Patient Satisfaction in the Spanish National Health Service: Partial Least Squares Structural Equation Modeling

Estimation of Additional Costs in Patients with Ventilator-Associated Pneumonia

Healthcare-associated infections (HAIs) present a global public health challenge, contributing to high morbidity and mortality and substantial economic burdens. Ventilator-associated pneumonia (VAP) ranks as the second most prevalent HAI in intensive care units (ICUs), emphasizing the need for economic analyses in this context. This retrospective cohort study, conducted at the General Hospital of Alicante from 2012 to 2019, aimed to assess additional costs related to VAP by comparing the extended length of stay for infected and non-infected ICU patients undergoing mechanical ventilation (MV) for more than 48 h. Employing propensity score association, 434 VAP patients were compared to an equal number without VAP. The findings indicate a significantly longer mechanical ventilation period for VAP patients (17.40 vs. 8.93 days, p < 0.001), resulting in an extra 13.56 days of stay and an additional cost of EUR 20,965.28 per VAP episode. The study estimated a total cost of EUR 12,348,965.28 for VAP during the study period, underscoring the economic impact of VAP. These findings underscore the urgent need for rigorous infection surveillance, prevention, and control measures to enhance healthcare quality and reduce overall expenditures.

COVID-19 and Public Health Spending; Effects on the Economic Sustainability of the Spanish Private Healthcare System

This research analyzes the influence of COVID-19 and public health spending policies on the economic sustainability of Spanish private hospitals. Moreover, it explores the relationship between public health spending policies and the spread of COVID-19 in Spain. Private health care is an understudied sector, yet it is fundamental to the health of citizens. Moreover, the economic causes linked to the spread of the pandemic have not yet been clearly established. Therefore, this work covers a gap in the literature. Private hospital profitability was analyzed by applying ordinary least squares and panel data regressions on financial and macroeconomic data for the period 2017-2020. The spread of COVID-19 was examined by means of cluster and component analysis. The results show that the COVID-19 pandemic negatively affected the economic sustainability of Spanish private hospitals, which was also influenced by public health spending. In turn, the spread of the pandemic was mainly related to population density, but was also influenced by public health spending and the gross domestic product of the region. Therefore, policymakers must consider that it is essential to make adequate investments in the healthcare system to cope with pandemics such as COVID-19. In addition, managers can see how corporate social responsibility is a valuable strategy for maintaining hospital profitability.

Unlocking the Secrets of Longevity: Exploring the Impact of Socioeconomic Factors and Health Resources on Life Expectancy in Oman and Qatar

In an era marked by a sweeping pandemic and the encroaching shadow of an energy crisis, the well-being and lifespan of global populations have become pressing concerns for every nation. This research zeroes in on life expectancy (LE), a powerful indicator of societal health in Oman and Qatar. Our study juxtaposes 3 key factors affecting LE: health status and resources (HSR), macroeconomics (ME), and sociodemographic (SD) factors. To achieve this, we tapped into a comprehensive data set from the World Bank, encompassing a transformative 3-decade span from 1990 to 2020. The intricate interplay between these factors and LE was deciphered through robust Structural Equation Modeling (SEM). Our findings construct a compelling narrative: ME has an indirect yet considerable influence on LE-manifesting with an effect of 0.602 for Oman and 0.676 for Qatar. This influence is mediated by SD and HSR components. Similarly, SD elements impact LE indirectly-with an effect of 0.653 for Oman and 0.759 for Qatar- this effect is mediated by HSR. In contrast, HSR themselves wield a robust and direct influence on LE, indicated by an effect of 0.839 for Oman and 0.904 for Qatar. All these aforementioned effects were statistically substantial (P < .001). Our research magnifies the robust direct influence of HSR on LE in both Oman and Qatar, simultaneously highlighting the noteworthy indirect role of ME and SD factors. This emphasizes the significance of adopting an integrated policy approach that considers all the SD, ME, and HSR factors to improve the population health in both countries, which are also crucial for promoting LE growth in the Gulf Cooperation Council region.

The Effect of Public Healthcare Expenditure on the Reduction in Mortality Rates Caused by Unhealthy Habits among the Population

The health systems of developed countries aim to reduce the mortality rates of their populations. To this end, they must fight against the unhealthy habits of citizens, such as smoking, excessive alcohol consumption, and sedentarism, since these result in a large number of deaths each year. Our research aims to analyze whether an increase in health resources influences the number of deaths caused by the unhealthy habits of the population. To achieve this objective, a sample containing key indicators of the Spanish health system was analyzed using the partial least squares structural equation modeling (PLS-SEM) method. The results show how increasing public health spending and, thus, the resources allocated to healthcare can curb the adverse effects of the population’s unhealthy habits. These results have important implications for theory and practice, demonstrating the need for adequate investment in the healthcare system to reduce mortality among the population.

Analysis of Patient Satisfaction through the Effect of Healthcare Spending on Waiting Times for Consultations and Operations

In recent years, public authorities have invested large amounts of public money in trying to reduce waiting times for consultations and operations with the aim of improving the quality of the healthcare system. Our research aims to analyze the effect of these investments on patient satisfaction through the mediating relationship of waiting times for consultations and operations, as well as from a gender perspective. By studying a series of key indicators of the Spanish healthcare system and applying partial least squares structural equation modelling (PLS-SEM), the findings show that the model explains 12.10% of the variance in consultant waiting times, 51.90% in operation waiting times, and 27.00% in patient satisfaction. We found that increased public spending leads to increased patient satisfaction by reducing waiting times. However, no gender-based differences were found. The results provide exciting implications for theory and practice, indicating how policymakers can orient their strategies towards improving patient satisfaction.

Health Policies Based on Patient Satisfaction: A Bibliometric Study

Healthcare decision-makers increasingly face a changing and ever-evolving landscape, forcing them to formulate public policies based on the results from different scientific investigations. This article evaluates the field of research on patient satisfaction as a basis for health policies. The analysis was carried out with a sample of 621 articles published between 2000 and 2020 in the Scopus database. The world's largest producer and research co-operator on patient satisfaction and health policy was the United States. However, the most prolific authors, institutions, and journals are of British origin. Regarding the themes, we find that, in economic and management matters, scientific production is scarce. To study the evolution of keywords, we divided the study period into two periods of an equal number of years. In both sub-periods, the keyword "Human" stands out. In the second sub-period, the word "Perception" stands out, which indicates the current attention paid to the patient's opinion.

Does descending health resources reform impact patient low-level hospital selection behavior? Evidence from Zhejiang, China

Background

Since 2013, China launched descending resources reform, which is a new attempt to correct unbalanced allocation of health resources through human capital spillovers and brand implantation from high-level hospitals. The purpose of this paper is to explore the patients’ hospital selection response to this reform with the focus of low-level hospitals to better understand the effect of this reform on correcting regional inequality of health resources allocation.

Methods

The European Consumer Satisfaction Index model (ECSI) was used to design a questionnaire, and cross-sectional data from 17 hospitals were collected through 1287 questionnaires from Zhejiang Province. Patient hospital selection (loyalty) is measured using ordinary variables by considering patient willingness to choose a low-level hospital when suffering an illness or severe illness. Analysis of variance (ANOVA) and the structure equation model are applied to examine the effect of reforms on patient behavior.

Results

The descending resources reform promotes improvements in the capabilities and medical environment of low-level hospitals, and descending doctors also have high accessibility. Perceived quality, patient expectations, and hospital image have significant positive effects on patient satisfaction, and the explanatory power of brand implantation from cooperative high-level hospitals and descending doctors is stronger than the image of the low-level hospital itself. And descending resources reform and patient satisfaction have significant positive impacts on patient’s choice for low-level hospitals with the existence of mediating effect of satisfaction.

Conclusions

This paper provides supporting empirical evidence of the descending resources reform’s impact on patients’ low-level hospital selection. This reform has been effective in improving the capabilities of low-level hospitals, and brand implantation of high-level hospitals shows strong explanatory power. China’s reform offers a distinct and valuable approach to correcting the uneven allocation of health resources. Besides, the findings also suggest that policymakers could pay more attention to the importance of information channels in impacting patient awareness, responses, and hospital selection.

Using Higher-Order Constructs to Estimate Health-Disease Status: The Effect of Health System Performance and Sustainability

This article aims to provide information to public agencies and policymakers on the determinants of health systems and their relationships that influence citizens’ health–disease status. A total of 61 indicators for each of 17 Spanish autonomous communities were collected from the Spanish Ministry of Health, Social Services, and Equality between 2008 and 2017. The applied technique was partial least squares structural equation modeling (PLS-SEM). Concerning health–disease status, an influence of sustainability and performance on the health system was hypothesized. The findings revealed that health system sustainability had a negative effect on health–disease status, measured in terms of disease incidence. However, the relationship between health system performance and health–disease status is positive. Furthermore, health system performance mediates the relationship between sustainability and health–disease status. According to our study, if we consider the opposite poles that make up the definition of health–disease status (well-being and disease), this concept is defined more by the incidence of the negative aspect.

Using Social Media Mining and PLS-SEM to Examine the Causal Relationship between Public Environmental Concerns and Adaptation Strategies

With growing scientific evidence showing the harmful impact of air pollution on the environment and individuals’ health in modern societies, public concern about air pollution has become a central focus of the development of air pollution prevention policy. Past research has shown that social media is a useful tool for collecting data about public opinion and conducting analysis of air pollution. In contrast to statistical sampling based on survey approaches, data retrieved from social media can provide direct information about behavior and capture long-term data being generated by the public. However, there is a lack of studies on how to mine social media to gain valuable insights into the public’s pro-environmental behavior. Therefore, research is needed to integrate information retrieved from social media sites into an established theoretical framework on environmental behaviors. Thus, the aim of this paper is to construct a theoretical model by integrating social media mining into a value-belief-norm model of public concerns about air pollution. We propose a hybrid method that integrates text mining, topic modeling, hierarchical cluster analysis, and partial least squares structural equation modelling (PLS-SEM). We retrieved data regarding public concerns about air pollution from social media sites. We classified the topics using hierarchical cluster analysis and interpreted the results in terms of the value-belief-norm theoretical framework, which encompasses egoistic concerns, altruistic concerns, biospheric concerns, and adaptation strategies regarding air pollution. Then, we used PLS-SEM to confirm the causal relationships and the effects of mediation. An empirical study based on the concerns of Taiwanese social media users about air pollution was used to demonstrate the feasibility of the proposed framework in general and to examine gender differences in particular. Based on the results of the empirical studies, we confirmed the robust effects of egoistic, altruistic, and biospheric concerns of public impact on adaptation strategies. Additionally, we found that gender differences can moderate the causal relationship between egoistic concerns, altruistic concerns, and adaptation strategies. These results demonstrate the effectiveness of enhancing perceptions of air pollution and environmental sustainability by the public. The results of the analysis can serve as a basis for environmental policy and environmental education strategies.

Who Is More Satisfied with Health Services? A Cross-Sectional Study in China

This cross-sectional study aims to assess the Chinese population’s satisfaction with health service and identify 2 types of variables, Andersen’s behavioral model related variables and social environment variables associated with high satisfaction. Data were derived from the 2013 Chinese General Social Survey (CGSS). Using exploratory factor analysis, the original questionnaire’s 10 health services were grouped into 2 dimensions, including “health management service” and “public health service.” Then, the satisfaction was described. The associations between satisfaction and factors were assessed using a multivariable logistic regression model. As a result, a total of 5283 subjects were enrolled. The satisfaction was 56.74% for “health management service” and 54.48% for “public health service.” Those with older age, lower education level, positive social environment factors (ie, higher perceived social class, higher perceived social trust, and perceived social equity), and having pension were more likely to report high satisfaction. Moreover, compared to the east region (the most prosperous region), the individuals from the central region or the north-east region (both regional economic levels were medium) had lower odds of reporting high satisfaction. In comparison, those from the west region (the least developed region) had higher odds. In conclusion, actionable measures to increase satisfaction should be proposed by the Chinese government, including increasing pension insurance coverage, increasing investment in health services, creating an excellent social environment, etc.

Health Investment Management and Healthcare Quality in the Public System: A Gender Perspective

The aim of this empirical research was to provide useful information for health system managers on the costs and investments involved in improving the quality of the National Health Service (NHS) based on patient assessments and from a gender perspective, i.e., without assuming that the perceived experience is identical for men and women. A cross-sectional study of 31 variables was applied using partial least squares structural equation modeling (PLS-SEM) as a research tool. The data were obtained from the Spanish Ministry of Health, Consumption, and Social Welfare for the entire Spanish territory between 2005 and 2018. The influence of expenditure, resource allocation, and mortality was hypothesized with regard to patient satisfaction according to disconfirmation theory. Patient satisfaction reflects clinical effectiveness, and therefore is a measure of health system quality. The results show that women are more sensitive to public investment in health than men, i.e., an increase in the level of spending and resources increases satisfaction more in women. In both sexes, the level of expenditure has a direct influence on patient satisfaction, and therefore on the quality of the healthcare system. It is important to increase spending on primary care, especially on specialized medical care and diagnostic equipment. However, reducing the use of drugs in favor of alternative treatments or therapies is considered to be positive. Likewise, spending has an impact on available resources, and these, in turn, have a positive influence on the level of use and a negative impact on mortality. Resources, especially healthcare staff, nuclear magnetic resonance equipment, and the number of posts in day hospitals, increase patients’ positive perception of the NHS.

Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research

This is a commentary on methodological challenges and analytical requirements in designing an evaluation of the knowledge, motivation, attitude, preventive practice-outcome (KMAP-O) model for selfcare management of diabetes. Critical issues pertaining to an investigation of the dose-response relationship between the intervention program and outcomes, the comparative effectiveness evaluation, and the lengths of observation were noted. Although numerous publications on factors influencing diabetes care and control were systematically reviewed and documented in the literature, scientific results on artificial intelligence research remain to be uncovered. To optimizing the knowledge and clinical practice in selfcare management, specific methodological approaches to predictive analytics are suggested for future clinical studies, using a comprehensive behavioral system such as the KMAP-O model.

Attitude to COVID-19 Prevention With Large-Scale Social Restrictions (PSBB) in Indonesia: Partial Least Squares Structural Equation Modeling

There is a continuous increase in the number of COVID-19 cases in Indonesia. To control its spread, the government has implemented several strategies, such as policies associated with large-scale social restrictions (Indonesian: Pembatasan Sosial Berskala Besar or PSBB). The purpose of this study is to determine the variables that influence attitudes toward PSBB policies in Indonesia. This is a cross-sectional study with data obtained from 856 respondents from all provinces in Indonesia using the partial least squares and structural equation model (PLS-SEM). A total of 23 indicators were used to examine these policies, which were grouped into five variables: benefits of the PSBB (5 indicators), positive perception (5 indicators), negative perception (3 indicators), threatened perceptions of COVID-19 (5 indicators), and attitude toward the PSBB policy (5 indicators). The model explains over 50% of attitudes exhibited toward PSBB policy implementation and how it is influenced by the perceived benefits, negative and positive perceptions as well as the threat associated with COVID-19. The policy of stay at home, physical distancing, and always using face masks needs to be continued for the public to have a supportive attitude of the PSBB policy in preventing the transmission of COVID-19.

A Derivation of Factors Influencing the Diffusion and Adoption of an Open Source Learning Platform

During the past two decades, open source learning platforms (OSLPs) have become a dominant part of modern education. OSLPs are free for usage and customization—unlike proprietary software restricted by copyright licenses. By utilizing OSLPs, users can download and use the source code, write new features, fix bugs, improve performances, or learn from others how specific problems can be solved. Albeit dominant, the frequency of usage and motivation of OSLPs by students is not high; however, there has been very little research about this, and the problem is significant. Therefore, this research aimed to derive the factors that affect the adoption and diffusion of OSLPs. The factors on the diffusion and adoption were defined based on the innovation diffusion theory (IDT) and the technology acceptance model (TAM), where the integrated theoretical framework is called the IDT-TAM. Partial Least Square structural equation modeling was used to confirm the hypothesized IDT-TAM. An empirical study was based on the sample data collected from 340 Taiwanese technical university students to demonstrate the feasibility of the analytical framework and derive the factors related to the adoption and diffusion of the OSLP for students. Based on the results of the empirical study, through the mediation of perceived attitude (PA) and perceived usefulness (PU), trialability (TL), observability (OS), ease of use (EU), and relative advantage (RA) are the factors most related to the diffusion and acceptance of the OSLP innovations. The analytical results can serve as the basis for the design, development, and enhancement of acceptance and diffusion of OSLP.

Determinants of life expectancy and clustering of provinces to improve life expectancy: an ecological study in Indonesia

BACKGROUND

Life expectancy acts as a population measure of the performance of healthcare systems. Regional disparities on life expectancy in Indonesia has been persisted and become a public health policy challenge. A systematic clustering of provinces can be a valuable alternative for organizing cooperation that aimed to increase life expectancy and reduce disparities. This study aimed to identify determinants of life expectancy and designate clusters of Indonesian provinces with similar characteristics. This approach can be useful in generating alternative cooperation strategies to improve life expectancy.

METHODS

We carefully selected variables that have been shown to impact life expectancy and gathered 2015 data from Indonesia's Ministry of Health. All 34 Indonesian provinces were included as analysis units. We performed structural equation modeling (SEM) to select domains that needed to work on from theoretical models. Based on SEM results, we performed cluster analysis to arrange cooperation groups.

RESULTS

Life expectancy showed correlations with mean years of schooling, expenditure per capita, health workforce, healthcare facilities, and environment. Expenditure per capita also was the strongest of all constructs. Based on SEM results, we performed cluster analysis to arrange cooperation groups of total 34 provinces and generated five clusters of provinces.

CONCLUSIONS

Enhancing the economy is the most effective approach for improving life expectancy and other constructs. These clusters can build cooperation that is new, within, and across clusters. These results may be useful in formulating cooperation strategies aimed at increasing life expectancy.