Socioeconomic inequalities in mortality, morbidity and diabetes management for adults with type 1 diabetes: A systematic review.

AIMS: To systematically review the evidence of socioeconomic inequalities for adults with type 1 diabetes in relation to mortality, morbidity and diabetes management. METHODS: We carried out a systematic search across six relevant databases and included all studies reporting associations between socioeconomic indicators and mortality, morbidity, or diabetes management for adults with type 1 diabetes. Data extraction and quality assessment was undertaken for all included studies. A narrative synthesis was conducted. RESULTS: A total of 33 studies were identified. Twelve cohort, 19 cross sectional and 2 case control studies met the inclusion criteria. Regardless of healthcare system, low socioeconomic status was associated with poorer outcomes. Following adjustments for other risk factors, socioeconomic status was a statistically significant independent predictor of mortality in 9/10 studies and morbidity in 8/10 studies for adults with type 1 diabetes. There appeared to be an association between low socioeconomic status and some aspects of diabetes management. Although only 3 of 16 studies made adjustments for confounders and other risk factors, poor diabetes management was associated with lower socioeconomic status in 3/3 of these studies. CONCLUSIONS: Low socioeconomic status is associated with higher levels of mortality and morbidity for adults with type 1 diabetes even amongst those with access to a universal healthcare system. The association between low socioeconomic status and diabetes management requires further research given the paucity of evidence and the potential for diabetes management to mitigate the adverse effects of low socioeconomic status

High-quality health systems in the Sustainable Development Goals era: time for a revolution.

Executive summary: Although health outcomes have improved in low-income and middle-income countries (LMICs) in the past several decades, a new reality is at hand. Changing health needs, growing public expectations, and ambitious new health goals are raising the bar for health systems to produce better health outcomes and greater social value. But staying on current trajectory will not suffice to meet these demands. What is needed are high-quality health systems that optimise health care in each given context by consistently delivering care that improves or maintains health, by being valued and trusted by all people, and by responding to changing population needs. Quality should not be the purview of the elite or an aspiration for some distant future; it should be the DNA of all health systems. Furthermore, the human right to health is meaningless without good quality care because health systems cannot improve health without it. We propose that health systems be judged primarily on their impacts, including better health and its equitable distribution; on the confidence of people in their health system; and on their economic benefit, and processes of care, consisting of competent care and positive user experience. The foundations of high-quality health systems include the population and their health needs and expectations, governance of the health sector and partnerships across sectors, platforms for care delivery, workforce numbers and skills, and tools and resources, from medicines to data. In addition to strong foundations, health systems need to develop the capacity to measure and use data to learn. High-quality health systems should be informed by four values: they are for people, and they are equitable, resilient, and efficient. For this Commission, we examined the literature, analysed surveys, and did qualitative and quantitative research to evaluate the quality of care available to people in LMICs across a range of health needs included in the Sustainable Development Goals (SDGs). We explored the ethical dimensions of high-quality care in resource-constrained settings and reviewed available measures and improvement approaches. We reached five conclusions: The care that people receive is often inadequate, and poor-quality care is common across conditions and countries, with the most vulnerable populations faring the worst Data from a range of countries and conditions show systematic deficits in quality of care. In LMICs, mothers and children receive less than half of recommended clinical actions in a typical preventive or curative visit, less than half of suspected cases of tuberculosis are correctly managed, and fewer than one in ten people diagnosed with major depressive disorder receive minimally adequate treatment. Diagnoses are frequently incorrect for serious conditions, such as pneumonia, myocardial infarction, and newborn asphyxia. Care can be too slow for conditions that require timely action, reducing chances of survival. At the system level, we found major gaps in safety, prevention, integration, and continuity, reflected by poor patient retention and insufficient coordination across platforms of care. One in three people across LMICs cited negative experiences with their health system in the areas of attention, respect, communication, and length of visit (visits of 5 min are common); on the extreme end of these experiences were disrespectful treatment and abuse. Quality of care is worst for vulnerable groups, including the poor, the less educated, adolescents, those with stigmatised conditions, and those at the edges of health systems, such as people in prisons. Universal health coverage (UHC) can be a starting point for improving the quality of health systems. Improving quality should be a core component of UHC initiatives, alongside expanding coverage and financial protection. Governments should start by establishing a national quality guarantee for health services, specifying the level of competence and user experience that people can expect. To ensure that all people will benefit from improved services, expansion should prioritise the poor and their health needs from the start. Progress on UHC should be measured through effective (quality-corrected) coverage. High-quality health systems could save over 8 million lives each year in LMICs More than 8 million people per year in LMICs die from conditions that should be treatable by the health system. In 2015 alone, these deaths resulted in US$6 trillion in economic losses. Poor-quality care is now a bigger barrier to reducing mortality than insufficient access. 60% of deaths from conditions amenable to health care are due to poor-quality care, whereas the remaining deaths result from non-utilisation of the health system. High-quality health systems could prevent 2·5 million deaths from cardiovascular disease, 1 million newborn deaths, 900 000 deaths from tuberculosis, and half of all maternal deaths each year. Quality of care will become an even larger driver of population health as utilisation of health systems increases and as the burden of disease shifts to more complex conditions. The high mortality rates in LMICs for treatable causes, such as injuries and surgical conditions, maternal and newborn complications, cardiovascular disease, and vaccine preventable diseases, illustrate the breadth and depth of the health-care quality challenge. Poor-quality care can lead to other adverse outcomes, including unnecessary health-related suffering, persistent symptoms, loss of function, and a lack of trust and confidence in health systems. Waste of resources and catastrophic expenditures are economic side effects of poor-quality health systems. As a result of this, only one-quarter of people in LMICs believe that their health systems work well. Health systems should measure and report what matters most to people, such as competent care, user experience, health outcomes, and confidence in the system Measurement is key to accountability and improvement, but available measures do not capture many of the processes and outcomes that matter most to people. At the same time, data systems generate many metrics that produce inadequate insight at a substantial cost in funds and health workers' time. For example, although inputs such as medicines and equipment are commonly counted in surveys, these are weakly related to the quality of care that people receive. Indicators such as proportion of births with skilled attendants do not reflect quality of childbirth care and might lead to false complacency about progress in maternal and newborn health. This Commission calls for fewer, but better, measures of health system quality to be generated and used at national and subnational levels. Countries should report health system performance to the public annually by use of a dashboard of key metrics (eg, health outcomes, people's confidence in the system, system competence, and user experience) along with measures of financial protection and equity. Robust vital registries and trustworthy routine health information systems are prerequisites for good performance assessment. Countries need agile new surveys and real-time measures of health facilities and populations that reflect the health systems of today and not those of the past. To generate and interpret data, countries need to invest in national institutions and professionals with strong quantitative and analytical skills. Global development partners can support the generation and testing of public goods for health system measurement (civil and vital registries, routine data systems, and routine health system surveys) and promote national and regional institutions and the training and mentoring of scientists. New research is crucial for the transformation of low-quality health systems to high-quality ones Data on care quality in LMICs do not reflect the current disease burden. In many of these countries, we know little about quality of care for respiratory diseases, cancer, mental health, injuries, and surgery, as well as the care of adolescents and elderly people. There are vast blind spots in areas such as user experience, system competence, confidence in the system, and the wellbeing of people, including patient-reported outcomes. Measuring the quality of the health system as a whole and across the care continuum is essential, but not done. Filling in these gaps will require not only better routine health information systems for monitoring, but also new research, as proposed in the research agenda of this Commission. For example, research will be needed to rigorously evaluate the effects and costs of recommended improvement approaches on health, patient experience, and financial protection. Implementation science studies can help discern the contextual factors that promote or hinder reform. New data collection and research should be explicitly designed to build national and regional research capacity. Improving quality of care will require system-wide action To address the scale and range of quality deficits we documented in this Commission, reforming the foundations of the health system is required. Because health systems are complex adaptive systems that function at multiple interconnected levels, fixes at the micro-level (ie, health-care provider or clinic) alone are unlikely to alter the underlying performance of the whole system. However, we found that interventions aimed at changing provider behaviour dominate the improvement field, even though many of these interventions have a modest effect on provider performance and are difficult to scale and sustain over time. Achieving high-quality health systems requires expanding the space for improvement to structural reforms that act on the foundations of the system. This Commission endorses four universal actions to raise quality across the health system. First, health system leaders need to govern for quality by adopting a shared vision of quality care, a clear quality strategy, strong regulation, and continuous learning. Ministries of health cannot accomplish this alone and need to partner with the private sector, civil society, and sectors outside of health care, such as education, infrastructure, communication, and transport. Second, countries should redesign service delivery to maximise health outcomes rather than geographical access to services alone. Primary care could tackle a greater range of low-acuity conditions, whereas hospitals or specialised health centres should provide care for conditions, such as births, that need advanced clinical expertise or have the risk of unexpected complications. Third, countries should transform the health workforce by adopting competency-based clinical education, introducing training in ethics and respectful care, and better supporting and respecting all workers to deliver the best care possible. Fourth, governments and civil society should ignite demand for quality in the population to empower people to hold systems accountable and actively seek high-quality care. Additional targeted actions in areas such as health financing, management, district-level learning, and others can complement these efforts. What works in one setting might not work elsewhere, and improvement efforts should be adapted for local context and monitored. Funders should align their support with system-wide strategies rather than contribute to the proliferation of micro-level efforts. In this Commission, we assert that providing health services without guaranteeing a minimum level of quality is ineffective, wasteful, and unethical. Moving to a high-quality health system—one that improves health and generates confidence and economic benefits—is primarily a political, not technical, decision. National governments need to invest in high-quality health systems for their own people and make such systems accountable to people through legislation, education about rights, regulation, transparency, and greater public participation. Countries will know that they are on the way towards a high-quality, accountable health system when health workers and policymakers choose to receive health care in their own public institutions.Fil: Kruk, Margaret E.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Gage, Anna D.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Arsenault, Catherine. Harvard University. Harvard School of Public Health; Estados UnidosFil: Jordan, Keely. New York College of Global Public Health; Estados UnidosFil: Leslie, Hannah H.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Roder DeWan, Sanam. Harvard University. Harvard School of Public Health; Estados UnidosFil: Adeyi, Olusoji. Banco Mundial; Estados UnidosFil: Barker, Pierre. Institute For Healthcare Improvement; Estados UnidosFil: Daelmans, Bernadette. Organizacion Mundial de la Salud; SuizaFil: Doubova, Svetlana V.. Instituto Mexicano del Seguro Social; MéxicoFil: English, Mike. KEMRI - Wellcome Trust; KeniaFil: Garcia Elorrio, Ezequiel. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Guanais, Frederico. Banco Interamericano de Desarrollo; Estados UnidosFil: Gureje, Oye. University Of Ibadan; NigeriaFil: Hirschhorn, Lisa R.. Northwestern University; Estados UnidosFil: Jiang, Lixin. National Center For Cardiovascular Diseases; ChinaFil: Kelley, Edward. Organizacion Mundial de la Salud; SuizaFil: Lemango, Ephrem Tekle. Federal Ministry of Health; EtiopíaFil: Liljestrand, Jerker. Bill and Melinda Gates Foundation; Estados UnidosFil: Malata, Address. Malawi University Of Science And Technology; MalauiFil: Marchant, Tanya. London School of Hygiene & Tropical Medicine; Reino UnidoFil: Matsoso, Malebona Precious. National Department of Health of the Republic of South Africa; SudáfricaFil: Meara, John G.. Harvard Medical School; Estados UnidosFil: Mohanan, Manoj. University of Duke; Estados UnidosFil: Ndiaye, Youssoupha. Ministry of Health and Social Action of the Republic of Senegal; SenegalFil: Norheim, Ole F.. University of Bergen; NoruegaFil: Reddy, K. Srinath. Public Health Foundation of India; IndiaFil: Rowe, Alexander K.. Centers for Disease Control and Prevention; Estados UnidosFil: Salomon, Joshua A.. Stanford University School Of Medicine; Estados UnidosFil: Thapa, Gagan. Legislature Parliament Of Nepal; NepalFil: Twum Danso, Nana A. Y.. Maza; GhanaFil: Pate, Muhammad. Big Win Philanthropy; Reino Unid

Inequalities in health care among patients with type 2 diabetes by individual Socio-Economic Status (SES) and regional deprivation: A systematic literature review.

Introduction Quality of care could be influenced by individual socio-economic status (SES) and by residential area deprivation. The objective is to synthesize the current evidence regarding inequalities in health care for patients with Type 2 diabetes mellitus (Type 2 DM). Methods The systematic review focuses on inequalities concerning process (e.g. measurement of HbA1c, i.e. glycolised haemoglobin) and intermediate outcome indicators (e.g. HbA1c level) of Type 2 diabetes care. In total, of n = 886 publications screened, n = 21 met the inclusion criteria. Results A wide variety of definitions for ‘good quality diabetes care’, regional deprivation and individual SES was observed. Despite differences in research approaches, there is a trend towards worse health care for patients with low SES, concerning both process of care and intermediate outcome indicators. Patients living in deprived areas less often achieve glycaemic control targets, tend to have higher blood pressure (BP) and worse lipid profile control. Conclusion The available evidence clearly points to the fact that socio-economic inequalities in diabetes care do exist. Low individual SES and residential area deprivation are often associated with worse process indicators and worse intermediate outcomes, resulting in higher risks of microvascular and macrovascular complications. These inequalities exist across different health care systems. Recommendations for further research are provided. &nbsp

Modernisation of Endoscopic Equipment Using 3D Indicators

The development of new software to improve the operation of modernised and developed technological facilities in different sectors of the national economy requires a systematic approach. For example, the use of video recording systems obtained during operations with the use of endoscopic equipment allows monitoring the work of doctors. Minor change of the used software allows using additionally processed video fragments for creation of training complexes. The authors of the present article took part in the development of many educational software and hardware systems. The first such system was the “Contact” system, developed in the eighties of the last century at Riga Polytechnic Institute. Later on, car simulators, air plan simulators, walking excavator simulators and the optical software-hardware training system “Three-Dimensional Medical Atlas” were developed. Analysis of various simulators and training systems showed that the computers used in them could not by themselves be a learning system. When creating a learning system, many factors must be considered so that the student does not receive false skills. The goal of the study is to analyse the training systems created for the professional training of medical personnel working with endoscopic equipment, in particular, with equipment equipped with 3D indicators