The Perspective of Balancing the Economic Growth of Healthcare Systems and Environmental Prevention

Based on real situations that mankind is confronting with the difficult era; insufficiency in food supplies, natural disasters, epidemic, etc. The paper is to econometrically compute portfolio optimization and predict efficiency frontiers for solving the most sensible scenario to suggest a sustainable policy in the three important pillars such as the growth of economic systems, environmental management, and public healthcare. The main observations are annual time-series information between 2000 and 2017 and collected from three countries in ASEAN. Singapore, Thailand, and Malaysia are the target. Methodologically, this research is to apply the quantum mechanism and the wave function for clarifying a real data distribution; true mean, and standard deviation of the data. These outcomes are the initial raw material for the modern portfolio optimization (for short-run policies) and efficient frontier computation (for long-term policies). Empirically, the results show some exclusive issues that can be the help for managing feasible budget allocations fairly and sustainably.

The perspective of balancing economic growth healthcare system and environmental prevention the efficient budget for ASEAN-3 countries

Based on real situations that mankind is confronting with the difficult era; insufficiency in food supplies, natural disasters, epidemic, etc. The paper is to econometrically compute portfolio optimization and predict efficiency frontiers for solving the most sensible scenario to suggest a sustainable policy in the three important pillars such as the growth of economic systems, environmental management, and public healthcare. The main observations are annual time-series information between 2000 and 2017 and collected from three countries in ASEAN. Singapore, Thailand, and Malaysia are the target. Methodologically, this research is to apply the quantum mechanism and the wave function for clarifying a real data distribution; true mean, and standard deviation of the data. These outcomes are the initial raw material for the modern portfolio optimization (for short-run policies) and efficient frontier computation (for long-term policies). Empirically, the results show some exclusive issues that can be the help for managing feasible budget allocations fairly and sustainably.

Profile and Predictors of Maternal Quality of Life During Physiological Pregnancy: A Cross-Sectional Analysis

BackgroundQuality of Life (QoL) and its determinants are significant in all stages of life, including pregnancy. The physical and emotional changes during pregnancy affect the QoL of pregnant women, affecting both maternal and infant health. Hence, assessing the QoL of pregnant women is gaining interest in literature. We, therefore, aimed to describe the QoL of pregnant women during physiological pregnancy and to identify its associated predictors in women attending a public healthcare institute of Quetta city, Pakistan.MethodsA cross-sectional study was conducted at the Obstetrics and Gynecology Department of Sandeman Provincial Hospital Quetta city, Pakistan. The respondents were asked to answer the Urdu (lingua franca of Pakistan) version of the Quality of Life Questionnaire for Physiological Pregnancy. Data were coded and analyzed by SPPS v 21. The Kolmogorov–Smirnov test was used to establish normality of the data and non-parametric tests were used accordingly. Quality of Life was assessed as proposed by the developers. The Chi-square test was used to identify significant associations and linear regression was used to identify the predictors of QoL. For all analyses, p < 0.05 was taken significantly.ResultsFour hundred and three pregnant women participated in the study with a response rate of 98%. The mean QoL score was 19.85 ± 4.89 indicating very good QoL in the current cohort. The Chi-Square analysis reported a significant association between age, education, occupation, income, marital status, and trimester. Education was reported as a positive predictor for QoL (p = 0.006, β = 2.157). On the other hand, trimester was reported as a negative predictor of QoL (p = 0.013, β = −1.123).ConclusionImproving the QoL among pregnant women requires better identification of their difficulties and guidance. The current study highlighted educational status and trimester as the predictors of QoL in pregnant women. Health care professionals and policymakers should consider the identified factors while designing therapeutic plans and interventions for pregnant women.

Impact of the Expert Consensus on Carbapenem Consumption Trends and Patterns in Public Healthcare Institutes: An Interrupted Time Series Analysis, 2017–2020

Background: Carbapenems are considered the last line of defence against bacterial infections, but their high consumption and the resulting antibacterial resistance are an increasing global concern. In this context, the Chinese health authority issued an expert consensus on the clinical applications of carbapenems. However, the long- and short-term effects of the expert consensus on carbapenem use are not clear.Methods: This study was conducted in Shaanxi, a northwest province of China. We collected all available carbapenem procurement data between January 2017 and December 2020 from the Provincial Drug Centralized Bidding Procurement System. A quasi-experimental interrupted time series analysis was used to evaluate the longitudinal effectiveness of expert consensus by measuring the change in the Defined Daily Dosesper 1,000 inhabitants per day (DID), the percentage of carbapenem expenditures to total antimicrobial expenditure, the total carbapenem expenditure, and the defined daily cost (DDDc). We used Stata SE version 15.0 for data analysis, and p < 0.05 was considered statistically significant.Results: After the distribution of the expert consensus, the level (p = 0.769) and trend (p = 0.184) of DID decreased, but the differences were not statistically significant. The percentage of carbapenem expenditures to total antimicrobial expenditure decreased abruptly (p < 0.001) after the intervention, but the long-term trend was still upward. There was no statistically significant relationship between the release of the expert consensus and carbapenem expenditure in the long term, but there was a decreasing trend (p = 0.032). However, the expert consensus had a positive impact on the economic burden of carbapenem usage in patients, as the level (p < 0.001), and trend (p = 0.003) of DDDc significantly decreased.Conclusion: The long-term effects of the distribution of the expert consensus on the use and expenditure of carbapenems in public health institutions in Shaanxi Province were not optimal. It is time to set up more administrative measures and scientific supervision to establish a specific index to limit the application of carbapenems.

Use of 30-Hz Accelerated iTBS in Drug-Resistant Unipolar and Bipolar Depression in a Public Healthcare Setting: A Case Series

Background: Depressive episodes, especially when resistant to pharmacotherapy, are a hard challenge to face for clinicians and a leading cause of disability worldwide. Neuromodulation has emerged as a potential therapeutic option for treatment-resistant depression (TRD), in particular transcranial magnetic stimulation (TMS). In this article, we present a case series of six patients who received TMS with an accelerated intermittent theta-burst stimulation (iTBS) protocol in a public healthcare setting.Methods: We enrolled a total number of six participants, affected by a treatment-resistant depressive episode, in either Major Depressive Disorder (MDD) or Bipolar Disorder (BD). Patients underwent an accelerated iTBS protocol, targeted to the left dorsolateral prefrontal cortex (DLPFC), 3-week-long, with a total of 6 days of overall stimulation. On each stimulation day, the participants received 3 iTBS sessions, with a 15-min pause between them. Patients were assessed by the Hamilton Rating Scale for Depression (HAM-D), the Montgomery-Asberg Depression Rating Scale (MADRS), the Hamilton Rating Scale for Anxiety (HAM-A), and the Mania Rating Scale (MRS). At baseline (T0), at the end of the second week (T1), and at the end of the cycle of stimulation (T2).Results: The rANOVA (repeated Analysis of Variance) statistics showed no significant effect of time on the rating scale scores, with a slight decrease in MADRS scores and a very slight increase in HAM-A and HAM-D scores. No manic symptoms emerged during the entire protocol.Conclusions: Although accelerated iTBS might be considered a less time-consuming strategy for TMS administration, useful in a public healthcare setting, our results in a real-word six-patient population with TRD did not show a significant effect. Further studies on wider samples are needed to fully elucidate the potential of accelerated iTBS protocols in treatment-resistant depression.

Evaluating the effectiveness of care coordination interventions designed and implemented through a participatory action research process: Lessons learned from a quasi-experimental study in public healthcare networks in Latin America

Background Despite increasing recommendations for health professionals to participate in intervention design and implementation to effect changes in clinical practice, little is known about this strategy’s effectiveness. This study analyses the effectiveness of interventions designed and implemented through participatory action research (PAR) processes in healthcare networks of Brazil, Chile, Colombia, Mexico and Uruguay to improve clinical coordination across care levels, and offers recommendations for future research. Methods The study was quasi-experimental. Two comparable networks, one intervention (IN) and one control (CN), were selected in each country. Baseline (2015) and evaluation (2017) surveys of a sample of primary and secondary care doctors (174 doctors/network/year) were conducted using the COORDENA® questionnaire. Most of the interventions chosen were based on joint meetings, promoting cross-level clinical agreement and communication for patient follow-up. Outcome variables were: a) intermediate: interactional and organizational factors; b) distal: experience of cross-level clinical information coordination, of clinical management coordination and general perception of coordination between levels. Poisson regression models were estimated. Results A statistically significant increase in some of the interactional factors (intermediate outcomes) -knowing each other personally and mutual trust- was observed in Brazil and Chile INs; and in some organizational factors -institutional support- in Colombia and Mexico. Compared to CNs in 2017, INs of Brazil, Chile, Colombia and Mexico showed significant differences in some factors. In distal outcomes, care consistency items improved in Brazil, Colombia and Uruguay INs; and patient follow-up improved in Chile and Mexico. General perception of clinical coordination increased in Brazil, Colombia and Mexico INs. Compared to CNs in 2017, only Brazil showed significant differences. Conclusions Although more research is needed, results show that PAR-based interventions improved some outcomes regarding clinical coordination at network level, with differences between countries. However, a PAR process is, by definition, slow and gradual, and longer implementation periods are needed to achieve greater penetration and quantifiable changes. The participatory and flexible nature of interventions developed through PAR processes poses methodological challenges (such as defining outcomes or allocating individuals to different groups in advance), and requires a comprehensive mixed-methods approach that simultaneously evaluates effectiveness and the implementation process to better understand its outcomes.

What motivates physicians to propose private services in a mixed private-public healthcare system? A mixed methods study

Background Implementation of private elements, including private insurances, in public healthcare system is now common in many countries, and its impacts have been well studied. Little, however, is known about the motives leading physicians, major role players in the system, to promote the usage of private services. The aim of this study was to explore the various motives leading physicians within public systems to propose private services to their patients, while examining the possible associations to their specialty and level of commitment. Methods A total of 197 physicians from specialisms loaded more to private/public sectors participated in a cross-sectional telephone survey regarding their attitudes on their practices, private insurances, access to healthcare, and job satisfaction. The association between the likert scale questions to their recommendation to purchase private insurance, and the commitment they felt towards patients were analyzed using Generalized Estimating Equations (GEE) as well as logistic regression models. Results Our findings suggest physicians engaged in dual practice are less likely to promote private insurances among their patients if they are satisfied with their public job (OR = 0.92, 95%CI 0.89,0.94). Physicians perceived private insurances as beneficial for patients, were found likely to promote them (OR = 1.65, %95CI 1.16, 2.35). The commitment physicians felt toward patients who paid out-of-pocket money was associated to their sense of being trusted and valued (OR = 1.99, 95%CI 1.33, 2.88; OR = 1.5, 95%CI 1.05, 2.13 respectively). Conclusion This study suggests a deeper understanding of physicians’ daily experience of the private-public mix and it’s consequences, and could provide a platform for future studies. Further studies on physician’s role in health privatization processes are needed, and could aid policymakers in their efforts to strengthen healthcare systems around the world.

Estimation of Underreported Cases of Infections and Deaths from COVID-19 for Countries with Limited and Scarce Data: Examples from Nepal

COVID-19 pandemic has overburdened the public healthcare system around the world. Further, lockdown imposed to curb the spread of pandemic has shown to have an adverse effect on economic and health status of an individual. It has also compelled us to switch from the physical world to virtual world, thus depriving us of benefits of person-to-person direct contact. People from developing countries are specially affected. An average person here lacks basic skills needed to survive in the digital world. Due to limited COVID-19 testing capacities in such countries, there is also less testing. Less testing means less contact tracing, underreported cases, and rapid spread of disease. In this paper, the underreported cases of daily infections and daily deaths are predicted using mathematical models. This is based on daily data published by the Government of Nepal. Here, Kathmandu valley is taken as a model area for estimation of underreporting. The behavior of probability of infection, probability of recovery, and probability of deaths is also mathematically analyzed. A time-dependent susceptible infected and recovered model is also proposed. Here, the second wave of COVID-19 is analyzed in detail from 1 Feb 2021 to 1 June 2021. The effect of lockdown on the psychology of people is also modeled with principal components analysis. The inherent and latent factors affecting the people in lockdown are identified. This is based on detailed primary data collected from a survey of 277 households.

PrAna: an R package to calculate and visualize England NHS primary care prescribing data

Background The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage. Design We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England’s national level prescription data provided by National Health Service, for the years 2015–2018. Datasets generated using PrAna can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region. Results PrAnaViz’s targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region. Conclusion PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.