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. 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Multidimensional embedded MEMS motion detectors for wearable mechanocardiography and 4D medical imaging

Background: Cardiovascular diseases are the number one cause of death. Of these deaths, almost 80% are due to coronary artery disease (CAD) and cerebrovascular disease. Multidimensional microelectromechanical systems (MEMS) sensors allow measuring the mechanical movement of the heart muscle offering an entirely new and innovative solution to evaluate cardiac rhythm and function. Recent advances in miniaturized motion sensors present an exciting opportunity to study novel device-driven and functional motion detection systems in the areas of both cardiac monitoring and biomedical imaging, for example, in computed tomography (CT) and positron emission tomography (PET). Methods: This Ph.D. work describes a new cardiac motion detection paradigm and measurement technology based on multimodal measuring tools — by tracking the heart’s kinetic activity using micro-sized MEMS sensors — and novel computational approaches — by deploying signal processing and machine learning techniques—for detecting cardiac pathological disorders. In particular, this study focuses on the capability of joint gyrocardiography (GCG) and seismocardiography (SCG) techniques that constitute the mechanocardiography (MCG) concept representing the mechanical characteristics of the cardiac precordial surface vibrations. Results: Experimental analyses showed that integrating multisource sensory data resulted in precise estimation of heart rate with an accuracy of 99% (healthy, n=29), detection of heart arrhythmia (n=435) with an accuracy of 95-97%, ischemic disease indication with approximately 75% accuracy (n=22), as well as significantly improved quality of four-dimensional (4D) cardiac PET images by eliminating motion related inaccuracies using MEMS dual gating approach. Tissue Doppler imaging (TDI) analysis of GCG (healthy, n=9) showed promising results for measuring the cardiac timing intervals and myocardial deformation changes. Conclusion: The findings of this study demonstrate clinical potential of MEMS motion sensors in cardiology that may facilitate in time diagnosis of cardiac abnormalities. Multidimensional MCG can effectively contribute to detecting atrial fibrillation (AFib), myocardial infarction (MI), and CAD. Additionally, MEMS motion sensing improves the reliability and quality of cardiac PET imaging.Moniulotteisten sulautettujen MEMS-liiketunnistimien käyttö sydänkardiografiassa sekä lääketieteellisessä 4D-kuvantamisessa Tausta: Sydän- ja verisuonitaudit ovat yleisin kuolinsyy. Näistä kuolemantapauksista lähes 80% johtuu sepelvaltimotaudista (CAD) ja aivoverenkierron häiriöistä. Moniulotteiset mikroelektromekaaniset järjestelmät (MEMS) mahdollistavat sydänlihaksen mekaanisen liikkeen mittaamisen, mikä puolestaan tarjoaa täysin uudenlaisen ja innovatiivisen ratkaisun sydämen rytmin ja toiminnan arvioimiseksi. Viimeaikaiset teknologiset edistysaskeleet mahdollistavat uusien pienikokoisten liiketunnistusjärjestelmien käyttämisen sydämen toiminnan tutkimuksessa sekä lääketieteellisen kuvantamisen, kuten esimerkiksi tietokonetomografian (CT) ja positroniemissiotomografian (PET), tarkkuuden parantamisessa. Menetelmät: Tämä väitöskirjatyö esittelee uuden sydämen kineettisen toiminnan mittaustekniikan, joka pohjautuu MEMS-anturien käyttöön. Uudet laskennalliset lähestymistavat, jotka perustuvat signaalinkäsittelyyn ja koneoppimiseen, mahdollistavat sydämen patologisten häiriöiden havaitsemisen MEMS-antureista saatavista signaaleista. Tässä tutkimuksessa keskitytään erityisesti mekanokardiografiaan (MCG), joihin kuuluvat gyrokardiografia (GCG) ja seismokardiografia (SCG). Näiden tekniikoiden avulla voidaan mitata kardiorespiratorisen järjestelmän mekaanisia ominaisuuksia. Tulokset: Kokeelliset analyysit osoittivat, että integroimalla usean sensorin dataa voidaan mitata syketiheyttä 99% (terveillä n=29) tarkkuudella, havaita sydämen rytmihäiriöt (n=435) 95-97%, tarkkuudella, sekä havaita iskeeminen sairaus noin 75% tarkkuudella (n=22). Lisäksi MEMS-kaksoistahdistuksen avulla voidaan parantaa sydämen 4D PET-kuvan laatua, kun liikeepätarkkuudet voidaan eliminoida paremmin. Doppler-kuvantamisessa (TDI, Tissue Doppler Imaging) GCG-analyysi (terveillä, n=9) osoitti lupaavia tuloksia sydänsykkeen ajoituksen ja intervallien sekä sydänlihasmuutosten mittaamisessa. Päätelmä: Tämän tutkimuksen tulokset osoittavat, että kardiologisilla MEMS-liikeantureilla on kliinistä potentiaalia sydämen toiminnallisten poikkeavuuksien diagnostisoinnissa. Moniuloitteinen MCG voi edistää eteisvärinän (AFib), sydäninfarktin (MI) ja CAD:n havaitsemista. Lisäksi MEMS-liiketunnistus parantaa sydämen PET-kuvantamisen luotettavuutta ja laatua

The Application of Computer Techniques to ECG Interpretation

This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Dysrhythmia Monitoring Practices of Nurses on a Telemetry Unit

Standards of practice for hospital electrocardiogram monitoring were recommended in 2004 by the American Heart Association; however they are not widely followed. Many nurses monitor in a single lead regardless of diagnosis and are unable to differentiate wide QRS complex tachycardias. The purpose of this project was to evaluate the effectiveness of an interactive web-based education program combined with unit-based collaborative learning activities on both telemetry staff nurses‘ knowledge of dysrhythmias and their monitoring practices for patients at risk for wide QRS complex tachycardias. This interventional, one group before-and-after cohort study design consisted of four components: interactive web-based educational program with a pretest and posttest, unit-based collaborative activities, competency skills validation, and patient audits of electrode placement and lead selection at baseline, six weeks, and 18 weeks. There were 34 nurses who consented to participate, 16 started the program, and nine finished all the components. The pretest scores ranged from 0 – 60% with median of 36.5%. The posttest scores ranged from 47 – 93% with median of 80%. The Wilcoxon Signed Ranks test showed a significant difference between the pretest and posttest scores (p = .008). The patient audit results did not indicate significant differences in proportions of correct electrode placement and correct lead selection between baseline, 6 weeks, and 18 weeks. The program was effective in increasing nurses‘ knowledge about dysrhythmias; however, it was not effective in changing monitoring behavior. More research is needed to see if this type of program is more effective if it involves all the staff on the unit who are responsible for monitoring, and if additional strategies are used, such as unit champions and group rewards

Neonatal Health Care

This issue of Children concerns healthcare delivery and research in neonatology. Several articles concern the work of the California Perinatal Quality Care Collaborative, including a history by founder Dr. Jeffrey Gould, and recent quality improvement work. Other articles concern methodological issues in neonatal research and findings of recent clinical studies

Evidence-based Education: The development of a model to use protocols and small-scale aggregated trials to create a prospective cumulative meta-analysis as an evidence base for interventions.

In education, there has been a worldwide increase in the use of evidence in education to inform policy and practice. In the USA, bodies such as the Institute of Educational Sciences’ (IES) What Works Clearinghouse (WWC), the Best Evidence Encyclopaedia (BEE) and the Department General Administrative Regulations (EDGAR) and in the UK the Education Endowment Foundation (EEF) have been established to inform education decision making. The global increase in the use of evidence in education is based on the premise that if programmes are selected on the basis of more robust evidence, using these tested interventions should increase the chance of positive outcomes if they are deployed in other schools and contexts. The aim of this thesis is to explore evidence-based education in the literature review before proposing a new theoretical model for evidence generation, introducing the use of protocols and small-scale aggregated trials linked to a prospective cumulative meta-analysis (PCM). The application of a PCM allows replication as a way to test how likely the intervention effect sizes will translate when they are tested using large scale randomised controlled trials and also as a method to test stability and improve dissemination after the initial research. The thesis includes two primary research studies for online cross-age peer tutoring across the transition boundary between primary and secondary schools and online small group teaching. The purpose of the trials were to test the implementation of the methodology for the use of protocols and small-scale aggregated trials linked to a prospective cumulative meta-analysis (PCM). Study One focuses on online peer tutoring across the transition for primary and secondary pupils and Study Two investigates the effectiveness of online small group teaching for mathematics. The thesis demonstrates how the use of the model can be used to increase replication in the testing phase of an intervention, using empirical evidence from the online peer tutoring trials involving data collected across three cohorts of schools in an academic year. The impact of this research will provide an alternative testing framework for deciding in future trials if the evidence is robust for the commissioning of large scale randomised controlled trials in education