.1427 and the GWR model at 117.6174. This model successfully identifies significant local and global variables and shows variations in influence at different locations in NTT Province. These findings provide valuable insights for policymakers and practitioners in designing and implementing more effective poverty alleviation strategies tailored to local conditions in NTT Province.

Pengaruh Sarana Prasarana Dan Disiplin Kerja Terhadap Kinerja Pegawai Dinas Pemadam Kebakaran Kota Bekasi

This research aims to determine the influence of infrastructure and work discipline on the performance of Bekasi City Fire Department employees. The research method used is quantitative research, where this research is used to examine certain populations and samples, data collection uses research instruments, quantitative or statistical data analysis, aims to test predetermined hypotheses. The sampling technique used was saturated sampling technique or the entire population was sampled. The population in this study was 55 respondents. Data analysis uses Smart PLS 4.0 software and hypothesis testing, namely the t test and F test. Based on the results of the path coefficient hypothesis test, there are P-values ​​of 0.000 or &lt; 0.05 and the t-statistics value of infrastructure has a value of 5,713 or &gt; 1.96, it is stated that there is a significant influence between the infrastructure variables on employee performance. Based on the results of the path coefficient hypothesis test, there is a P-value of 0.002 or &lt;0.05 and the t-statistics value of work discipline has a value of 3,080 or &gt; 1.96, so it is stated that there is a significant influence between the work discipline variable on employee performance.

Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria

Studying the spatiotemporal dynamics of crime is crucial for accurate crime geography research. While studies have examined crime patterns related to weekdays, seasons, and specific events, there is a noticeable gap in research on nighttime crimes. This study focuses on crimes occurring during the nighttime, investigating the temporal definition of nighttime crime and the correlation between nighttime lights and criminal activities. The study concentrates on four types of nighttime crimes, assault, theft, burglary, and robbery, conducting univariate and multivariate analyses. In the univariate analysis, correlations between nighttime crimes and nighttime light (NTL) values detected in satellite images and between streetlight density and nighttime crimes are explored. The results highlight that nighttime burglary strongly relates to NTL and streetlight density. The multivariate analysis delves into the relationships between each nighttime crime type and socioeconomic and urban infrastructure variables. Once again, nighttime burglary exhibits the highest correlation. For both univariate and multivariate regression models the geographically weighted regression (GWR) outperforms ordinary least squares (OLS) regression in explaining the relationships. This study underscores the importance of considering the location and offense time in crime geography research and emphasizes the potential of using NTL in nighttime crime analysis.

What Makes An Effective Vocational High School Entrepreneurial Leadership? Experience From Indonesia

The government encourages vocational high schools (SMK) to carry out organizational transformation to become SMKs for Regional Public Service Bodies (SMK-BLUD). Through BLUDs, SMKs that have excellent products can manage finances and production processes more flexibly without violating regulations, so that entrepreneurial leadership effectiveness can be achieved. This study aims to analyze the factors that influence the effectiveness of entrepreneurial leadership in vocational high schools using PLS-SEM analysis. Data was obtained by distributing questionnaires to 180 respondents, including teachers, school principals, and committee members at 23 SMK-BLUDs in East Java and the Special Region of Yogyakarta. It is known that the variables of regulation, teacher support, self-capacity, and infrastructure have a positive and significant influence on the quality of entrepreneurial leadership. In addition, the existence of partnerships for each school indirectly has a positive and significant influence on the quality of entrepreneurial leadership. The results of this model show a predictive relevance (Q2) value of 0.96, meaning that this model has good predictive relevance.

Latent class models for capturing unobserved heterogeneity in major global causes of mortality: The cases of traffic crashes and COVID-19

Existing models for correlating global mortality rates with underlying country-specific factors overlook the variations in the effects of these factors on mortality across different countries. These may arise from social, cultural, and political complexities which are usually not measurable and are therefore referred to as unobserved heterogeneity in the statistical literature. Unobserved heterogeneity leads to biased parameter estimates in the models, erroneous inferences about the effects of factors contributing to mortalities, and ultimately inefficient policies. In this paper, latent class modelling is proposed for capturing such unobserved heterogeneity on the cases of traffic mortality and COVID-19 mortality. The ‘pyramid’ model of safety management is used as a common framework for model formulation. The proposed latent class model is an extension of the Negative Binomial (NB) model used in risk epidemiology. The model is tested with data from 105 countries, retrieved from international databases, including socioeconomic, infrastructure, exposure, transport, and COVID-19 variables. The results suggest that there exist two (different) latent country classes in both causes of mortality. The probability of a country belonging to a certain latent class is a much more efficient metric of country membership than previous deterministic groupings (e.g. income or geographic). Variables such as the elderly population, the GDP per capita or the level of motorization, have different effects in different country classes; these effects are not identifiable by conventional statistical modelling. The impact of ignoring unobserved heterogeneity in country mortality modelling is shown by comparing the results with those of conventional NB models.

Pengaruh Infrastruktur terhadap PDRB Kawasan Timur Indonesia Tahun 2014 – 2022

Economic growth according to Solow Swan's theory is influenced by the factors of capital accumulation, labor, and technological progress. Infrastructure is a form of physical capital that can increase economic activity. During the government of President Joko Widodo, there is the concept of “Nawacita” which in its agenda has points to increase people's productivity and competitiveness in the international market and points to build Indonesia from the periphery by strengthening regions and villages within the framework of a unitary state. The real condition that occurs today is the phenomenon of the development gap. In order to implement this agenda, the government divides Indonesia into the Western Region and the Eastern Region of Indonesia. Eastern Indonesia is considered to be underdeveloped because if seen from the contribution of KTI to the National GRDP, it only contributes less than 25 percent. The purpose of this study is how infrastructure affects the 17 provinces of Eastern Indonesia. The study uses secondary data with panel data regression analysis with the Fixed Effect Model (FEM). The variables used are economic growth represented by GRDP as the dependent variable and road infrastructure, electricity infrastructure, TPAK, number of internet users as independent variables. The results showed that the variables of electricity infrastructure and the number of internet users had a significant positive effect on economic growth while the variables of road infrastructure and TPAK had no significant effect on economic growth.

Socio-demographic and infrastructural variables influencing maternal risk concentration among ever-married women of reproductive age in rural West Bengal, India.

The risk of a woman dying as a result of pregnancy or childbirth during her lifetime is about one in six in the poorest parts of the world. The present study aims to determine prevalence of maternal risk and the influencing variables among ever-married women belonging to the reproductive age group (15-49) of Birbhum district, West Bengal. A cohort-based retrospective cross-sectional study was carried out among the sample of 229 respondents through a purposive stratified random sampling method and a pre-designed semi-structured questionnaire. The ordinal logistic regression (OLR) model was taken as a tool of assessment. Before developing the proportional OLR model, we have checked the multicollinearity effect among the predictors and the first-order effect modifier was evaluated as well. We performed data analysis using SPSS version 26. The result shows that illiterate women (Odds ratios [OR]=2.81, 95% CI, 0.277-1.791), from lower standard of living (OR=1.14, 95% CI, -0.845-1.116), married before the age of 15years (OR=21.96, 95% CI, -0.55-6.73) and between the age of 15-18years (OR=24.51. 95% CI, -0.45-6.85) are more likely to be affected by the higher concentration of maternal risk. Other important predictor is the time of pregnancy registration. Considering the transport and related en-route causalities, the result portraying a clear picture where the distance and travel time becoming significant factors in determining the concentration of maternal risk. Incidences of child marriages should be restricted. Eradicating factors influencing an individual's decision to seek care would be an essential contribution in excluding the dominant maternal risk factors.

Demographic, socioeconomic, and health structure factors associated with the use of HIV pre-exposure prophylaxis in Brazil: A nationwide ecological study.

Aims: To assess the cumulative rate of HIV Pre-Exposure Prophylaxis (PrEP) users in Brazil since its 2018 implementation and to analyze the association between PrEP usage and state-level structural factors. Methods: A nationwide ecological study from 2018 to 2022 was conducted, examining the 5-year cumulative rate of PrEP users in relation to demographic, socioeconomic, and healthcare infrastructure variables. Multiple linear regression analysis identified significant predictors of PrEP utilization. Results: Between 2018 and 2022, 124,796 individuals used PrEP, with a cumulative rate of 61.5 per 100,000 population. The highest usage was in Minas Gerais, São Paulo, and Santa Catarina, while the lowest was in Distrito Federal, Maranhão, and Alagoas. Regression analysis showed that higher PrEP usage was associated with lower population density, a younger median age, a lower male to female ratio, and reduced social vulnerability. Additionally, PrEP usage was positively associated with the density of medical doctors and the number of dispensing units. Conclusions: The study reveals significant regional disparities in PrEP usage across Brazil, influenced by socioeconomic and healthcare factors. It highlights the need for targeted public health strategies to enhance PrEP access and uptake, especially in socially vulnerable regions.

Closing the gap between acceptable and ideal in catheterisation for paediatric and congenital heart disease-A global view.

In recent issues of the Journal of the Society for Cardiovascular Angiography and Interventions and the Journal of the American College of Cardiology: Cardiovascular Interventions, Holzer and colleagues presented an Expert Consensus Document titled: "PICS / AEPC / APPCS / CSANZ / SCAI / SOLACI: Expert consensus statement on cardiac catheterization for pediatric patients and adults with congenital heart disease." This Expert Consensus Document is a massively important contribution to the community of paediatric and congenital cardiac care. This document was developed as an Expert Consensus Document by the Pediatric and Congenital Interventional Cardiovascular Society, the Association for European Paediatric and Congenital Cardiology, the Asia-Pacific Pediatric Cardiac Society, the Cardiac Society of Australia and New Zealand, the Society for Cardiovascular Angiography and Interventions, and the Latin American Society of Interventional Cardiology, as well as the Congenital Cardiac Anesthesia Society and the American Association of Physicists in Medicine.As perfectly stated in the Preamble of this Expert Consensus Document, "This expert consensus document is intended to inform practitioners, payors, hospital administrators and other parties as to the opinion of the aforementioned societies about best practices for cardiac catheterisation and transcatheter management of paediatric and adult patients with congenital heart disease, with added accommodations for resource-limited environments." And, the fact that the authorship of this Expert Consensus Document includes global representation is notable, commendable, and important.This Expert Consensus Document has the potential to fill an important gap for this patient population. National guideline documents for specific aspects of interventions in patients with paediatric heart disease, including training guidelines, do exist. However, this current Expert Consensus Document authored by Holzer and colleagues provides truly globally applicable standards on cardiac catheterisation for both paediatric patients and adults with congenital heart disease (CHD).Our current Editorial provides different regional perspectives from senior physicians dedicated to paediatric and congenital cardiac care who are practicing in Europe, the Asia-Pacific region, Latin America, Australia/New Zealand, and North America. Establishing worldwide standards for cardiac catheterisation laboratories for children and adults with CHD is a significant stride towards improving the quality and consistency of care. These standards should not only reflect the current state of medical knowledge but should also be adaptable to future advancements, ultimately fostering better outcomes and enhancing the lives of individuals affected by CHD worldwide.Ensuring that these standards are accessible and adaptable across different healthcare settings globally is a critical step. Given the variability in resources and infrastructure globally, the need exists for flexibility and tailoring to implement recommendations.The potential impact of the Expert Consensus Document and its recommendations is likely significant, but heterogeneity of healthcare systems will pose continuing challenges on healthcare professionals. Indeed, this heterogeneity of healthcare systems will challenge healthcare professionals to finally close the gap between acceptable and ideal in the catheterisation of patients with paediatric and/or congenital heart disease.