Showing papers on "Health care published in 2019"

Dissecting racial bias in an algorithm used to manage the health of populations

Abstract: Health systems rely on commercial prediction algorithms to identify and help patients with complex health needs. We show that a widely used algorithm, typical of this industry-wide approach and affecting millions of patients, exhibits significant racial bias: At a given risk score, Black patients are considerably sicker than White patients, as evidenced by signs of uncontrolled illnesses. Remedying this disparity would increase the percentage of Black patients receiving additional help from 17.7 to 46.5%. The bias arises because the algorithm predicts health care costs rather than illness, but unequal access to care means that we spend less money caring for Black patients than for White patients. Thus, despite health care cost appearing to be an effective proxy for health by some measures of predictive accuracy, large racial biases arise. We suggest that the choice of convenient, seemingly effective proxies for ground truth can be an important source of algorithmic bias in many contexts.

Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis

Abstract: Summary Background Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). Methods We estimated the incidence of infections with 16 antibiotic resistance–bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011–12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. Findings From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148–763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480–38 430) attributable deaths and 874 541 (768 837–989 068) DALYs. The burden for the EU and EEA was highest in infants (aged Interpretation Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases. Funding European Centre for Disease Prevention and Control.

The Danish health care system and epidemiological research: from health care contacts to database records

Abstract: Denmark has a large network of population-based medical databases, which routinely collect high-quality data as a by-product of health care provision. The Danish medical databases include administrative, health, and clinical quality databases. Understanding the full research potential of these data sources requires insight into the underlying health care system. This review describes key elements of the Danish health care system from planning and delivery to record generation. First, it presents the history of the health care system, its overall organization and financing. Second, it details delivery of primary, hospital, psychiatric, and elderly care. Third, the path from a health care contact to a database record is followed. Finally, an overview of the available data sources is presented. This review discusses the data quality of each type of medical database and describes the relative technical ease and cost-effectiveness of exact individual-level linkage among them. It is shown, from an epidemiological point of view, how Denmark's population represents an open dynamic cohort with complete long-term follow-up, censored only at emigration or death. It is concluded that Denmark's constellation of universal health care, long-standing routine registration of most health and life events, and the possibility of exact individual-level data linkage provides unlimited possibilities for epidemiological research.

Nutrition Therapy for Adults With Diabetes or Prediabetes: A Consensus Report.

Abstract: This Consensus Report is intended to provide clinical professionals with evidence-based guidance about individualizing nutrition therapy for adults with diabetes or prediabetes. Strong evidence supports the efficacy and cost-effectiveness of nutrition therapy as a component of quality diabetes care, including its integration into the medical management of diabetes; therefore, it is important that all members of the health care team know and champion the benefits of nutrition therapy and key nutrition messages. Nutrition counseling that works toward improving or maintaining glycemic targets, achieving weight management goals, and improving cardiovascular risk factors (e.g., blood pressure, lipids, etc.) within individualized treatment goals is recommended for all adults with diabetes and prediabetes. Though it might simplify messaging, a “one-size-fits-all” eating plan is not evident for the prevention or management of diabetes, and it is an unrealistic expectation given the broad spectrum of people affected by diabetes and prediabetes, their cultural backgrounds, personal preferences, co-occurring conditions (often referred to as comorbidities), and socioeconomic settings in which they live. Research provides clarity on many food choices and eating patterns that can help people achieve health goals and quality of life. The American Diabetes Association (ADA) emphasizes that medical nutrition therapy (MNT) is fundamental in the overall diabetes management plan, and the need for MNT should be reassessed frequently by health care providers in collaboration with people with diabetes across the life span, with special attention during times of changing health status and life stages (1–3). This Consensus Report now includes information on prediabetes, and previous ADA nutrition position statements, the last of which was published in 2014 (4), did not. Unless otherwise noted, the research reviewed was limited to those studies conducted in adults diagnosed with prediabetes, type 1 diabetes, and/or type 2 diabetes. Nutrition therapy for children with diabetes or women …

Taiwan's National Health Insurance Research Database: past and future.

Abstract: Taiwan's National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan's Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.

Epidemiology of cardiovascular disease in China: current features and implications.

Abstract: Cardiovascular disease (CVD) is the leading cause of death in China. To develop effective and timely strategies to cope with the challenges of CVD epidemics, we need to understand the current epidemiological features of the major types of CVD and the implications of these features for the prevention and treatment of CVD. In this Review, we summarize eight important features of the epidemiology of CVD in China. Some features indicate a transition in CVD epidemiology owing to interrelated changes in demography, environment, lifestyle, and health care, including the rising burden from atherosclerotic CVD (ischaemic heart disease and ischaemic stroke), declining mortality from haemorrhage stroke, varied regional epidemiological trends in the subtypes of CVD, increasing numbers of patients with moderate types of ischaemic heart disease and ischaemic stroke, and increasing ageing of patients with CVD. Other features highlight the problems that need particular attention, including the high proportion of out-of-hospital death of patients with ischaemic heart disease with insufficient prehospital care; the wide gaps between guideline-recommended goals and levels of lifestyle indicators; and the huge number of patients with undiagnosed, untreated, or uncontrolled hypertension, hypercholesterolaemia, or diabetes mellitus.

Prevalence and Trends of Developmental Disabilities among Children in the United States: 2009-2017.

Abstract: OBJECTIVES: To study the national prevalence of 10 developmental disabilities in US children aged 3 to 17 years and explore changes over time by associated demographic and socioeconomic characteristics, using the National Health Interview Survey. METHODS: Data come from the 2009 to 2017 National Health Interview Survey, a nationally representative survey of the civilian noninstitutionalized population. Parents reported physician or other health care professional diagnoses of attention-deficit/hyperactivity disorder; autism spectrum disorder; blindness; cerebral palsy; moderate to profound hearing loss; learning disability; intellectual disability; seizures; stuttering or stammering; and other developmental delays. Weighted percentages for each of the selected developmental disabilities and any developmental disability were calculated and stratified by demographic and socioeconomic characteristics. RESULTS: From 2009 to 2011 and 2015 to 2017, there were overall significant increases in the prevalence of any developmental disability (16.2%–17.8%, P CONCLUSIONS: The prevalence of developmental disability among US children aged 3 to 17 years increased between 2009 and 2017. Changes by demographic and socioeconomic subgroups may be related to improvements in awareness and access to health care.

Big data and machine learning algorithms for health-care delivery

Abstract: Analysis of big data by machine learning offers considerable advantages for assimilation and evaluation of large amounts of complex health-care data. However, to effectively use machine learning tools in health care, several limitations must be addressed and key issues considered, such as its clinical implementation and ethics in health-care delivery. Advantages of machine learning include flexibility and scalability compared with traditional biostatistical methods, which makes it deployable for many tasks, such as risk stratification, diagnosis and classification, and survival predictions. Another advantage of machine learning algorithms is the ability to analyse diverse data types (eg, demographic data, laboratory findings, imaging data, and doctors' free-text notes) and incorporate them into predictions for disease risk, diagnosis, prognosis, and appropriate treatments. Despite these advantages, the application of machine learning in health-care delivery also presents unique challenges that require data pre-processing, model training, and refinement of the system with respect to the actual clinical problem. Also crucial are ethical considerations, which include medico-legal implications, doctors' understanding of machine learning tools, and data privacy and security. In this Review, we discuss some of the benefits and challenges of big data and machine learning in health care.

Human Wounds and Its Burden: An Updated Compendium of Estimates.

Abstract: Significance: A 2018 retrospective analysis of Medicare beneficiaries identified that ∼8.2 million people had wounds with or without infections. Medicare cost estimates for acute and chronic wound treatments ranged from $28.1 billion to $96.8 billion. Highest expenses were for surgical wounds followed by diabetic foot ulcers, with a higher trend toward costs associated with outpatient wound care compared with inpatient. Increasing costs of health care, an aging population, recognition of difficult-to-treat infection threats such as biofilms, and the continued threat of diabetes and obesity worldwide make chronic wounds a substantial clinical, social, and economic challenge. Recent Advances: Chronic wounds are not a problem in an otherwise healthy population. Underlying conditions ranging from malnutrition, to stress, to metabolic syndrome, predispose patients to chronic, nonhealing wounds. From an economic point of view, the annual wound care products market is expected to reach $15-22 billion by 2024. The National Institutes of Health's (NIH) Research Portfolio Online Reporting Tool (RePORT) now lists wounds as a category. Future Directions: A continued rise in the economic, clinical, and social impact of wounds warrants a more structured approach and proportionate investment in wound care, education, and related research.

Multitask learning and benchmarking with clinical time series data.

Abstract: Health care is one of the most exciting frontiers in data mining and machine learning. Successful adoption of electronic health records (EHRs) created an explosion in digital clinical data available for analysis, but progress in machine learning for healthcare research has been difficult to measure because of the absence of publicly available benchmark data sets. To address this problem, we propose four clinical prediction benchmarks using data derived from the publicly available Medical Information Mart for Intensive Care (MIMIC-III) database. These tasks cover a range of clinical problems including modeling risk of mortality, forecasting length of stay, detecting physiologic decline, and phenotype classification. We propose strong linear and neural baselines for all four tasks and evaluate the effect of deep supervision, multitask training and data-specific architectural modifications on the performance of neural models.

Waste in the US Health Care System: Estimated Costs and Potential for Savings.

Abstract: Importance The United States spends more on health care than any other country, with costs approaching 18% of the gross domestic product (GDP). Prior studies estimated that approximately 30% of health care spending may be considered waste. Despite efforts to reduce overtreatment, improve care, and address overpayment, it is likely that substantial waste in US health care spending remains. Objectives To estimate current levels of waste in the US health care system in 6 previously developed domains and to report estimates of potential savings for each domain. Evidence A search of peer-reviewed and “gray” literature from January 2012 to May 2019 focused on the 6 waste domains previously identified by the Institute of Medicine and Berwick and Hackbarth: failure of care delivery, failure of care coordination, overtreatment or low-value care, pricing failure, fraud and abuse, and administrative complexity. For each domain, available estimates of waste-related costs and data from interventions shown to reduce waste-related costs were recorded, converted to annual estimates in 2019 dollars for national populations when necessary, and combined into ranges or summed as appropriate. Findings The review yielded 71 estimates from 54 unique peer-reviewed publications, government-based reports, and reports from the gray literature. Computations yielded the following estimated ranges of total annual cost of waste: failure of care delivery, $102.4 billion to $165.7 billion; failure of care coordination, $27.2 billion to $78.2 billion; overtreatment or low-value care, $75.7 billion to $101.2 billion; pricing failure, $230.7 billion to $240.5 billion; fraud and abuse, $58.5 billion to $83.9 billion; and administrative complexity, $265.6 billion. The estimated annual savings from measures to eliminate waste were as follows: failure of care delivery, $44.4 billion to $93.3 billion; failure of care coordination, $29.6 billion to $38.2 billion; overtreatment or low-value care, $12.8 billion to $28.6 billion; pricing failure, $81.4 billion to $91.2 billion; and fraud and abuse, $22.8 billion to $30.8 billion. No studies were identified that focused on interventions targeting administrative complexity. The estimated total annual costs of waste were $760 billion to $935 billion and savings from interventions that address waste were $191 billion to $282 billion. Conclusions and Relevance In this review based on 6 previously identified domains of health care waste, the estimated cost of waste in the US health care system ranged from $760 billion to $935 billion, accounting for approximately 25% of total health care spending, and the projected potential savings from interventions that reduce waste, excluding savings from administrative complexity, ranged from $191 billion to $282 billion, representing a potential 25% reduction in the total cost of waste. Implementation of effective measures to eliminate waste represents an opportunity reduce the continued increases in US health care expenditures.

Estimating the Attributable Cost of Physician Burnout in the United States

Abstract: This study examined the economic cost of physician burnout by using published research findings and industry reports. The authors estimate that burnout costs a practice an average of $7600 in reduc...

Do no harm: a roadmap for responsible machine learning for health care.

Abstract: Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-based interventions in health care. To be successful, translation will require a team of engaged stakeholders and a systematic process from beginning (problem formulation) to end (widespread deployment).

Vital Signs: Epidemiology and Recent Trends in Methicillin-Resistant and in Methicillin-Susceptible Staphylococcus aureus Bloodstream Infections — United States

Abstract: Introduction Staphylococcus aureus is one of the most common pathogens in health care facilities and in the community, and can cause invasive infections, sepsis, and death. Despite progress in preventing methicillin-resistant S. aureus (MRSA) infections in health care settings, assessment of the problem in both health care and community settings is needed. Further, the epidemiology of methicillin-susceptible S. aureus (MSSA) infections is not well described at the national level.

The development of software to support multiple systematic review types: the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information (JBI SUMARI).

Abstract: Aim:Systematic reviews play an important role in ensuring trustworthy recommendations in healthcare. However, systematic reviews can be laborious to undertake and as such software has been developed to assist in the conduct and reporting of systematic reviews. The Joanna Briggs Institute and

Why cultural safety rather than cultural competency is required to achieve health equity: a literature review and recommended definition

Abstract: Eliminating indigenous and ethnic health inequities requires addressing the determinants of health inequities which includes institutionalised racism, and ensuring a health care system that delivers appropriate and equitable care. There is growing recognition of the importance of cultural competency and cultural safety at both individual health practitioner and organisational levels to achieve equitable health care. Some jurisdictions have included cultural competency in health professional licensing legislation, health professional accreditation standards, and pre-service and in-service training programmes. However, there are mixed definitions and understandings of cultural competency and cultural safety, and how best to achieve them. A literature review of 59 international articles on the definitions of cultural competency and cultural safety was undertaken. Findings were contextualised to the cultural competency legislation, statements and initiatives present within Aotearoa New Zealand, a national Symposium on Cultural Competence and Māori Health, convened by the Medical Council of New Zealand and Te Ohu Rata o Aotearoa – Māori Medical Practitioners Association (Te ORA) and consultation with Māori medical practitioners via Te ORA. Health practitioners, healthcare organisations and health systems need to be engaged in working towards cultural safety and critical consciousness. To do this, they must be prepared to critique the ‘taken for granted’ power structures and be prepared to challenge their own culture and cultural systems rather than prioritise becoming ‘competent’ in the cultures of others. The objective of cultural safety activities also needs to be clearly linked to achieving health equity. Healthcare organisations and authorities need to be held accountable for providing culturally safe care, as defined by patients and their communities, and as measured through progress towards achieving health equity. A move to cultural safety rather than cultural competency is recommended. We propose a definition for cultural safety that we believe to be more fit for purpose in achieving health equity, and clarify the essential principles and practical steps to operationalise this approach in healthcare organisations and workforce development. The unintended consequences of a narrow or limited understanding of cultural competency are discussed, along with recommendations for how a broader conceptualisation of these terms is important.

Global mortality associated with seasonal influenza epidemics: New burden estimates and predictors from the GLaMOR Project.

Abstract: Background Until recently, the World Health Organization (WHO) estimated the annual mortality burden of influenza to be 250 000 to 500 000 all-cause deaths globally; however, a 2017 study indicated a substantially higher mortality burden, at 290 000-650 000 influenza-associated deaths from respiratory causes alone, and a 2019 study estimated 99 000-200 000 deaths from lower respiratory tract infections directly caused by influenza. Here we revisit global and regional estimates of influenza mortality burden and explore mortality trends over time and geography. Methods We compiled influenza-associated excess respiratory mortality estimates for 31 countries representing 5 WHO regions during 2002-2011. From these we extrapolated the influenza burden for all 193 countries of the world using a multiple imputation approach. We then used mixed linear regression models to identify factors associated with high seasonal influenza mortality burden, including influenza types and subtypes, health care and socio-demographic development indicators, and baseline mortality levels. Results We estimated an average of 389 000 (uncertainty range 294 000-518 000) respiratory deaths were associated with influenza globally each year during the study period, corresponding to ~ 2% of all annual respiratory deaths. Of these, 67% were among people 65 years and older. Global burden estimates were robust to the choice of countries included in the extrapolation model. For people Conclusions Our global estimate of influenza-associated excess respiratory mortality is consistent with the 2017 estimate, despite a different modelling strategy, and the lower 2019 estimate which only captured deaths directly caused by influenza. Our finding that baseline respiratory mortality and access to health care are associated with influenza-related mortality in persons

Adherence in Hypertension

Abstract: The global epidemic of hypertension is largely uncontrolled and hypertension remains the leading cause of noncommunicable disease deaths worldwide. Suboptimal adherence, which includes failure to initiate pharmacotherapy, to take medications as often as prescribed, and to persist on therapy long-term, is a well-recognized factor contributing to the poor control of blood pressure in hypertension. Several categories of factors including demographic, socioeconomic, concomitant medical-behavioral conditions, therapy-related, healthcare team and system-related factors, and patient factors are associated with nonadherence. Understanding the categories of factors contributing to nonadherence is useful in managing nonadherence. In patients at high risk for major adverse cardiovascular outcomes, electronic and biochemical monitoring are useful for detecting nonadherence and for improving adherence. Increasing the availability and affordability of these more precise measures of adherence represent a future opportunity to realize more of the proven benefits of evidence-based medications. In the absence of new antihypertensive drugs, it is important that healthcare providers focus their attention on how to do better with the drugs they have. This is the reason why recent guidelines have emphasize the important need to address drug adherence as a major issue in hypertension management.

Diversity improves performance and outcomes.

Abstract: Background Research on the effects of increasing workplace diversity has grown substantially. Unfortunately, little is focused on the healthcare industry, leaving organizations to make decisions based on conflicting findings regarding the association of diversity with quality and financial outcomes. To help improve the evidence-based research, this umbrella review summarizes diversity research specific to healthcare. We also look at studies focused on professional skills relevant to healthcare. The goal is to assess the association between diversity, innovation, patient health outcomes, and financial performance. Methods Medical and business research indices were searched for diversity studies published since 1999. Only meta-analyses and large-scale studies relating diversity to a financial or quality outcome were included. The research also had to include the healthcare industry or involve a related skill, such as innovation, communication and risk assessment. Results Most of the sixteen reviews matching inclusion criteria demonstrated positive associations between diversity, quality and financial performance. Healthcare studies showed patients generally fare better when care was provided by more diverse teams. Professional skills-focused studies generally find improvements to innovation, team communications and improved risk assessment. Financial performance also improved with increased diversity. A diversity-friendly environment was often identified as a key to avoiding frictions that come with change. Conclusions Diversity can help organizations improve both patient care quality and financial results. Return on investments in diversity can be maximized when guided deliberately by existing evidence. Future studies set in the healthcare industry, will help leaders better estimate diversity-related benefits in the context of improved health outcomes, productivity and revenue streams, as well as the most efficient paths to achieve these goals.

Federated Learning for Healthcare Informatics

Abstract: With the rapid development of computer software and hardware technologies, more and more healthcare data are becoming readily available from clinical institutions, patients, insurance companies and pharmaceutical industries, among others. This access provides an unprecedented opportunity for data science technologies to derive data-driven insights and improve the quality of care delivery. Healthcare data, however, are usually fragmented and private making it difficult to generate robust results across populations. For example, different hospitals own the electronic health records (EHR) of different patient populations and these records are difficult to share across hospitals because of their sensitive nature. This creates a big barrier for developing effective analytical approaches that are generalizable, which need diverse, "big data". Federated learning, a mechanism of training a shared global model with a central server while keeping all the sensitive data in local institutions where the data belong, provides great promise to connect the fragmented healthcare data sources with privacy-preservation. The goal of this survey is to provide a review for federated learning technologies, particularly within the biomedical space. In particular, we summarize the general solutions to the statistical challenges, system challenges and privacy issues in federated learning, and point out the implications and potentials in healthcare.

Smart healthcare: making medical care more intelligent

Abstract: With the development of information technology, the concept of smart healthcare has gradually come to the fore. Smart healthcare uses a new generation of information technologies, such as the internet of things (loT), big data, cloud computing, and artificial intelligence, to transform the traditional medical system in an all-round way, making healthcare more efficient, more convenient, and more personalized. With the aim of introducing the concept of smart healthcare, in this review, we first list the key technologies that support smart healthcare and introduce the current status of smart healthcare in several important fields. Then we expound the existing problems with smart healthcare and try to propose solutions to them. Finally, we look ahead and evaluate the future prospects of smart healthcare.

Enhancing the Impact of Implementation Strategies in Healthcare: A Research Agenda.

Abstract: The field of implementation science was developed to better understand the factors that facilitate or impede implementation and generate evidence for implementation strategies. In this article, we briefly review progress in implementation science, and suggest five priorities for enhancing the impact of implementation strategies. Specifically, we suggest the need to: (1) enhance methods for designing and tailoring implementation strategies; (2) specify and test mechanisms of change; (3) conduct more effectiveness research on discrete, multi-faceted, and tailored implementation strategies; (4) increase economic evaluations of implementation strategies; and (5) improve the tracking and reporting of implementation strategies. We believe that pursuing these priorities will advance implementation science by helping us to understand when, where, why, and how implementation strategies improve implementation effectiveness and subsequent health outcomes.

Blockchain Technology in Healthcare: A Comprehensive Review and Directions for Future Research

Abstract: One of the most important discoveries and creative developments that is playing a vital role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far they are. In the last couple of years, the upsurge in blockchain technology has obliged scholars and specialists to scrutinize new ways to apply blockchain technology with a wide range of domains. The dramatic increase in blockchain technology has provided many new application opportunities, including healthcare applications. This survey provides a comprehensive review of emerging blockchain-based healthcare technologies and related applications. In this inquiry, we call attention to the open research matters in this fast-growing field, explaining them in some details. We also show the potential of blockchain technology in revolutionizing healthcare industry.

Applications of artificial neural networks in health care organizational decision-making: A scoping review

Abstract: Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. Applications of ANN to diagnosis are well-known; however, ANN are increasingly used to inform health care management decisions. We provide a seminal review of the applications of ANN to health care organizational decision-making. We screened 3,397 articles from six databases with coverage of Health Administration, Computer Science and Business Administration. We extracted study characteristics, aim, methodology and context (including level of analysis) from 80 articles meeting inclusion criteria. Articles were published from 1997–2018 and originated from 24 countries, with a plurality of papers (26 articles) published by authors from the United States. Types of ANN used included ANN (36 articles), feed-forward networks (25 articles), or hybrid models (23 articles); reported accuracy varied from 50% to 100%. The majority of ANN informed decision-making at the micro level (61 articles), between patients and health care providers. Fewer ANN were deployed for intra-organizational (meso- level, 29 articles) and system, policy or inter-organizational (macro- level, 10 articles) decision-making. Our review identifies key characteristics and drivers for market uptake of ANN for health care organizational decision-making to guide further adoption of this technique.

Mental health and HIV/AIDS: The need for an integrated response

Abstract: Tremendous biomedical advancements in HIV prevention and treatment have led to aspirational efforts to end the HIV epidemic. However, this goal will not be achieved without addressing the significant mental health and substance use problems among people living with HIV (PLWH) and people vulnerable to acquiring HIV. These problems exacerbate the many social and economic barriers to accessing adequate and sustained healthcare, and are among the most challenging barriers to achieving the end of the HIV epidemic. Rates of mental health problems are higher among both people vulnerable to acquiring HIV and PLWH, compared with the general population. Mental health impairments increase risk for HIV acquisition and for negative health outcomes among PLWH at each step in the HIV care continuum. We have the necessary screening tools and efficacious treatments to treat mental health problems among people living with and at risk for HIV. However, we need to prioritize mental health treatment with appropriate resources to address the current mental health screening and treatment gaps. Integration of mental health screening and care into all HIV testing and treatment settings would not only strengthen HIV prevention and care outcomes, but it would additionally improve global access to mental healthcare.