Effect of lifting COVID-19 restrictions on utilisation of primary care services in Nepal: a difference-in-differences analysis

INTRODUCTION: An increasing number of studies have reported disruptions in health service utilisation due to the COVID-19 pandemic and its associated restrictions. However, little is known about the effect of lifting COVID-19 restrictions on health service utilisation. The objective of this study was to estimate the effect of lifting COVID-19 restrictions on primary care service utilisation in Nepal. METHODS: Data on utilisation of 10 primary care services were extracted from the Health Management Information System across all health facilities in Nepal. We used a difference-in-differences design and linear fixed effects regressions to estimate the effect of lifting COVID-19 restrictions. The treatment group included palikas that had lifted restrictions in place from 17 August 2020 to 16 September 2020 (Bhadra 2077) and the control group included palikas that had maintained restrictions during that period. The pre-period included the 4 months of national lockdown from 24 March 2020 to 22 July 2020 (Chaitra 2076 to Ashar 2077). Models included month and palika fixed effects and controlled for COVID-19 incidence. RESULTS: We found that lifting COVID-19 restrictions was associated with an average increase per palika of 57.5 contraceptive users (95% CI 14.6 to 100.5), 15.6 antenatal care visits (95% CI 5.3 to 25.9) and 1.6 child pneumonia visits (95% CI 0.2 to 2.9). This corresponded to a 9.4% increase in contraceptive users, 34.2% increase in antenatal care visits and 15.6% increase in child pneumonia visits. Utilisation of most other primary care services also increased after lifting restrictions, but coefficients were not statistically significant. CONCLUSIONS: Despite the ongoing pandemic, lifting restrictions can lead to an increase in some primary care services. Our results point to a causal link between restrictions and health service utilisation and call for policy makers in low- and middle-income countries to carefully consider the trade-offs of strict lockdowns during future COVID-19 waves or future pandemics

Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis

BACKGROUND: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses are concentrated in high-income countries and focus on hospitals. We used the positive deviance approach to identify the factors that differentiate best from worst primary care performance among health facilities across six low-resource health systems. METHODS: This positive deviance analysis used nationally representative samples of public and private health facilities from Service Provision Assessments of the Democratic Republic of the Congo, Haiti, Malawi, Nepal, Senegal, and Tanzania. Data were collected starting June 11, 2013, in Malawi and ending Feb 28, 2020, in Senegal. We assessed facility performance through completion of the Good Medical Practice Index (GMPI) of essential clinical actions (eg, taking a thorough history, conducting an adequate physical examination) according to clinical guidelines and measured with direct observations of care. We identified hospitals and clinics in the top decile of performance (defined as best performers) and conducted a quantitative, cross-national positive deviance analysis to compare them with facilities performing below the median (defined as worst performers) and identify facility-level factors that explain the gap between best and worst performance. FINDINGS: We identified 132 best-performing and 664 worst-performing hospitals, and 355 best-performing and 1778 worst-performing clinics based on clinical performance across countries. The mean GMPI score was 0.81 (SD 0.07) for the best-performing hospitals and 0.44 (0.09) for the worst-performing hospitals. Among clinics, mean GMPI scores were 0.75 (0.07) for the best performers and 0.34 (0.10) for the worst performers. High-quality governance, management, and community engagement were associated with best performance compared with worst performance. Private facilities out-performed government-owned hospitals and clinics. INTERPRETATION: Our findings suggest that best-performing health facilities are characterised by good management and leaders who can engage staff and community members. Governments should look to best performers to identify scalable practices and conditions for success that can improve primary care quality overall and decrease quality gaps between health facilities. FUNDING: Bill & Melinda Gates Foundation

Journal of Telecommunications and Information Technology, 2018, nr 1

This paper proposes a fuzzy Manhattan distance-based similarity for gang formation of resources (FMDSGR) method with priority task scheduling in cloud computing. The proposed work decides which processor is to execute the current task in order to achieve efficient resource utilization and effective task scheduling. FMDSGR groups the resources into gangs which rely upon the similarity of resource characteristics in order to use the resources effectively. Then, the tasks are scheduled based on the priority in the gang of processors using gang-based priority scheduling (GPS). This reduces mainly the cost of deciding which processor is to execute the current task. Performance has been evaluated in terms of makespan, scheduling length ratio, speedup, efficiency and load balancing. CloudSim simulator is the toolkit used for simulation and for demonstrating experimental results in cloud computing environments

Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium

COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions

Mitochondrial targeting theranostic nanomedicine and molecular biomarkers for efficient cancer diagnosis and therapy.

Mitochondria play a crucial part in the cell's ability to adapt to the changing microenvironments and their dysfunction is associated with an extensive array of illnesses, including cancer. Mitochondrial dysfunction has been identified as a potential therapeutic target for cancer therapy. The objective of this article is to give an in-depth analysis of cancer treatment that targets the mitochondrial genome at the molecular level. Recent studies provide insights into nanomedicine techniques and theranostic nanomedicine for mitochondrial targeting. It also provides conceptual information on mitochondrial biomarkers for cancer treatment. Major drawbacks and challenges involved in mitochondrial targeting for advanced cancer therapy have also been discussed. There is a lot of evidence and reason to support using nanomedicine to focus on mitochondrial function. The development of a delivery system with increased selectivity and effectiveness is a prerequisite for a theranostic approach to cancer treatment. If given in large amounts, several new cancer-fighting medicines have been created that are toxic to healthy cells as well. For effective therapy, a new drug must be developed rather than an old one. When it comes to mitochondrial targeting therapy, theranostic techniques offer valuable insight

Expression of chemokine receptor CXCR4 in esophageal squamous cell and adenocarcinoma

BACKGROUND: Prognosis of esophageal cancer is poor despite curative surgery. The chemokine receptor CXCR4 has been proposed to distinctly contribute to tumor growth, dissemination and local immune escape in a limited number of malignancies. The aim of our study was to evaluate the role of CXCR4 in tumor spread of esophageal cancer with a differentiated view of the two predominant histologic types – squamous cell and adenocarcinoma. METHODS: Esophageal cancer tissue samples were obtained from 102 consecutive patients undergoing esophageal resection for cancer with curative intent. The LSAB+ System was used to detect the protein CXCR4. Tumor samples were classified into two groups based on the homogeneous staining intensity. A cut-off between CXCR4w (= weak expression) and CXCR4s (= strong expression) was set at 1.5 (grouped 0 – 1.5 versus 2.0 – 3). Long-term survival rates were calculated using life tables and the Kaplan-Meier method. Using the Cox's proportional hazards analysis, a model of survival prediction was established. RESULTS: The overall expression rate for CXCR4 in esophageal squamous cell carcinoma was 94.1%. Subdividing these samples, CXCR4w was found in 54.9% and CXCR4s in 45.1%. In adenocarcinoma, an overall expression rate of 89.1% was detected with a weak intensitiy in 71.7% compared to strong staining in 29.3% (p = 0.066 squamous cell versus adenocarcinoma). The Cox's proportional hazards analysis identified the pM-category with a hazard ratio (HR) of 1.860 (95% CI: 1.014–3.414) (p = 0.045), the histologic tumor type (HR: 0.334; 95% CI: 0.180–0.618) (p = 0.0001) and the operative approach (transthoracic > transhiatal esophageal resection) (HR: 0.546; 95% CI: 0.324–0.920) (p = 0.023) as independent factors with a possible influence on the long-term prognosis in patients with esophageal carcinoma, whereas CXCR4 expression was statistically not significant (>0.05). CONCLUSION: Expression of the chemokine receptor CXCR4 in esophageal cancer is of major relevance in both histologic entities – squamous cell and adenocarcinoma. Though with lack of statistical significance, strong CXCR4 expression revealed a poorer long-term prognosis following curative esophagectomy in both histologic subtypes. Thus, the exact biological functions of CXCR4 in terms of tumor dissemination of esophageal cancer is yet undetermined. Inhibition of esophageal cancer progression by CXCR4 antagonists might be a promising therapeutic option in the future

Diseases, Injuries, and Risk Factors in Child and Adolescent Health, 1990 to 2017: Findings From the Global Burden of Diseases, Injuries, and Risk Factors 2017 Study.

Importance:Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies. Objective:To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories. Design, Setting, and Participants:This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis. It also describes epidemiologic transitions by evaluating historical associations between disease indicators and the Socio-Demographic Index (SDI), a composite indicator of income, educational attainment, and fertility. Data collected from 1990 to 2017 on children and adolescents from birth through 19 years of age in 195 countries and territories were assessed. Data analysis occurred from January 2018 to August 2018. Exposures:Being under the age of 20 years between 1990 and 2017. Main Outcomes and Measures:Death and disability. All-cause and cause-specific deaths, disability-adjusted life years, years of life lost, and years of life lived with disability. Results:Child and adolescent deaths decreased 51.7% from 13.77 million (95% uncertainty interval [UI], 13.60-13.93 million) in 1990 to 6.64 million (95% UI, 6.44-6.87 million) in 2017, but in 2017, aggregate disability increased 4.7% to a total of 145 million (95% UI, 107-190 million) years lived with disability globally. Progress was uneven, and inequity increased, with low-SDI and low-middle-SDI locations experiencing 82.2% (95% UI, 81.6%-82.9%) of deaths, up from 70.9% (95% UI, 70.4%-71.4%) in 1990. The leading disaggregated causes of disability-adjusted life years in 2017 in the low-SDI quintile were neonatal disorders, lower respiratory infections, diarrhea, malaria, and congenital birth defects, whereas neonatal disorders, congenital birth defects, headache, dermatitis, and anxiety were highest-ranked in the high-SDI quintile. Conclusions and Relevance:Mortality reductions over this 27-year period mean that children are more likely than ever to reach their 20th birthdays. The concomitant expansion of nonfatal health loss and epidemiological transition in children and adolescents, especially in low-SDI and middle-SDI countries, has the potential to increase already overburdened health systems, will affect the human capital potential of societies, and may influence the trajectory of socioeconomic development. Continued monitoring of child and adolescent health loss is crucial to sustain the progress of the past 27 years