Showing papers on "Health care published in 2017"

What is polypharmacy? A systematic review of definitions

Abstract: Multimorbidity and the associated use of multiple medicines (polypharmacy), is common in the older population. Despite this, there is no consensus definition for polypharmacy. A systematic review was conducted to identify and summarise polypharmacy definitions in existing literature. The reporting of this systematic review conforms to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist. MEDLINE (Ovid), EMBASE and Cochrane were systematically searched, as well as grey literature, to identify articles which defined the term polypharmacy (without any limits on the types of definitions) and were in English, published between 1st January 2000 and 30th May 2016. Definitions were categorised as i. numerical only (using the number of medications to define polypharmacy), ii. numerical with an associated duration of therapy or healthcare setting (such as during hospital stay) or iii. Descriptive (using a brief description to define polypharmacy). A total of 1156 articles were identified and 110 articles met the inclusion criteria. Articles not only defined polypharmacy but associated terms such as minor and major polypharmacy. As a result, a total of 138 definitions of polypharmacy and associated terms were obtained. There were 111 numerical only definitions (80.4% of all definitions), 15 numerical definitions which incorporated a duration of therapy or healthcare setting (10.9%) and 12 descriptive definitions (8.7%). The most commonly reported definition of polypharmacy was the numerical definition of five or more medications daily (n = 51, 46.4% of articles), with definitions ranging from two or more to 11 or more medicines. Only 6.4% of articles classified the distinction between appropriate and inappropriate polypharmacy, using descriptive definitions to make this distinction. Polypharmacy definitions were variable. Numerical definitions of polypharmacy did not account for specific comorbidities present and make it difficult to assess safety and appropriateness of therapy in the clinical setting.

Implicit bias in healthcare professionals: a systematic review

Abstract: Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients. PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies. Forty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals’ attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care. The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics. Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.

Executive Leadership and Physician Well-being: Nine Organizational Strategies to Promote Engagement and Reduce Burnout

Abstract: These are challenging times for health care executives. The health care field is experiencing unprecedented changes that threaten the survival of many health care organizations. To successfully navigate these challenges, health care executives need committed and productive physicians working in collaboration with organization leaders. Unfortunately, national studies suggest that at least 50% of US physicians are experiencing professional burnout, indicating that most executives face this challenge with a disillusioned physician workforce. Burnout is a syndrome characterized by exhaustion, cynicism, and reduced effectiveness. Physician burnout has been shown to influence quality of care, patient safety, physician turnover, and patient satisfaction. Although burnout is a system issue, most institutions operate under the erroneous framework that burnout and professional satisfaction are solely the responsibility of the individual physician. Engagement is the positive antithesis of burnout and is characterized by vigor, dedication, and absorption in work. There is a strong business case for organizations to invest in efforts to reduce physician burnout and promote engagement. Herein, we summarize 9 organizational strategies to promote physician engagement and describe how we have operationalized some of these approaches at Mayo Clinic. Our experience demonstrates that deliberate, sustained, and comprehensive efforts by the organization to reduce burnout and promote engagement can make a difference. Many effective interventions are relatively inexpensive, and small investments can have a large impact. Leadership and sustained attention from the highest level of the organization are the keys to making progress.

The COMET Handbook: Version 1.0

Abstract: The selection of appropriate outcomes is crucial when designing clinical trials in order to compare the effects of different interventions directly. For the findings to influence policy and practice, the outcomes need to be relevant and important to key stakeholders including patients and the public, health care professionals and others making decisions about health care. It is now widely acknowledged that insufficient attention has been paid to the choice of outcomes measured in clinical trials. Researchers are increasingly addressing this issue through the development and use of a core outcome set, an agreed standardised collection of outcomes which should be measured and reported, as a minimum, in all trials for a specific clinical area. Accumulating work in this area has identified the need for guidance on the development, implementation, evaluation and updating of core outcome sets. This Handbook, developed by the COMET Initiative, brings together current thinking and methodological research regarding those issues. We recommend a four-step process to develop a core outcome set. The aim is to update the contents of the Handbook as further research is identified.

Controlled Interventions to Reduce Burnout in Physicians A Systematic Review and Meta-analysis

Abstract: Importance Burnout is prevalent in physicians and can have a negative influence on performance, career continuation, and patient care. Existing evidence does not allow clear recommendations for the management of burnout in physicians. Objective To evaluate the effectiveness of interventions to reduce burnout in physicians and whether different types of interventions (physician-directed or organization-directed interventions), physician characteristics (length of experience), and health care setting characteristics (primary or secondary care) were associated with improved effects. Data Sources MEDLINE, Embase, PsycINFO, CINAHL, and Cochrane Register of Controlled Trials were searched from inception to May 31, 2016. The reference lists of eligible studies and other relevant systematic reviews were hand searched. Study Selection Randomized clinical trials and controlled before-after studies of interventions targeting burnout in physicians. Data Extraction and Synthesis Two independent reviewers extracted data and assessed the risk of bias. The main meta-analysis was followed by a number of prespecified subgroup and sensitivity analyses. All analyses were performed using random-effects models and heterogeneity was quantified. Main Outcomes and Measures The core outcome was burnout scores focused on emotional exhaustion, reported as standardized mean differences and their 95% confidence intervals. Results Twenty independent comparisons from 19 studies were included in the meta-analysis (n = 1550 physicians; mean [SD] age, 40.3 [9.5] years; 49% male). Interventions were associated with small significant reductions in burnout (standardized mean difference [SMD] = −0.29; 95% CI, −0.42 to −0.16; equal to a drop of 3 points on the emotional exhaustion domain of the Maslach Burnout Inventory above change in the controls). Subgroup analyses suggested significantly improved effects for organization-directed interventions (SMD = −0.45; 95% CI, −0.62 to −0.28) compared with physician-directed interventions (SMD = −0.18; 95% CI, −0.32 to −0.03). Interventions delivered in experienced physicians and in primary care were associated with higher effects compared with interventions delivered in inexperienced physicians and in secondary care, but these differences were not significant. The results were not influenced by the risk of bias ratings. Conclusions and Relevance Evidence from this meta-analysis suggests that recent intervention programs for burnout in physicians were associated with small benefits that may be boosted by adoption of organization-directed approaches. This finding provides support for the view that burnout is a problem of the whole health care organization, rather than individuals.

Social Organization of Medical Work

Abstract: Technologies developed to manage long-term, incurable illnesses have radically and irrevocably altered t he organisational structure of health care, presenting us wi th a bewildering array of medical specialities. '

Machine Learning and Data Mining Methods in Diabetes Research.

Abstract: The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

Wearable Sensors for Remote Health Monitoring.

Abstract: Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed.

Prevention and monitoring of cardiac dysfunction in survivors of adult cancers: American society of clinical oncology clinical practice guideline

Abstract: Purpose Cardiac dysfunction is a serious adverse effect of certain cancer-directed therapies that can interfere with the efficacy of treatment, decrease quality of life, or impact the actual survival of the patient with cancer. The purpose of this effort was to develop recommendations for prevention and monitoring of cardiac dysfunction in survivors of adult-onset cancers. Methods Recommendations were developed by an expert panel with multidisciplinary representation using a systematic review (1996 to 2016) of meta-analyses, randomized clinical trials, observational studies, and clinical experience. Study quality was assessed using established methods, per study design. The guideline recommendations were crafted in part using the Guidelines Into Decision Support methodology. Results A total of 104 studies met eligibility criteria and compose the evidentiary basis for the recommendations. The strength of the recommendations in these guidelines is based on the quality, amount, and consistency of the evidence and the balance between benefits and harms. Recommendations It is important for health care providers to initiate the discussion regarding the potential for cardiac dysfunction in individuals in whom the risk is sufficiently high before beginning therapy. Certain higher risk populations of survivors of cancer may benefit from prevention and screening strategies implemented during cancer-directed therapies. Clinical suspicion for cardiac disease should be high and threshold for cardiac evaluation should be low in any survivor who has received potentially cardiotoxic therapy. For certain higher risk survivors of cancer, routine surveillance with cardiac imaging may be warranted after completion of cancer-directed therapy, so that appropriate interventions can be initiated to halt or even reverse the progression of cardiac dysfunction.

Quitting Smoking Among Adults — United States, 2000–2015

Abstract: Quitting cigarette smoking benefits smokers at any age (1). Individual, group, and telephone counseling and seven Food and Drug Administration-approved medications increase quit rates (1-3). To assess progress toward the Healthy People 2020 objectives of increasing the proportion of U.S. adults who attempt to quit smoking cigarettes to ≥80.0% (TU-4.1), and increasing recent smoking cessation success to ≥8.0% (TU-5.1),* CDC assessed national estimates of cessation behaviors among adults aged ≥18 years using data from the 2000, 2005, 2010, and 2015 National Health Interview Surveys (NHIS). During 2015, 68.0% of adult smokers wanted to stop smoking, 55.4% made a past-year quit attempt, 7.4% recently quit smoking, 57.2% had been advised by a health professional to quit, and 31.2% used cessation counseling and/or medication when trying to quit. During 2000-2015, increases occurred in the proportion of smokers who reported a past-year quit attempt, recently quit smoking, were advised to quit by a health professional, and used cessation counseling and/or medication (p<0.05). Throughout this period, fewer than one third of persons used evidence-based cessation methods when trying to quit smoking. As of 2015, 59.1% of adults who had ever smoked had quit. To further increase cessation, health care providers can consistently identify smokers, advise them to quit, and offer them cessation treatments (2-4). In addition, health insurers can increase cessation by covering and promoting evidence-based cessation treatments and removing barriers to treatment access (2,4-6).

Uncertainty and the welfare economics of medical care: an Austrian rebuttal Part 2

Abstract: Part 2 of this 3 part series continues a rebuttal to Kenneth Arrow’s famous argument that health care is special and free market economic principles do not apply. The rebuttal is based on concepts of Austrian Economics. Part 1 of the series framed the debate and discussed general concepts. Part 2 discusses specific examples of how health care is special and does not behave according to market principles. Uncertainty of demand and uncertainty of outcome are discussed in detail. Information asymmetry is a special form of uncertainty that Kenneth Arrow claimed was somewhat unique to health care. Free market solutions to these problems are discussed in general with specific examples provided. The conclusions are that free market insurance (as opposed to subsidy) handles uncertainty of demand, branding handles uncertainty of outcome, and the free market for specialized information handles information asymmetry.

Barriers of Influenza Vaccination Intention and Behavior – A Systematic Review of Influenza Vaccine Hesitancy, 2005 – 2016

Abstract: Background Influenza vaccine hesitancy is a significant threat to global efforts to reduce the burden of seasonal and pandemic influenza. Potential barriers of influenza vaccination need to be identified to inform interventions to raise awareness, influenza vaccine acceptance and uptake. Objective This review aims to (1) identify relevant studies and extract individual barriers of seasonal and pandemic influenza vaccination for risk groups and the general public; and (2) map knowledge gaps in understanding influenza vaccine hesitancy to derive directions for further research and inform interventions in this area. Methods Thirteen databases covering the areas of Medicine, Bioscience, Psychology, Sociology and Public Health were searched for peer-reviewed articles published between the years 2005 and 2016. Following the PRISMA approach, 470 articles were selected and analyzed for significant barriers to influenza vaccine uptake or intention. The barriers for different risk groups and flu types were clustered according to a conceptual framework based on the Theory of Planned Behavior and discussed using the 4C model of reasons for non-vaccination. Results Most studies were conducted in the American and European region. Health care personnel (HCP) and the general public were the most studied populations, while parental decisions for children at high risk were under-represented. This study also identifies understudied concepts. A lack of confidence, inconvenience, calculation and complacency were identified to different extents as barriers to influenza vaccine uptake in risk groups. Conclusion Many different psychological, contextual, sociodemographic and physical barriers that are specific to certain risk groups were identified. While most sociodemographic and physical variables may be significantly related to influenza vaccine hesitancy, they cannot be used to explain its emergence or intensity. Psychological determinants were meaningfully related to uptake and should therefore be measured in a valid and comparable way. A compendium of measurements for future use is suggested as supporting information.

Recognizing Sepsis as a Global Health Priority - A WHO Resolution.

Abstract: The World Health Organization has adopted a resolution on improving the prevention, diagnosis, and management of sepsis. Millions of lives can be saved if politicians, policymakers, health care administrators, researchers, and clinicians take coordinated actions.

Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations

Abstract: Big data, we have all heard, promise to transform health care. But in the “hype cycle” of emerging technologies, machine learning now rides atop the “peak of inflated expectations,” and we need to better appreciate the technology’s capabilities and limitations.

Effects of Care Coordination on Hospitalization, Quality of Care, and Health Care Expenditures Among Medicare Beneficiaries

Abstract: Supplementary material http://jama.ama-assn.org/cgi/content/full/301/6/603/DC1 eTables Correction Contact me if this article is corrected. Citations Contact me when this article is cited. This article has been cited 1 time. Topic collections Contact me when new articles are published in these topic areas. Medicine; Quality of Care; Quality of Care, Other; Randomized Controlled Trial Aging/ Geriatrics; Medical Practice; Medical Practice, Other; Primary Care/ Family

EQ-5D and the EuroQol Group: Past, Present and Future.

Abstract: Over the period 1987-1991 an inter-disciplinary five-country group developed the EuroQol instrument, a five-dimensional three-level generic measure subsequently termed the 'EQ-5D'. It was designed to measure and value health status. The salient features of its development and its consolidation and expansion are discussed. Initial expansion came, in particular, in the form of new language versions. Their development raised translation and semantic issues, experience with which helped feed into the design of two further instruments, the EQ-5D-5L and the youth version EQ-5D-Y. The expanded usage across clinical programmes, disease and condition areas, population surveys, patient-reported outcomes, and value sets is outlined. Valuation has been of continued relevance for the Group as this has allowed its instruments to be utilised as part of the economic appraisal of health programmes and their incorporation into health technology assessments. The future of the Group is considered in the context of: (1) its scientific strategy, (2) changes in the external environment affecting the demand for EQ-5D, and (3) a variety of issues it is facing in the context of the design of the instrument, its use in health technology assessment, and potential new uses for EQ-5D outside of clinical trials and technology appraisal.

Standards for Reporting Implementation Studies (StaRI) Statement

Abstract: Implementation studies are often poorly reported and indexed, reducing their potential to inform initiatives to improve healthcare services. The Standards for Reporting Implementation Studies (StaRI) initiative aimed to develop guidelines for transparent and accurate reporting of implementation studies. Informed by the findings of a systematic review and a consensus-building e-Delphi exercise, an international working group of implementation science experts discussed and agreed the StaRI Checklist comprising 27 items. It prompts researchers to describe both the implementation strategy (techniques used to promote implementation of an underused evidence-based intervention) and the effectiveness of the intervention that was being implemented. An accompanying Explanation and Elaboration document (published in BMJ Open, doi:10.1136/bmjopen-2016-013318) details each of the items, explains the rationale, and provides examples of good reporting practice. Adoption of StaRI will improve the reporting of implementation studies, potentially facilitating translation of research into practice and improving the health of individuals and populations.

Interprofessional collaboration to improve professional practice and healthcare outcomes

Abstract: Background Poor interprofessional collaboration (IPC) can adversely affect the delivery of health services and patient care. Interventions that address IPC problems have the potential to improve professional practice and healthcare outcomes. Objectives To assess the impact of practice-based interventions designed to improve interprofessional collaboration (IPC) amongst health and social care professionals, compared to usual care or to an alternative intervention, on at least one of the following primary outcomes: patient health outcomes, clinical process or efficiency outcomes or secondary outcomes (collaborative behaviour). Search methods We searched CENTRAL (2015, issue 11), MEDLINE, CINAHL, ClinicalTrials.gov and WHO International Clinical Trials Registry Platform to November 2015. We handsearched relevant interprofessional journals to November 2015, and reviewed the reference lists of the included studies. Selection criteria We included randomised trials of practice-based IPC interventions involving health and social care professionals compared to usual care or to an alternative intervention. Data collection and analysis Two review authors independently assessed the eligibility of each potentially relevant study. We extracted data from the included studies and assessed the risk of bias of each study. We were unable to perform a meta-analysis of study outcomes, given the small number of included studies and their heterogeneity in clinical settings, interventions and outcomes. Consequently, we summarised the study data and presented the results in a narrative format to report study methods, outcomes, impact and certainty of the evidence. Main results We included nine studies in total (6540 participants); six cluster-randomised trials and three individual randomised trials (1 study randomised clinicians, 1 randomised patients, and 1 randomised clinicians and patients). All studies were conducted in high-income countries (Australia, Belgium, Sweden, UK and USA) across primary, secondary, tertiary and community care settings and had a follow-up of up to 12 months. Eight studies compared an IPC intervention with usual care and evaluated the effects of different practice-based IPC interventions: externally facilitated interprofessional activities (e.g. team action planning; 4 studies), interprofessional rounds (2 studies), interprofessional meetings (1 study), and interprofessional checklists (1 study). One study compared one type of interprofessional meeting with another type of interprofessional meeting. We assessed four studies to be at high risk of attrition bias and an equal number of studies to be at high risk of detection bias. For studies comparing an IPC intervention with usual care, functional status in stroke patients may be slightly improved by externally facilitated interprofessional activities (1 study, 464 participants, low-certainty evidence). We are uncertain whether patient-assessed quality of care (1 study, 1185 participants), continuity of care (1 study, 464 participants) or collaborative working (4 studies, 1936 participants) are improved by externally facilitated interprofessional activities, as we graded the evidence as very low-certainty for these outcomes. Healthcare professionals' adherence to recommended practices may be slightly improved with externally facilitated interprofessional activities or interprofessional meetings (3 studies, 2576 participants, low certainty evidence). The use of healthcare resources may be slightly improved by externally facilitated interprofessional activities, interprofessional checklists and rounds (4 studies, 1679 participants, low-certainty evidence). None of the included studies reported on patient mortality, morbidity or complication rates. Compared to multidisciplinary audio conferencing, multidisciplinary video conferencing may reduce the average length of treatment and may reduce the number of multidisciplinary conferences needed per patient and the patient length of stay. There was little or no difference between these interventions in the number of communications between health professionals (1 study, 100 participants; low-certainty evidence). Authors' conclusions Given that the certainty of evidence from the included studies was judged to be low to very low, there is not sufficient evidence to draw clear conclusions on the effects of IPC interventions. Neverthess, due to the difficulties health professionals encounter when collaborating in clinical practice, it is encouraging that research on the number of interventions to improve IPC has increased since this review was last updated. While this field is developing, further rigorous, mixed-method studies are required. Future studies should focus on longer acclimatisation periods before evaluating newly implemented IPC interventions, and use longer follow-up to generate a more informed understanding of the effects of IPC on clinical practice.

Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop

Abstract: Devices and programs using digital technology to foster or support behavior change (digital interventions) are increasingly ubiquitous, being adopted for use in patient diagnosis and treatment, self-management of chronic diseases, and in primary prevention. They have been heralded as potentially revolutionizing the ways in which individuals can monitor and improve their health behaviors and health care by improving outcomes, reducing costs, and improving the patient experience. However, we are still mainly in the age of promise rather than delivery. Developing and evaluating these digital interventions presents new challenges and new versions of old challenges that require use of improved and perhaps entirely new methods for research and evaluation. This article discusses these challenges and provides recommendations aimed at accelerating the rate of progress in digital behavior intervention research and practice. Areas addressed include intervention development in a rapidly changing technological landscape, promoting user engagement, advancing the underpinning science and theory, evaluating effectiveness and cost-effectiveness, and addressing issues of regulatory, ethical, and information governance. This article is the result of a two-day international workshop on how to create, evaluate, and implement effective digital interventions in relation to health behaviors. It was held in London in September 2015 and was supported by the United Kingdom's Medical Research Council (MRC), the National Institute for Health Research (NIHR), the Methodology Research Programme (PI Susan Michie), and the Robert Wood Johnson Foundation of the United States (PI Kevin Patrick). Important recommendations to manage the rapid pace of change include considering using emerging techniques from data science, machine learning, and Bayesian approaches and learning from other disciplines including computer science and engineering. With regard to assessing and promoting engagement, a key conclusion was that sustained engagement is not always required and that for each intervention it is useful to establish what constitutes "effective engagement," that is, sufficient engagement to achieve the intended outcomes. The potential of digital interventions for testing and advancing theories of behavior change by generating ecologically valid, real-time objective data was recognized. Evaluations should include all phases of the development cycle, designed for generalizability, and consider new experimental designs to make the best use of rich data streams. Future health economics analyses need to recognize and model the complex and potentially far-reaching costs and benefits of digital interventions. In terms of governance, developers of digital behavior interventions should comply with existing regulatory frameworks, but with consideration for emerging standards around information governance, ethics, and interoperability.

Adherence to Methodological Standards in Research Using the National Inpatient Sample.

Abstract: Importance Publicly available data sets hold much potential, but their unique design may require specific analytic approaches. Objective To determine adherence to appropriate research practices for a frequently used large public database, the National Inpatient Sample (NIS) of the Agency for Healthcare Research and Quality (AHRQ). Design, Setting, and Participants In this observational study of the 1082 studies published using the NIS from January 2015 through December 2016, a representative sample of 120 studies was systematically evaluated for adherence to practices required by AHRQ for the design and conduct of research using the NIS. Exposures None. Main Outcomes and Measures All studies were evaluated on 7 required research practices based on AHRQ’s recommendations and compiled under 3 domains: (1) data interpretation (interpreting data as hospitalization records rather than unique patients); (2) research design (avoiding use in performing state-, hospital-, and physician-level assessments where inappropriate; not using nonspecific administrative secondary diagnosis codes to study in-hospital events); and (3) data analysis (accounting for complex survey design of the NIS and changes in data structure over time). Results Of 120 published studies, 85% (n = 102) did not adhere to 1 or more required practices and 62% (n = 74) did not adhere to 2 or more required practices. An estimated 925 (95% CI, 852-998) NIS publications did not adhere to 1 or more required practices and 696 (95% CI, 596-796) NIS publications did not adhere to 2 or more required practices. A total of 79 sampled studies (68.3% [95% CI, 59.3%-77.3%]) among the 1082 NIS studies screened for eligibility did not account for the effects of sampling error, clustering, and stratification; 62 (54.4% [95% CI, 44.7%-64.0%]) extrapolated nonspecific secondary diagnoses to infer in-hospital events; 45 (40.4% [95% CI, 30.9%-50.0%]) miscategorized hospitalizations as individual patients; 10 (7.1% [95% CI, 2.1%-12.1%]) performed state-level analyses; and 3 (2.9% [95% CI, 0.0%-6.2%]) reported physician-level volume estimates. Of 27 studies (weighted; 218 studies [95% CI, 134-303]) spanning periods of major changes in the data structure of the NIS, 21 (79.7% [95% CI, 62.5%-97.0%]) did not account for the changes. Among the 24 studies published in journals with an impact factor of 10 or greater, 16 (67%) did not adhere to 1 or more practices, and 9 (38%) did not adhere to 2 or more practices. Conclusions and Relevance In this study of 120 recent publications that used data from the NIS, the majority did not adhere to required practices. Further research is needed to identify strategies to improve the quality of research using the NIS and assess whether there are similar problems with use of other publicly available data sets.

A three-talk model for shared decision making: multistage consultation process

Abstract: OBJECTIVES To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. DESIGN Multistage consultation process. SETTING Key informant group, communities of interest, and survey of clinical specialties. PARTICIPANTS 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. RESULTS After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. CONCLUSIONS The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences.

Integrating blockchain for data sharing and collaboration in mobile healthcare applications

Abstract: Enabled by mobile and wearable technology, personal health data delivers immense and increasing value for healthcare, benefiting both care providers and medical research The secure and convenient sharing of personal health data is crucial to the improvement of the interaction and collaboration of the healthcare industry Faced with the potential privacy issues and vulnerabilities existing in current personal health data storage and sharing systems, as well as the concept of self-sovereign data ownership, we propose an innovative user-centric health data sharing solution by utilizing a decentralized and permissioned blockchain to protect privacy using channel formation scheme and enhance the identity management using the membership service supported by the blockchain A mobile application is deployed to collect health data from personal wearable devices, manual input, and medical devices, and synchronize data to the cloud for data sharing with healthcare providers and health insurance companies To preserve the integrity of health data, within each record, a proof of integrity and validation is permanently retrievable from cloud database and is anchored to the blockchain network Moreover, for scalable and performance considerations, we adopt a tree-based data processing and batching method to handle large data sets of personal health data collected and uploaded by the mobile platform

Asthma costs and social impact

Abstract: In recent decades, both asthma prevalence and incidence have been increasing worldwide, not only due to the genetic background, but mainly because of the effect of a wide number of environmental and lifestyle risk factors. In many countries noncommunicable diseases, like asthma, are not yet considered a healthcare priority. This review will analyze and discuss disparities in asthma management in several countries and regions, such as access to healthcare human resources and medications, due to limited financial capacity to develop strategies to control and prevent this chronic disease. This review tries to explore the social and economic burden of asthma impact on society. Although asthma is generally accepted as a costly illness, the total costs to society (direct, indirect and intangible asthma costs) are difficult to estimate, mainly due to different disease definitions and characterizations but also to the use of different methodologies to assess the asthma socio-economic impact in different societies. The asthma costs are very variables from country to country, however we can estimate that a mean cost per patient per year, including all asthmatics (intermittent, mild, moderate and severe asthma) in Europe is $USD 1,900, which seems lower than USA, estimated mean $USD 3,100.

GRAM: Graph-based Attention Model for Healthcare Representation Learning

Abstract: Deep learning methods exhibit promising performance for predictive modeling in healthcare, but two important challenges remain: - Data insufficiency: Often in healthcare predictive modeling, the sample size is insufficient for deep learning methods to achieve satisfactory results. Interpretation: The representations learned by deep learning methods should align with medical knowledge. To address these challenges, we propose GRaph-based Attention Model (GRAM) that supplements electronic health records (EHR) with hierarchical information inherent to medical ontologies. Based on the data volume and the ontology structure, GRAM represents a medical concept as a combination of its ancestors in the ontology via an attention mechanism. We compared predictive performance (i.e. accuracy, data needs, interpretability) of GRAM to various methods including the recurrent neural network (RNN) in two sequential diagnoses prediction tasks and one heart failure prediction task. Compared to the basic RNN, GRAM achieved 10% higher accuracy for predicting diseases rarely observed in the training data and 3% improved area under the ROC curve for predicting heart failure using an order of magnitude less training data. Additionally, unlike other methods, the medical concept representations learned by GRAM are well aligned with the medical ontology. Finally, GRAM exhibits intuitive attention behaviors by adaptively generalizing to higher level concepts when facing data insufficiency at the lower level concepts.

Bright Futures Guidelines for Health Supervision of Infants, Children, and Adolescents, 4th Ed

Abstract: This essential resource provides key background information and recommendations for themes critical to healthy child development along with well-child supervision standards for 31 age-based visits--from Newborn through 21 Years. The result: better health care, more efficient visits, stronger partnerships with children and families, and better ability to keep up with changes in family, communities, and society that affect a child's health.

National and State Estimates of the Numbers of Adults and Children with Active Epilepsy - United States, 2015.

Abstract: Epilepsy, a brain disorder leading to recurring seizures, has garnered increased public health focus because persons with epilepsy experience pronounced and persistent health and socioeconomic disparities despite treatment advances, public awareness programs, and expanded rights for persons with disabilities (1,2). For almost all states, epilepsy prevalence estimates do not exist. CDC used national data sources including the 2015 National Health Interview Survey (NHIS) for adults (aged ≥18 years), the 2011-2012 National Survey of Children's Health (NSCH), and the 2015 Current Population Survey data, describing 2014 income levels, to estimate prevalent cases of active epilepsy, overall and by state, to provide information for state public health planning. In 2015, 1.2% of the U.S. population (3.4 million persons: 3 million adults and 470,000 children) reported active epilepsy (self-reported doctor-diagnosed epilepsy and under treatment or with recent seizures within 12 months of interview) or current epilepsy (parent-reported doctor-diagnosed epilepsy and current epilepsy). Estimated numbers of persons with active epilepsy, after accounting for income and age differences by state, ranged from 5,900 in Wyoming to 427,700 in California. NHIS data from 2010-2015 indicate increases in the number of persons with active epilepsy, probably because of population growth. This study provides updated national and modeled state-specific numbers of active epilepsy cases. Public health practitioners, health care providers, policy makers, epilepsy researchers, and other epilepsy stakeholders, including family members and people with epilepsy, can use these findings to ensure that evidence-based programs meet the complex needs of adults and children with epilepsy and reduce the disparities resulting from it.