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We study changes in age-specific diabetes-related mortality and annual health care utilization. We find that half of the estimated 16% increase of diabetic mortality falls within employable age groups. We estimate that disease combination-specific increase in case fatality has resulted in premature diabetic mortality costing $3.2 billion annually. The estimated annual direct cost of treating high-risk diabetics reaches $36 billion, of which Medicare and Other Federal Programs compensate 54%. Respiratory conditions among diabetics comprise the same proportion of high-risk diabetics as do the disease combinations including coronary heart diseases. Treating of general diabetic conditions has become more efficient as indicated by the estimated declines in per unit health care costs.

The Epidemiologic Transition can help us understand a fundamental puzzle about aging. The puzzle stems from two seemingly contradictory facts. The first fact is that death rates from noninfectious degenerative maladies – the so-called diseases of aging – increase as people age. It seems to be at odds with the historical fact that for nearly a century in which people were aging more than ever before, the aggregate rates of such diseases have been decreasing. In what sense can both be true? Crucial to resolving the puzzle are the age-profiles of such diseases in cohorts that grew up in the different regimes of the Transition. For each cohort, noninfectious diseases had increased with age, resulting in an upward-sloping age profile, which affirms the first fact. As the regimes were transitioning from the Malthusian to the modern one, however, the profiles of successive cohorts had been shifting downward: death rates from noninfectious diseases were shrinking at each age, signifying the newer cohorts’ greater aging potentials. The shifting profiles had been renewing the cohort mix of the population, shaping the century-long descent of such diseases in aggregate, giving rise to the historical fact. The profiles had shifted early in the cohorts’ adult years, associating closely with the newer epidemiologic conditions in childhood. Those conditions appear to be a circumstance under which aging potentials of cohorts could be misgauged, including in one troubling episode in the first half of the nineteenth century when the potentials had reversed.

The purpose of this paper is to investigate the moderating effect of disease risk in terms of the major signals (i.e. status, reputation and self-representation) on the e-consultation platforms.

In this study, the proposed research hypotheses are tested using the transaction data collected from xywy.com (in Need of Therapy). In fact, xywy.com is one the leading e-consultation service websites in China that provides a platform for the interactions between the physicians and patients (Yu et al., 2016; Peng et al., 2015). Generally speaking, it has all the needed design elements and in other words, a standard e-consultation website should have such items/components as physician homepage, physician review, free consultation, paid consultation and recommendation systems.

The obtained results reveal that all attributes including status, reputation and self-representation have a positive impact on physician’s online order volume. Moreover, there is a positive moderating effect of disease risk onto the online reputation, indicating a higher effect exists for the diseases with high risk. However, the effect of offline status and online self-representation is not moderated by the disease risk, indicating market signals (online reputation) may have a stronger predictive power than seller signals (offline status and online self- representation), and therefore market signals are more effective when/if the disease risk is high.

E-consultation has gradually become a significant trend to provide the healthcare services, in the emerging economy such as China because of shortage of medical resources but having an adequate access in internet usage. The impacts of signals on the health care market have been validated by previous studies. However, the research focusing on the moderating effect of signaling environment in the health care industry is still lacking. As a result, the value of this research helps to bridge the aforementioned research gap.

Using micro data on virtually all of the drugs and diseases of over 500,000 people enrolled in Puerto Rico's Medicaid program, the impact of the vintage (original FDA approval year) of drugs used to treat a patient on the patient's three-year probability of survival, controlling for demographic characteristics (age, sex, and region), utilization of medical services, and the nature and complexity of illness are examined. It is found that people using newer drugs during January–June, 2000, were less likely to die by the end of 2002, conditional on the covariates. The estimated mortality rates are strictly declining with respect to drug vintage. For pre-1970 drugs, the estimated mortality rate is 4.4%. The mortality rates for 1970s, 1980s, and 1990s drugs are 3.6%, 3.0%, and 2.5%, respectively. The actual mortality rate is about 16% (3.7% vs. 4.4%) lower than it would have been if all of the drugs utilized in 2000 had been pre-1970 drugs. Estimates for subgroups of people with specific diseases display the same general pattern.

Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive measures and to reduce the impact of epidemic in an area.

A deep neural network (DNN) based context aware smart epidemic system has been proposed to prevent and monitor epidemic spread in a geographical area. Various neural networks (NNs) have been used: LSTM, RNN, BPNN to detect the level of disease, direction of spread of disease in a geographical area and marking the high-risk areas. Multiple DNNs collect and process various data points and these DNNs are decided based on type of data points. Output of one DNN is used by another DNN to reach to final prediction.

The experimental evaluation of the proposed framework achieved the accuracy of 87% for the synthetic dataset generated for Zika epidemic in Brazil in 2016.

The proposed framework is designed in a way that every data point is carefully processed and contributes to the final decision. These multiple DNNs will act as a single DNN for the end user.

To assist in achieving cost effective health care allocations in a collective choice setting, the purpose of this paper is to illustrate the use of a tool not common in the public budgeting literature but is common in the health economics literature.

Through a meta-analysis of the health care spending literature that computed the value of quality-adjusted life years, the authors provide an alternative approach for budgeters and policymakers.

The authors provide an alternative approach for budgeters and policymakers for weighing the benefits of alternative health care spending allocations.

The authors introduce an alternative approach for weighing the benefits of alternative health care spending allocations. As a tool for budgeting professionals, cost per QALY allows for the opportunity to raise cost-effectiveness of public health expenditures as a tool for governments to allocate resources based on outcomes, rather than inputs.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Bats provide many ecosystem services and have intrinsic value. They also act as host reservoirs for some viruses. Several studies have linked zoonotic diseases to bats, raising questions about the risks bats pose, especially to people living close to bat roosts. Through a series of case studies undertaken in three communities, the purpose of this paper is to explore the various ways in which framings and perceptions of bats can influence a potential spillover of bat-borne viruses to humans in Ghana. It assesses the social, cultural and economic factors that drive human-bat interactions and posits that understanding the socio-economic contexts in which human-bat interactions occur is key to the success of future communication strategies.

Primary data collection methods included participatory landscape mappings, transect walks, focus group discussions and questionnaire surveys.

Perceptions of bats vary and are influenced by personal beliefs, the perceived economic benefits derived from bats and the location of bat roosts. Activities that put people at risk include bat hunting, butchering and consumption of poorly prepared bat meat. Those who live and work close to bat roosts, and bat hunters, for example, are more at risk of bat-borne zoonotic disease spillover. Disease risk perceptions were generally low, with high levels of uncertainty, indicating the need for clearer information about personal protective practices.

The results of the study may well inform future risk communication strategies as well as help in developing effective responses to zoonotic disease risk, disease outbreaks and the conservation of bats in communities.

Purpose – To explore how home care social worker perceptions of their organizations' dominant goals and means affect direct service home care professionals' care delivery and meeting of patient needs for persons with Alzheimer's disease.

Methodology/approach – The study used a convenience sample of 34 home care social workers in the New York City metropolitan area and an extensive literature review.

Findings – The study found that literature indicates a dissonance between effective, evidence-based research psychosocial Alzheimer's disease interventions and Medicare home health policy which does not cover their use. Furthermore, interviews indicated home care social workers' different strategies to cope with organization demands, which affect their perceptions and care delivered to patients. The coping strategies are characterized using a modified version of Merton's (1957) adaptation model – conformist, innovator, and rebel.

Contribution to the field – The study is the first to use the voice of home care social workers to explore how perceptions of organizational dominant goals and means affect direct service home care professionals' care delivery and meeting of patient needs. The study asserts the need for a home care-based policy model drawing on the Hospice Medicare Benefit (HMB) to address Alzheimer's disease more cost-effectively with a more positive quality of life manner, thus limiting the adverse consequences of the evolving epidemic.

EigenFactor service went through some changes in 2011 before issuing the most current edition (EF‐2010) following the release of the 2010 edition of the Journal Citation Reports (JCR‐2010) in mid‐2011. Ranking journals by the EigenFactor Score (EFS) and the Article Influence Score (AIS) offered an additional pair of bibliometric indicators to assess the impact of journals in the (sub)disciplinary fields of the sciences and social sciences. In evaluating the clout, importance, and impact of journals it is essential to compare apples to apples, i.e. limiting the assessments to journals belonging to the same (sub)disciplinary areas. This paper aims to examine the quality of the subject categories created for EF‐2010 and of the JCR‐2010 subject categories as implemented within the EigenFactor services.

The paper compares the adequacy of the subject categories in the JCR‐2010 and EF‐2010, examining the assignment of 77 information and library science journals and 50 business/marketing journals to the 64 subject categories used in EF‐2010.

The study finds that EF‐2010 uses a very broad categorisation system of merely 64 subject categories along with the much more specific subject categories originally developed and enhanced for the JCR database of the Institute for Scientific Information (now Thomson‐Reuters). JCR‐2010 has four times as many categories than the former, and would offer a far more realistic comparison of the impact of comparable journals in EF‐2010 if the developers of the EigenFactor database had retained the assignment of the journals to the JCR subject categories. The inconsistency, inaccuracy and incompleteness of the journal classification practice in EF‐2010 creates a highly distorted picture of the standing of journals in their (sub)disciplinary leagues, and makes it very difficult for the users to reproduce the far more refined league lists of journals.

The paper describes the most serious limitations and errors in the classification of journals in the EF‐2010 edition.