Improvement Research Carried Out Through Networked Communities: Accelerating Learning about Practices that Support More Productive Student Mindsets

The research on academic mindsets shows significant promise for addressing important problems facing educators. However, the history of educational reform is replete with good ideas for improvement that fail to realize the promises that accompany their introduction. As a field, we are quick to implement new ideas but slow to learn how to execute well on them. If we continue to implement reform as we always have, we will continue to get what we have always gotten. Accelerating the field's capacity to learn in and through practice to improve is one key to transforming the good ideas discussed at the White House meeting into tools, interventions, and professional development initiatives that achieve effectiveness reliably at scale. Toward this end, this paper discusses the function of networked communities engaged in improvement research and illustrates the application of these ideas in promoting greater student success in community colleges. Specifically, this white paper:* Introduces improvement research and networked communities as ideas that we believe can enhance educators' capacities to advance positive change. * Explains why improvement research requires a different kind of measures -- what we call practical measurement -- that are distinct from those commonly used by schools for accountability or by researchers for theory development.* Illustrates through a case study how systematic improvement work to promote student mindsets can be carried out. The case is based on the Carnegie Foundation's effort to address the poor success rates for students in developmental math at community colleges.Specifically, this case details:- How a practical theory and set of practical measures were created to assess the causes of "productive persistence" -- the set of "non-cognitive factors" thought to powerfully affect community college student success. In doing this work, a broad set of potential factors was distilled into a digestible framework that was useful topractitioners working with researchers, and a large set of potential measures was reduced to a practical (3-minute) set of assessments.- How these measures were used by researchers and practitioners for practical purposes -- specifically, to assess changes, predict which students were at-risk for course failure, and set priorities for improvement work.-How we organized researchersto work with practitioners to accelerate field-based experimentation on everyday practices that promote academic mindsets(what we call alpha labs), and how we organized practitioners to work with researchers to test, revise, refine, and iteratively improve their everyday practices (using plando-study-act cycles).While significant progress has already occurred, robust, practical, reliable efforts to improve students' mindsets remains at an early formative stage. We hope the ideas presented here are an instructive starting point for new efforts that might attempt to address other problems facing educators, most notably issues of inequality and underperformance in K-12 settings

Briefing to the incoming Minister of Health 2014

Executive summary This briefing provides you, as the incoming Minister, with information on challenges and opportunities facing the New Zealand health and disability system, and how the Ministry can advise and support you to implement your Government’s priorities for health. The Ministry looks forward to discussing with you how to progress your health policies, including: providing high-quality health services; healthy communities; a strong and engaged health workforce; quality aged care and mental health services. The New Zealand health and disability sector provides world-class services, is driven by a trusted, passionate and skilled workforce, across a spectrum of public, NGOs and private providers, and serves a population that can generally access the care it needs, when it needs it. There are, however, many pressures and environmental changes that require both immediate management and longer-term strategic change. As Minister, you have a number of levers at your disposal to guide system change through setting policy direction, legislation and regulations, funding models and performance management, as well as influencing culture and leadership. Every New Zealander will, at some point in their lives, rely on our health and disability system. It is a large and complex system with multiple decision-makers and mixed public and private ownership models. It operates in a dynamic, continually changing environment characterised by well-known global and local challenges, including:   changing population health needs and burden of disease (especially the rising impact of long- term conditions and risk factors, such as diabetes and obesity)   the growing impact of health-care associated infections, antimicrobial resistance and emerging infectious diseases, eg, Ebola   rapid advances in technology, developments in personalised medicine and changing public expectations   an ageing population, and a workforce that is ageing along with the population   a constrained funding environment for the foreseeable future   a growing fiscal sustainability challenge as health consumes an increasing proportion of total government expenditure. These challenges are placing pressure and new demands on the way public health and disability services are currently delivered. Significant gains in the overall health of New Zealanders could be achieved by concentrating on people who have poorer health outcomes, complex health needs or who need a stronger voice. These might include vulnerable children, older people, people with long-term conditions, people with mental health and addiction problems and people with disabilities. Health and disability services need to build on current progress and adapt to future needs. The health system’s ability to provide a sustainable, quality public health service depends on keeping ahead of the challenges. This briefing provides some suggestions for where we could work with you to meet these challenges. There are opportunities to make better use of existing resources, people, facilities and funding, through new ways of delivering services that keep people well with better prevention and early Briefing to the Incoming Minister of Health v intervention. Significant gains could be made by developing a longer-term focus on preventing disability and illness in the first place. There are new opportunities for the health workforce to work in different ways with a broader range of colleagues across the health and wider social sectors, and with partners in the community. To better equip the New Zealand health and disability system for the future, we suggest focusing on four areas. 1  Better integrate services within health and across the social sector: Strengthening integration within health and across government to support the most vulnerable, reduce inequities and address issues outside the health and disability system that impact on health. 2  Improve the way services are purchased and provided: Ensuring funding models support change, building and supporting the key enablers and drivers of change: workforce, health information and capital. 3  Lift quality and performance: Driving performance through measuring and rewarding the right things to improve quality. 4  Support leadership and capability for change: Supporting strong governance, clinical and executive leadership and capability across the health sector.&nbsp

The Global academic research organization network: Data sharing to cure diseases and enable learning health systems.

Introduction:Global data sharing is essential. This is the premise of the Academic Research Organization (ARO) Council, which was initiated in Japan in 2013 and has since been expanding throughout Asia and into Europe and the United States. The volume of data is growing exponentially, providing not only challenges but also the clear opportunity to understand and treat diseases in ways not previously considered. Harnessing the knowledge within the data in a successful way can provide researchers and clinicians with new ideas for therapies while avoiding repeats of failed experiments. This knowledge transfer from research into clinical care is at the heart of a learning health system. Methods:The ARO Council wishes to form a worldwide complementary system for the benefit of all patients and investigators, catalyzing more efficient and innovative medical research processes. Thus, they have organized Global ARO Network Workshops to bring interested parties together, focusing on the aspects necessary to make such a global effort successful. One such workshop was held in Austin, Texas, in November 2017. Representatives from Japan, Taiwan, Singapore, Europe, and the United States reported on their efforts to encourage data sharing and to use research to inform care through learning health systems. Results:This experience report summarizes presentations and discussions at the Global ARO Network Workshop held in November 2017 in Austin, TX, with representatives from Japan, Korea, Singapore, Taiwan, Europe, and the United States. Themes and recommendations to progress their efforts are explored. Standardization and harmonization are at the heart of these discussions to enable data sharing. In addition, the transformation of clinical research processes through disruptive innovation, while ensuring integrity and ethics, will be key to achieving the ARO Council goal to overcome diseases such that people not only live longer but also are healthier and happier as they age. Conclusions:The achievement of global learning health systems will require further exploration, consensus-building, funding aligned with incentives for data sharing, standardization, harmonization, and actions that support global interests for the benefit of patients

Tennessee Diabetes Action Report, February 2017

https://digitalcommons.memphis.edu/govpubs-tn-dept-health-diabetes-action-report/1002/thumbnail.jp

Clinical Practice Implementation to Address ASCVD Risk: A Practice Change in Primary Care

Practice Problem: Heart disease stands as the leading cause of mortality in the United States. While healthcare providers strive to identify and optimize prevention strategies, particularly in high-risk patient populations, notable gaps in care persist, notably in the management of modifiable risk factors such as low-density lipoprotein cholesterol (LDL). By harnessing the power of artificial intelligence (AI) integrated software within clinical settings, we can revolutionize the landscape of this devastating chronic disease. PICOT: The PICOT question that guided this project was: In Primary Care Advanced Practice Providers (APP) caring for high-risk and/or very high-risk patients with atherosclerotic cardiovascular disease (ASCVD) (P), how do automated electronic alerts with guideline-based recommendations (I) compare to standard notification practice (C) affect referral initiation to cardiology or prompt medication change (O) within 10 weeks (T)? Evidence: In the realm of modern healthcare, it is crucial to recognize the impact of AI on Electronic Health Records (EHRs). This fusion of data analysis and health information technology provides an opportunity for healthcare treatments to become much more effective, resulting in better patient outcomes. Fifteen studies that matched the inclusion criteria were collected and used as substantiating evidence for this project. Intervention: AI software integrated into the EHR system computed comprehensive data analytics, consequently discovering a substantial cohort of patients with an elevated risk profile for ASCVD, accompanied by an LDL-C level that exceeded established clinical guidelines. Subsequently, an automated communication was sent to the APP, furnishing them with pertinent notifications and offering referral recommendations. Outcome: By integrating AI processes into the EHR, data management is streamlined and real-time disease prevention analysis is achieved. The primary goal was to identify high-risk ASCVD patient groups using AI within the EHR and assess the effectiveness of AI-generated electronic alerts with clinical guidance in encouraging behavior change. The clinical significance of this data collection and implementation was substantial. While the statistical analysis produced relevant metrics, it also exhibited applicability in the clinical context. The data exposed a patient population lacking aggressive medical management or referrals, a concern noted by APPs. Conclusion: Introducing AI-based tools can direct the pathway of care and bridge crucial gaps in care in high-risk populations. The result of this technology utilization and integration offers timely screening strategies, education, clinical decision support, and opportunities to address vital pathways for providers and health systems to address ASCVD treatment gaps

Portuguese hospitals’ main challenges in implementing Big Data projects for early detection of adverse events

Big Data has been creating much excitement and promises to solve many of the current health systems’ challenges. A specific application allows predicting adverse events, such as nosocomial infections, 24-48 hours earlier than traditional methods, by analysing in real-time physiological data allied with clinical information, and by extracting knowledge from this stored data. However, the implementation of this kind of projects is not without challenges. Hence, the objective of this thesis is to understand the main barriers in implementing Big Data projects for early detection of adverse events in the specific case of Portuguese hospitals. The collection of primary data, through surveys and interviews, allowed identifying three main barriers. Firstly, there is a generalized low knowledge regarding Big Data, which can hinder the consideration of these projects in the yearly budget and create difficulties in understanding how it can be applied and benefit the hospital. Secondly, a shortage of “Data Scientists” in Portuguese hospitals was reported, being this skilled labour crucial to creatively look at the data and understand how it generates value. Finally, an initial high investment with still undiscovered business value is a true barrier, reflecting the hospitals’ budget constraints. However, two initially identified obstacles were not validated by this analysis. Firstly, being an organizational change necessary to adapt to this new paradigm, resistance from managers and caregivers is not expected. Furthermore, data security and privacy were not considered true impediments but rather a requirement of the technology.“Big Data” tem vindo a despertar muita atenção e promete resolver os principais desafios que os sistemas de saúde hoje enfrentam. Uma aplicação específica permite prever intercorrências, como infeções adquiridas no hospital, 24-48 horas mais cedo do que os métodos tradicionais, através de uma análise em tempo real de fluxos fisiológicos e informação complementar, tal como da extração de novos algoritmos integrados nos dados armazenados. Contudo, a implementação destes projectos tem associada desafios e dificuldades. Assim, o objetivo desta tese é compreender quais as principais barreiras à implementação de projectos de “Big Data” para deteção precoce de intercorrências, no caso específico dos hospitais portugueses. Dados recolhidos através de inquéritos e entrevistas, permitiram identificar três barreiras principais. Primeiramente, o nível de conhecimento sobre “Big Data” é baixo, o que poderá impedir a inclusão deste tipo de projetos no orçamento e dificultar o entendimento relativamente à sua aplicação no meio hospitalar. Seguidamente, foi reportada uma carência generalizada de “Data Scientists”, sendo estes cruciais para olhar de forma criativa para os dados, compreendendo como podem gerar valor. Finalmente, a necessidade de existir um elevado investimento inicial, associada à falta de evidência relativamente aos benefícios, foi considerada uma barreira, refletida nas restrições orçamentais dos hospitais. Contudo, dois obstáculos inicialmente identificados, não foram validados pela análise. Primeiro, sendo necessária uma transformação organizacional, não é esperada resistência por parte dos gestores ou médicos e enfermeiros. Por outro lado, segurança e privacidade dos dados não foram consideradas uma barreira, mas algo que a tecnologia teria que garantir

Process improvement approaches for increasing the response of emergency departments against the Covid-19 pandemic: a systematic review

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions