Tag Archives: Population Health

Ethical Concepts of the New Public Health

I am currently working on two essays that I needed to submit with my fellowship application, but the event in Paris made me stop for a few minutes and reflect on the scorching reminder that terrorism has no religion, a brand of madness, not faith. Such event amplified the urgency to stress the significance of New Public Health that carries a high potential for healthy less aggressive societies.  The main principles of living together in healthy communities were summarized by Laaser et al. (2002) as four ethical concepts of the New Public Health essential to violence reduction – equity, participation, subsidiarity, and sustainability. The coupling of current economic, demographic, and social issues will play a role in guiding future policy revisions. While my fellowship of interest is in epidemiology and infectious diseases, increased understanding of the interrelated dimensions of deracination or forced migration using the modern concept of public health is warranted. It is critical to understand the determinants of violence: the type of stigmatization; the process of urbanization; religious, ethnic, and racial prejudices; women’s status; the level of education; employment status; socialization of the family; availability of firearms;  alcohol and drug consumption;  and poverty.

Reference

Laaser, U., Donev, D., Bjegovic, V., & Sarolli, Y. (2002). Public health and peace. Croatian medical journal, 43(2), 107-113.

In Texas, Everything is Bigger: In the context of data collection—is bigger better?

The traditional researcher concept that big data equates statistical significance could always eclipse the importance of understanding the interrelationship between the effect size, power, and sample size that could translate to both practical and statistical significance. In Texas, everything is bigger, everything a Texan do is bigger, but in the context of data collection—is bigger better? Current big data opportunities facing science, technology communities, and the health community is facing a tsunami of health- and healthcare-related content generated from numerous patient care points of contact, sophisticated medical instruments, and web-based health communities (Chen, Chiang & Storey, 2012). Two primary sources of health big data are payer–provider big data (electronic health records, insurance records, pharmacy prescription, patient feedback and responses), and data from my favorite field-genomics. I cannot help to imagine how many interesting research studies I could do with genomics-driven big data (genotyping, gene expression, sequencing data). Extracting knowledge from health big data poses significant research and practical challenges, especially considering the HIPAA (Health Insurance Portability and Accountability Act) and IRB (Institutional Review Board) requirements for building a privacy-preserving and trust-worthy health infrastructure and conducting ethical health-related research (Gelfand, 2011). Setting aside these challenges, can big data provide both practical and statistical significance? Just think about terabytes of expected raw sequencing data that associate variants that affect variation in two common highly heritable measures of obesity, weight and body mass index (BMI). For this discussion, let me broach the 2012 study of Hutchinson and Wilson in improving nutrition and physical activity in the workplace. The cumulative knowledge found in the meta-analysis of Hutchinson & Wilson (2012) found the extant results of 29 intervention studies examining physical activity or nutrition interventions in the workplace, published between 1999 and March 2009. The results from these 29 intervention studies were synthesized using meta-analyses in terms of the effectiveness of workplace health promotion programs to resolve inconsistent findings. The challenge of extant results that are sometimes discordant, Hutchinson & Wilson (2012) took into consideration the limitations in the methodology of some of the studies reviewed that demonstrated modest success in achieving long-term change. The importance of interventions’ association with successful outcomes that includes behavior maintenance and generalization was also considered in this study. Weighted Cohen’s d effect sizes, percentage overlap statistics, confidence intervals and failsafe Ns were calculated. The increased prevalence of obesity and its association with increased risk for chronic diseases including cancer, diabetes, cancer and cardiovascular disease warrants the needs for innovative and efficient interventions. Green (1988), stated that the workplace is a valuable intervention site for a number of reasons including the amount of time people spend at work, access to populations that may be difficult to engage in different settings and the opportunity to utilize peer networks and employer incentives. These reasons justify the practical significance of the study. Moreover, the statistical significance was established by the methodology of Hutchinson & Wilson (2012) developing inclusion criteria of the 29 identified studies. The inclusion criteria are published studies on workplace intervention; a control group, not receiving the intervention, health, and in particular diet, nutrition or physical activity as outcome measures; and statistical information for the calculation of effect sizes, (e.g. means and standard deviations, the results of t-tests or one-way F tests).Change over time (mean and standard deviation) data were requisite to calculate effect sizes for interventions. Studies that did not provide this data, the means and standard deviations at the end of the intervention of controls and interventions groups were compared. Statistical analyses was performed such as Cohen’s d to calculate effect sizes for the difference between the intervention and control groups on each outcome measure (diet measures: fruit, vegetables, fat; physical activity measures: activity, fitness; health measures: weight, cholesterol, blood pressure, heart rate or glucose). Based on outcome measures and the form of intervention, effect sizes were aggregated. Mean effect size, standard deviation and 95% confidence interval were calculated for each grouping (Zakzanis, 2001). Fail safe Ns (Nfs) were calculated to address the potential for studies with statistically significant results. The conclusion of this 2012 meta-analysis in terms of study design—randomized controlled trials were associated with larger effects; therefore, long-term maintenance of changes should be evaluated in order to determine the extent to which workplace interventions can make sustainable changes to individuals’ health.

References

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly36(4), 1165-1188. Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press. Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press. Forthofer, R.N., Lee, E.S. & Hernandez, M. (2006). Biostatistics: A Guide to Design, Analysis and Discovery. 2nd Edition [Vital Source Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9780123694928 Gelfand, A. (2011). Privacy and biomedical research: building a trust infrastructure: an exploration of data-driven and process-driven approaches to data privacy. Biomed Comput Rev2012, 23-28. Green, K. L. (1988). Issues of control and responsibility in workers’ health. Health Education & Behavior15(4), 473-486. Hutchinson, A. D., & Wilson, C. (2012). Improving nutrition and physical activity in the workplace: a meta-analysis of intervention studies. Health promotion international27(2), 238-249. Labilles, U. (2015). Big Data: Does it matter? Can it give a practical significance? Is bigger better? (Unpublished, Advanced Biostatistics (PUBH – 8500 – 1), 2015 Spring Qtr. Wk2DiscLabillesU) Walden University, Minneapolis. Thorleifsson, G., Walters, G. B., Gudbjartsson, D. F., Steinthorsdottir, V., Sulem, P., Helgadottir, A., … & Stefansson, K. (2009). Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nature genetics41(1), 18-24. Zakzanis, K. K. (2001). Statistics to tell the truth, the whole truth, and nothing but the truth: formulae, illustrative numerical examples, and heuristic interpretation of effect size analyses for neuropsychological researchers. Archives of clinical neuropsychology16(7), 653-667.

Socioeconomic Status and Public Health Financing

Health financing is the cornerstone of strategy development based on both in terms of raising resources and of ways to manage resources. It is critical to emphasize the need for greater evaluation of the distributional impact of policies and programs. Socioeconomic status could affect public health financing such as people with insurance or money, creating higher expenditures. On the other hand, medically underserved, uninsured and underinsured create greater expenses because they enter the health system at the advanced stages of diseases and in weakened conditions (Laureate Education, Inc., 2012). In addition to socioeconomic status, other social determinants that affects both average and distribution of health includes physical environment, lifestyle or behavior, working conditions, social network, family, demographics, political, legal, institutional and cultural factors. Since funding is considered as a scarce resource, it is paramount to allocate resources based on the identified gaps in care. The significance of socioeconomic data in US public health surveillance systems should be emphasized in order to monitor socio-economic gradients in health. Socioeconomic data is important in determining the allocation of resources for public health financing. Krieger et al. (2003) stated that the use of multilevel frameworks and area-based socioeconomic measures (ABSMs) for public health monitoring can potentially overcome the absence of socioeconomic data in most US public health surveillance systems. Moreover, political will is essential to bridging public health and action that will help in the development and implementation of public health policy based on scientific evidence and community participation. Epstein, Stern and Weissman (1990) found that hospitalized patients with lower socioeconomic status have longer stays and require more resources. It was suggested in this study that supplementary payments allocated to the poor merits further consideration. Strategies for more efficient provision of care for patients with low socioeconomic status can be developed at the managerial and clinical levels.

Inequality or disparity is defined as the difference in health status, inequalities in access to and quality of health care services. Additional disparities are attributed to factors such as discrimination in relation to health care system and the regulatory climate. The Institute of Medicine (IOM) found that disparities continue to dwell even when socio-demographic factors, insurance status, and clinical needs were controlled for racial and ethnic health care. Disparities dictate funding requirements for public health initiatives for the underserved populations. Furthering social justice and maximizing individual liberties will advance traditional public health goals. Socioeconomic status of communities drives the financing needs for public health initiatives; therefore, burdens of the program must be minimized and identified to reduce pre-existing social injustices. Social benefits, public health programs that stimulate dignified employment, and strengthening of communities are important benefits that should be given high consideration. Public health professionals and health department leaders may not have the capacity to implement all programs that could be beneficial to a target population or community, but advocacy is paramount to improving health. Sufficient data is critical to justify the necessity of the program. I believe that it is our duty as healthcare and public health leaders to remove from policy debates and decision-making any discriminatory procedures or unjustified limitations on personal liberties. Public policy should be based on an ethics perspective and multiple considerations.

References

Bleich, S. N., Jarlenski, M. P., Bell, C. N., & LaVeist, T. A. (2012). Health inequalities: trends, progress, and policy. Annual review of public health33, 7.

Carter-Pokras, O. & Baquet, C. (2002). What is a” health disparity”? Public health reports117(5), 426.

Epstein, A. M., Stern, R. S., & Weissman, J. S. (1990). Do the poor cost more? A multihospital study of patients’ socioeconomic status and use of hospital resources. New England Journal of Medicine322(16), 1122-1128.

Getzen, T. E. (2013). Health economics and financing (5th ed.). Hoboken, NJ: John Wiley and Sons.

Kass, N. E. (2001). An ethics framework for public health. American Journal of Public Health91(11), 1776-1782.

Krieger, N., Chen, J. T., Waterman, P. D., Rehkopf, D. H., & Subramanian, S. V. (2003). Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures-the public health disparities geocoding project. American journal of public health93(10), 1655-1671.

Laureate Education, Inc. (Executive Producer). (2012). Multi-media PowerPoint: Financing public health. Baltimore, MD: Author.

Palmer, N., Mueller, D. H., Gilson, L., Mills, A., & Haines, A. (2004). Health financing to promote access in low income settings—how much do we know? The Lancet364(9442), 1365-1370.

Patrick, D. L., & Erickson, P. (1993). Health status and health policy. Quality of life in health care evaluation and resource.

Shi, L., & Singh, D. A. (2011). The nation’s health (8th ed.). Sudbury, MA: Jones & Bartlett Learning.

Dallas’ Renaissance Plan: A Response to the Second Wave of Environmental Justice

Dallas is the seventh largest city in the United States with a population exceeding 1.1 million citizens in the year 2000. Dallas is the fourth largest park system in the United States. The second wave of the environmental justice movement is a concept concerned with urban design, public health, and availability of outdoor physical activities. The upgrade to the 21,526 acres of parkland will amplify the quality of and access to outdoor recreation. The Dallas Park and Recreation Department’s “Renaissance Plan” is a response to  the increased demand of the citizens for new and expanded park facilities, recreation programs, open space areas, and unique recreational amenities. Physical activity is one of the health indicators for Healthy People 2010, and responding to these demands is a step forward of meeting its goals.  Dallas’ wide spectrum of park facilities will provide physical activities that will have positive health outcome to Dallas residents including the low-income population of the Dallas County and contiguous counties. Recognition of environmental exposure affecting economically and politically disadvantaged members of the community gave birth to the first wave of environmental justice movement. In addition to health problems related to environmental exposures, environmental justice (EJ) also cover disparities in physical activity, dietary habits, and obesity among different populations. Disparities on the access of public facilities and resources for physical activity (PA) is an EJ issue that has a negative impact on health among low-income and racial/ethnic minorities (Labilles, 2013). The 2007 cross-sectional study of Taylor et al. suggest an association between disproportionate low access to parks and recreation services (PRS) and other activity-friendly environments in low-income and racial/ethnic minority communities.  The prevalence of lower levels of PA and higher rates of obesity was observed in the minority population, which is a direct outcome of the prevalence of lower levels of PA. These differences violate the fair treatment principle necessary for environmental justice.

The treatment of health conditions associated with physical inactivity such as obesity poses an economic cost of at least $117 billion each year. Physical inactivity contributes to many physical and mental health problems.  The reported 200,000-deaths per year in the US is attributed to physical inactivity, and data from surveillance system indicate that people from some racial/ethnic minority groups experience disproportionately higher rates of chronic diseases associated with physical inactivity. Taylor, Poston, Jones & Kraft (2006) findings, provided preliminary evidence for the hypothesis that socioeconomic status disparities in overweight and obesity are related to differences in environmental characteristics. However, most of the studies had encountered epidemiologic “black box” problem, making it impossible to determine which characteristics of the environment (e.g., density of food service outlets or physical activity resources) may be most important (Labilles, 2013). Ellaway et al. found that body-mass index (BMI), waist circumference, and prevalence of obesity, and greater obesity risk is associated with low area or neighborhood socio-economic status.

References

Behavioral Risk Factor Surveillance System (BRFSS). Atlanta: Centers for Disease Control and Prevention; 2000.Centers for Disease Control and Prevention; 2000.

Ellaway A, Anderson A, Macintyre S. Does area of residence affect body size and shape? Int J Obes Relat Metab Disord. 1997; 21:304-308.

Labilles, U. (2013). Environment Matters: The Disproportionate Burden of Environmental Challenges. PUBH 8115-1 Environmental Health Spring Qtr. Minneapolis: Walden University.

Taylor, W., Floyd, M., Whitt-Glover, M. & Brooks, J. (2007).  Environmental Justice: A Framework for Collaboration between the Public Health and Parks and Recreation Fields to Study Disparities in Physical Activity. Journal of Physical Activity & Health, 4, supp 1, s50-s63.

US Dept of Health and Human Services. Physical activity and health: A report of the Surgeon General. Atlanta: Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion; 1996.

US Dept of Health and Human Services. Healthy People 2010: With understanding and improving health and objectives for improving health (2nd ed). Washington: US Govt Printing Office; 2000.

Wolf AM, Manson JE, Colditz GA. The economic impact of overweight, obesity, and weight loss. In: Eckel R, ed. Obesity Mechanisms and Clinical Management. Philadelphia: Lippincott, Williams, & Wilkins; 2002.

 

 

A Challenge to Public Health Surveillance Interoperability and Clinical Research

The obstacles that impact interoperability of the disease surveillance systems starts with the issue of balance between the public interest in the collection of information and the privacy rights. In theory, properly utilized, surveillance is a fundamental government activity, indispensable in nature (Gostin & Gostin, 2000). The legal complications brought about by the Fourth Amendment prohibition against unreasonable searches and seizures, triggered the social impetus behind HIPAA and the HHS Report. The Fourth Amendment is a constitutional protection against wrongful enforcement of the law on access to private medical records. These offers insight into the growth and development of non-Fourth Amendment protections for medical records privacy, and examines later actions that appear to restrict or undercut these potential medical record protections. The shared goals of both public health surveillance and the protection of health information privacy will encourage individuals to fully utilize health services and cooperate with health agencies. The key to protecting the well-being of the community is the optimum balance between public health activities and privacy protection. This balance is challenged by the enactment and enforcement of current legislation such as the Health Insurance Portability and Accountability Act’s Privacy (HIPAA). The way public health exception of HIPAA Rule was drafted resulted to confusion and put this balance in jeopardy, as well as recognized reluctance to provide information to state and local public health agencies. Wilson (2009) stated that the exception ambiguously defines the role of public health authorities in maintaining the privacy of personally identifiable health information. Incertitude about privacy can be equipoised by initiatives by state and federal policy makers such as the report “Confidentiality of Individually-Identifiable Health Information” issued by the Department of Health and Human Services (HHS).  This report reflected a legitimate interpretation and representation of the best aspects of constitutional and judicial protections of medical records privacy using current innovative technology in health information and communication.

State, local, and tribal public health authorities shares the privacy challenges that are inherent in data sharing. Wilson (2009) stated that, in the process of promulgating the Privacy Rule, HHS recognized the need to inscribe an exception for public health purposes in order to allow authorities at all levels of government to continue to collect, analyze, and use health information that would otherwise be unavailable without prior patient consent. State courts and policy makers have produced some protection for individuals’ medical histories which are characterized more by their diversity and conflicting standards than by the quality of protection. Unfortunately, state laws offer little additional support for medical records protection from law enforcement intrusion, thereby it is paramount for continued collaboration between public health professionals, health leaders and policy makers to focus on needed amendments to protect the interest of both the public, patients and researchers which will then bridge the divide on the interpretation of the law. It is critical to acknowledge that challenge of law- and policy-makers in finding common ground between individual privacy expectations and the communal health authorities’ needs for identifiable health data. The dissemination and use of identifiable health data for public health purposes are typically supported by the public, but it relies on how the government and other entities maintain appropriate privacy and security protections in acquiring the data. It is warranted for the continued improvement on the level of protection afforded to the public and patients by state laws governing medical records privacy. Moral justifications should be considered in establishing firm, consistent set of rules governing law enforcement’s use and exchange of private medical records and data needed in clinical research. The obstacles that forestall data-sharing practices should be assessed and remedied within each jurisdiction. Legal interpretations should be openly discussed to properly develop and implement model policy to strengthen disease surveillance, and increase the efficiency of data-sharing practices between researchers and public health authorities at all levels.

References

Aarestrup, F. M., Brown, E. W., Detter, C., Gerner-Smidt, P., Gilmour, M. W., Harmsen, D., … & Schlundt, J. (2012). Integrating genome-based informatics to modernize global disease monitoring, information sharing, and response. Emerging infectious diseases18(11), e1.

Act, A. (1996). Health insurance portability and accountability act of 1996.Public Law104, 191.

Bernstein, A. B., & Sweeney, M. H. (2012). Public health surveillance data: legal, policy, ethical, regulatory, and practical issues. MMWR Surveill Summ, 30-4.

Carroll, L. N., Au, A. P., Detwiler, L. T., Fu, T. C., Painter, I. S., & Abernethy, N. F. (2014). Visualization and analytics tools for infectious disease epidemiology: A systematic review. Journal of biomedical informatics.

Chan, M., Kazatchkine, M., Lob-Levyt, J., Obaid, T., Schweizer, J., Sidibe, M., … & Yamada, T. (2010). Meeting the demand for results and accountability: a call for action on health data from eight global health agencies. PLoS Med7(1), e1000223.

Chowdhary, S., & Srivastava, A. (2013). Cloud Computing: A Key to Effective & Efficient Disease Surveillance System. In Int. Conf. on Advances in Signal Processing and Communication. ACEEE (Lucknow).

El Emam, K., Hu, J., Mercer, J., Peyton, L., Kantarcioglu, M., Malin, B., … & Earle, C. (2011). A secure protocol for protecting the identity of providers when disclosing data for disease surveillance. Journal of the American Medical Informatics Association18(3), 212-217.

Gostin, L. O., & Gostin, L. O. (2000). Public health law: power, duty, restraint (Vol. 3). Univ of California Press.

Gostin, L. O., Hodge, J. G., & Marks, L. (2002). The Nationalization of Health Information Privacy Protections. Tort & Insurance Law Journal, 1113-1138.

Hodge Jr, J. G., Torrey Kaufman, J. D., & Jaques, C. (2012). Legal Issues Concerning Identifiable Health Data Sharing Between State/Local Public Health Authorities and Tribal Epidemiology Centers in Selected US Jurisdictions.

Kulynych, J., & Korn, D. (2003). The New HIPAA (Health Insurance Portability and Accountability Act of 1996) Medical Privacy Rule Help or Hindrance for Clinical Research? Circulation108(8), 912-914.

Labilles, U. (2014). Obstacles of Disease Surveillance Interoperability: A Challenge to Public Health. (Unpublished, PUBH-8270-2. Health Informatics and Surveillance. 2014 Spring Qtr. WK11Disc) Walden University, Minneapolis.

Lenert, L., & Sundwall, D. N. (2012). Public health surveillance and meaningful use regulations: a crisis of opportunity. American journal of public health, 102(3), e1-e7.

Office for Civil Rights, H. H. S. (2002). Standards for privacy of individually identifiable health information. Final rule. Federal Register67(157), 53181.

Van Der Goes Jr, P. H. (1999). Opportunity Lost: Why and How to Improve the HHS-Proposed Legislation Governing Law Enforcement Access to Medical Records. University of Pennsylvania law review, 1009-1067.

Wilson, A. (2009). MISSING THE MARK: THE PUBLIC HEALTH EXCEPTION TO THE HIPAA PRIVACY RULE AND ITS IMPACT ON SURVEILLANCE ACTIVITY. HOUS. J. HEALTH L & POL’Y131(156), 131.

Middle East Respiratory Syndrome (MERS) and Global Disease Surveillance System

The first confirmed case of Middle East Respiratory Syndrome (MERS) in the United States raised concerns about the rapid spread of the disease if there is no disease surveillance system in place. MERS infection was first reported in Saudi Arabia in 2012. MERS morbidity and mortality is alarming in which its clinical features resembles severe acute respiratory syndrome (SARS) with the mortality rate of approximately 60% for those who was hospitalized with severe acute respiratory condition. The federal and state health officials released the information about the first U.S. MERS case on May 2, 2014 which is an example of the importance of disease surveillance in the public health system. The patient is a health care provider who flew from Saudi Arabia’s capital Riyadh to the United States, with a stop in London. He took a bus to Indiana after landing in nearby Chicago. On April 27, he began experiencing shortness of breath, coughing, and fever. Medical staff members who came into direct contact with this patient was placed in full isolation at Community Hospital in Munster, then were taken off duty and put in temporary home isolation. MERS have no known treatments, and symptoms can take up to 14 days to occur. The exposed medical staff members will be allowed back to work after the incubation period ends and their laboratory results are confirmed to be negative for the virus. The most important factor that is needed to be considered is the probability of rapid situational changes on the progression of human-to-human transmission. Anticipating this probability will be dependent upon the quality of surveillance systems to monitor symptomatic and mild infections. These include the network structure of infections within the MERS-CoV clusters. Understanding the pandemic potential of this virus is paramount to saving lives, therefore, it is important to acknowledge the significance of the necessary requirements for a sustained globalized environment in which the continued commitment of richer countries to make it a moral obligation to help institute required reforms, policies, structures and systems required for public health and disease surveillance. It is important to develop counter-measures in the event MERS-CoV starts evolving, and mutate that will make it easier to infect humans. Mathematical epidemiologists use reproduction number (R0) to measure the average number of infections in a fully susceptible population caused by one infected individual. In this scenario, R0 of this virus will need to be increased which will then pose a relevant challenge for estimating R0 from a series of outbreaks distributed through time. In a bioterrorism standpoint, it is critical for investigators to explore the probability for this virus to be mutated in a laboratory setting. Enhanced surveillance is needed to trace active contacts, as well as vigorous monitoring of the MERS-CoV animal hosts and transmission routes to human beings within and beyond the target population. As long as the transmission properties remain small, the rapid identification, and isolation of cases with a basic R0 will keep human-to-human transmission under control. Early detection of milder, and asymptomatic cases is paramount for the reduction of case fatality rate, since mortality rate of this disease is related to late stage diagnosis and comorbid medical conditions. Globalization has its positive and negative impacts, making the world smaller and increase its vulnerability to infectious disease outbreak. Renewed commitment to public health, and strong international partnerships are essential to strengthen national and international cooperation in infectious disease prevention and control.

References

Bauch, C. T., & Oraby, T. (2013). Assessing the pandemic potential of MERS-CoV. The Lancet382(9893), 662-664.

Breban, R., Riou, J., & Fontanet, A. (2013). Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk. The Lancet382(9893), 694-699.

CDC – Coronavirus – Middle East Respiratory Syndrome – MERS-CoV. (n.d.). Retrieved from http://www.cdc.gov/coronavirus/mers/

Heymann, D. L., & Rodier, G. R. (1998). Global surveillance of communicable diseases. Emerging infectious diseases4(3), 362.

Labilles, U. (2014). Middle East Respiratory Syndrome (MERS): The World is Getting Smaller. (Unpublished, PUBH-8270-2. Health Informatics and Surveillance. 2014 Spring Qtr. WK9Assgn) Walden University, Minneapolis.

Man treated for deadly MERS virus in Indiana improving: state … (n.d.). Retrieved from http://www.reuters.com/article/2014/05/04/us-usa-health-mers-idUSBREA4208620140504?feedType=RSS

Man treated for deadly MERS virus in Indiana improving: state … (n.d.). Retrieved from http://www.orlandosentinel.com/news/nationworld/sns-rt-us-usa-health-mers-20140502,0,6981423.story

WHO calling in the experts on MERS-CoV | Hospital Infection … (n.d.). Retrieved from http://hicprevent.blogs.ahcmedia.com/2013/07/08/who-forms-emergency-committee-to-prepare-for-mers-cov-emergence/

“Personal Health Records (PHR) and Health Information Exchange (HIE) in Managing Regional Multi-Site Medical Specialty Practice”

The true, meaningful use of personal health records (PHR), and  health information exchange (HIE) between regional sites or multi-site specialty practice could amplify coordination and efficiency for higher quality and  patient-centered care. PHR and HIE have been advocated as key new components in the effective delivery of modern health care. What is the impact of PHR and HIE to healthcare system? How can sharing health information between regional sites or multi-site specialty practice bridge the communication gap?  What is the role of specific-disease surveillance system in enhancing the management and delivery of quality of care? The effective use of cancer-related information aggregated from evolving health communication and information technology can help identify disease cluster such as the incidence of skin cancer in a geographic area which could improve communication strategy on a population wide basis. The processes of health communication and supportive health information technology infrastructure can influence patients’ health decisions, health-related behavior, and health outcomes. These make health communication and health information technology play an increase central role in health care delivery and public health. HINTS data could help a regional manager harness the appropriate communication channel to coordinate between facilities, and to identify barriers to the use of health information across community. Gauging the target group’s attitudes, regarding perceptions of health-relevant topics such as cancer screening will help develop more effective communication strategies. For example, a marked increase in the incidence rate of non-melanoma skin cancer (NMSC) based on a comprehensive surveillance system could help Mohs Micrographic Surgery facilities coordinate with dermatologists and dermato-pathologists. HINTS data can help refine information age health communication theories, and offer unique recommendations for managers, communication planners and researchers in their common aim to reduce the population cancer burden through effective, evidence-based, and patient- or public-centered communication (Hesse et al., 2006; Hesse et al., 2005; Nelson et al., 2004). The concept that captures an interactive phenomenon such as shared decision-making (SDM) utilized in concert with HINTS data recommendations will improve clinicians and patients communication. Kasper, Légaré, Scheibler & Geiger (2012) asserted that the complexity of challenges physicians have to face in critical decision making, can be alleviated by outsourcing parts of the information and decision making process to other health or medical professionals to provide optimal conditions for communication in the physician patient dyad.

References

Finney Rutten, L. J., Davis, T., Beckjord, E. B., Blake, K., Moser, R. P., & Hesse, B. W. (2012). Picking up the pace: changes in method and frame for the health information National Trends Survey (2011–2014). Journal of health communication17(8), 979-989.

Hesse, B. W., Nelson, D. E., Kreps, G. L., Croyle, R. T., Arora, N. K., Rimer, B. K., . . . Viswanath, K. (2005). Trust and sources of health information: The impact of the Internet and its implications for health care providers: Findings from the first Health Information National Trends Survey. Archives of Internal Medicine, 165, 2618–2624.

Hesse, B. W., Moser, R. P., Rutten, L. J. F., & Kreps, G. L. (2006). The health information national trends survey: research from the baseline. Journal of Health Communication11(S1), vii-xvi.

Kasper, J., Légaré, F., Scheibler, F., & Geiger, F. (2012). Turning signals into meaning–‘Shared decision making’meets communication theory. Health Expectations15(1), 3-11.

Labilles, U. (2014). The Role of Disease-specific Surveillance and Health Information Exchange (HIE) in Managing Regional Multi-site Medical Specialty Practice. (Unpublished, RSCH-8100H-2. Research Theory, Design, and Methods. 2014 Spring Qtr. WK7Assgn) Walden University, Minneapolis.

Nelson, D. E., Kreps, G. L., Hesse, B. W., Croyle, R. T., Willis, G., Arora, N. K., . . . Alden, S.
(2004). The Health Information National Trends Survey (HINTS): Development, design,
and dissemination. Journal of Health Communication, 9, 443–460.

Office of Disease Prevention and Health Promotion. (2010). Healthy People 2020. Retrieved
from http://www.healthypeople.gov/2020/default.aspx

Scholl, I., Loon, M. K. V., Sepucha, K., Elwyn, G., Légaré, F., Härter, M., & Dirmaier, J. (2011). Measurement of shared decision making–a review of instruments. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen105(4), 313-324.

Viswanath, K. (2005). Science and society: The communications revolution and cancer control. Nature Reviews Cancer, 5, 828–835.

Wen, K. Y., Kreps, G., Zhu, F., & Miller, S. (2010). Consumers’ perceptions about and use of the internet for personal health records and health information exchange: analysis of the 2007 Health Information National Trends Survey.Journal of medical Internet research12(4).

“What the Patterns Tell Us” Socioeconomic Status and Health

Fifty years ago, President Lyndon Johnson began his quest for a more just and honorable America with the passage of the Civil Rights Act of 1964, passed the Voting Rights Act of 1965 and the Fair Housing Act of 1968.  This week, President Barack Obama joined three former Presidents delivered remarks at the Civil Rights Summit at the Lyndon B. Johnson Presidential Library and Museum, and acknowledged racism has hardly been erased and that government programs have not always succeeded. Let us talk about socioeconomic and racial/ethnic disparity patterns in public health. What the patterns tell us? In Europe, the presence of detailed socioeconomic information in routine health data has facilitated the monitoring of socioeconomic patterns in diverse health indicators (Braveman, Cubbin, Egerter, Williams &  Pamuk, 2010). This socioeconomic information gave Public health professionals and researchers the ability to compare health of socioeconomically disadvantaged population with health differences among middle-class subgroups and, potentially, comparisons with the wealthy.  Braveman et al. (2010) gave emphasis on Europe’s data collection in contrast with routine the routine public health statistics in the United States.  Health difference across groups defines by socioeconomic factors have been examined less frequently. It was further noted by the study that routine health reporting should examine socioeconomic and racial/ethnic disparity patterns, jointly and separately. According to Collins (2004) “race and ethnicity are poorly defined terms that serve as flawed surrogates for multiple environmental and genetic factors in disease causation, including ancestral geographic origins, socioeconomic status, education and access to health care. Research must move beyond these weak and imperfect proxy relationships to define the more proximate factors that influence health” (para. 1).

Health disparities in many instances will hardly to do with genetics, but more directly associated in socioeconomic status (SES), access to health care, education, social marginalization, discrimination, culture, stress, diet and other factors. SES is one of the strongest and most consistent predictors of morbidity and mortality. As a complex phenomenon, the impact of SES on disease makes its definition and measurement of vital importance. SES is typically measured by determining education, income, and occupation (Winkleby, Jatulis, Frank & Fortmann, 1992). The Farquhar et al study is the only U.S. study on the associations between separate SES dimensions and risk factors or disease outcomes (Winkleby et al., 1992).  In the Farquhar et al. study (1985): Subjects aged 25 to 64 were drawn from the two control cities of the Stanford Five-City Project, a communitywide cardiovascular disease intervention study that contains data from four separate cross-sectional surveys, conducted from 1979 to 1986. Participants who were unemployed (n = 98), students (n = 130), or retirees (n = 146) were excluded because they had no occupation that could be ranked (Winkleby et al., 1992, p. 816).  Associations between one measure of SES and one risk factor, morbidity, or mortality in other studies have found that education is more strongly associated with disease than income or occupation.  One of the most complete studies of mortality differentials (Kitagawa et al., 1973) found “lower SES groups exhibited higher rates of all-cause mortality than did higher SES groups, irrespective of whether education, income, or occupation was used as the measure of SES” (p. 819). Lower levels of education are associated with hypertension, cigarette smoking, high cholesterol, cardiovascular disease (CVD) morbidity and mortality. According to Winkleby et al.,  there are no SES measure that is universally valid and suitable for all populations. The study noted  “if economics and time dictate that a single parameter be chosen, and if the research hypothesis does not dictate otherwise, the conclusion is that higher education, rather than income or occupation, may be the strongest and most consistent predictor of good health” (p. 819).

References

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Berger, M. & Leigh, J. (1989). Schooling, self-selection and health. J Hum Res. 24, 433-455.

Civil Rights Summit. (n.d.). Retrieved from http://www.civilrightssummit.org/ Chicago: Civil Rights Summit, http://www.civilrightssummit.org/ (accessed April 12, 2014).

Dyer, A., Stamler, J., Shekelle, R. & Schoenberger, J. (1976). The relationship of education to blood pressure: findings on 40,000 employed Chicagoans. Circulation. 54, 987-992.

Helmert, U., Herman, B., Joeckel, K., Greiser, E. & Madans, J. (1989). Social class and risk factors for coronary heart disease in the Federal Republic of Germany: results of the baseline survey of the German Cardiovascular Prevention Study. J Epidemiology Community Health. 43, 37-42.

Hypertension Detection and Follow-up Program Cooperative Group. Race, education and prevalence of hypertension. (1977). Am J Epidemiology. 106, 351-361.

Jacobsen, B. & Thelle, D. (1988). Risk Factors for coronary heart disease and level of eduvation. Am J Epidemiology. 127, 923-932.

Kitagawa, E. & Hauser, P. (1973). Differential mortality in the United States: Study in socioeconomic epidemiology. Harvard University Press, Cambridge, Mass.

Labilles, U. (2013). What the Patterns Tell Us: Socioeconomic Status and Health  (Unpublished, PUBH 8115-1 Wk6 Discussion, Social Behavioral and Cultural Fact in Public Health Spring Qtr.) Walden University, Minneapolis.

Millar, W. & Wigle, D. (1986). Socioeconomic disparities in risk factors for cardiovascular disease. Can Med Assoc J. 134, 127-132

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Socioeconomic status and health: … preview & related info … (n.d.). Retrieved from     http://www.mendeley.com/catalog/socioeconomic-status-health-education-income-occupation-contribute-risk-factors-cardiovascular-disea/

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Major Trends in Genomic Research and Development: Emerging Challenge to Public Health and Global Security

Shortly after I heard about the shooting at Fort hood on Wednesday, it again reminded me about the November 2009 massacre when Army Maj. Nidal Malik Hasan opened fire, killing 13 people and injuring 32. The first question that crossed my mind—is this another terrorist attack? Three days after the April 15, 2012 Boston marathon bombings, President Barack Obama travelled the city and reassure us as a nation to keep our spirit strong. The President stated “We carry on. We race. We strive. We build and we work, and we love, and we raise our kids to do the same. And we come together to celebrate life and to walk our cities and to cheer for our teams when the Sox, then Celtics, then Patriots or Bruins are champions again, to the chagrin of New York and Chicago fans”. This again assert the reality, that after the attack of 9/11 our lives will never be the same again. The increasing recognition that advances in biology is the center of current concerns about the heightened probability of genetics in facilitating the development of a new generation of biological weapons. The scientific and security communities should increase their vigilance on the misuse of genomic data and the ongoing trend of revolution on biology (Labilles, 2013b).  Advances in Genomics may have a significant impact to public health, but serious concerns have been raised about the consequences of the misapplication of this field for hostile purposes. Therefore, it is critical for the continued development of sophisticated analytic techniques to better distinguish anomalies from baseline data. Likewise, combined expertise amongst systems enhance early detection performance for detection of infectious diseases. Professor Thomas D. Cabot of Harvard University has said: “A world in which these capabilities are widely employed for hostile purposes would be a world in which the very nature of conflict had radically changed.” Labilles (2013c), we need to be aware of the implications of programs such as the Free Trade Agreement (FTA), and the need of strict surveillance of the methods and what is being traded between boundaries” (para.3). Our understanding of the brain and human behavior is reaching the point at which precise manipulation for beneficial reasons is clearly feasible. The information presently available has become widely used for military purposes, and there will be knowledge available for misuse, and there will be some willing to misuse it. The line of differentiation between chemical and biological weapons is getting thinner as the genomics revolution continuous.  An individual intentionally infected by Variola major and cross the border will be a deadly moving biologic weapon. This will cause high mortality, public panic and social disruption (Labilles, 2013b, p. 2). The terrorists’ main goal is always to challenge Americans’ sense of safety and confidence, a small chemical, biological, radiological, or nuclear (CBRN) attack could be successful.

According to Richard (2000), highest estimates of the Central Intelligence Agency (CIA) indicate that as many as 100,000 people may be trafficked into the U.S. each year. Modified traditional agents targeted at specific physiological processes can be carried or injected to any individuals estimated to be trafficked into the United States annually. The office of transnational Issues of the US CIA issued a bleak warning in the late 2003 about the future of biological weapons. The report, titled The Darker Bioweapons Future, argued “growing understanding of the complex biochemical pathways that underlie life processes have the potential to enable a class of new, more virulent biological agents engineered to attack distinct biochemical pathways and elicit specific effects” (Wheelis & Dando, 2005).  The report cited of specific examples of new biological weapons and noted about the effects of some of these engineered biological agents could be worse than any disease known to man.

The CIA estimated prevalence of human trafficking vary widely both by year and by the source, with no particular trend (Hopper, 2004, p. 125). A free and open society like the U.S. will always be tested by people who hated the kind of freedom we inherited from our founding fathers. While lethal chemicals are easy to acquire, getting large quantities, and weaponizing are difficult; biological agents can be acquired in nature or from medical supply houses. Like cyberthreats, biothreats are relatively inexpensive compared to explosive, nuclear, and chemical weapons. Both cyber and biothreats can replicate themselves and spread again in their respective cyber and physical borders (Rosen, 2011). To improve psychological profiling of terrorist groups and to develop better theories regarding the roots of terrorism, the need of scientific methodology application must be recognized. It is essential to be informed on the four biosecurity trends in order to avert the concept of militarization of biology, and focus on the potential for hostile manipulation of the human nervous system.

  1. Chemical, biological, and the manipulation and misuse of Emerging Infectious Disease: There is an unequivocal distinction between terrorism with chemical and biological (CB) materials, and terrorism with chemical and biological weapons. Rosen & Lucey (2001): Terrorism with CB materials deals with the use of any toxic substance or pathogen in pursuit of certain goals. Terrorism with CB weapons refers to the use of warfare agent that is a toxic chemical designed, developed and selected by the military to support specific missions laid out in the military doctrine of a state. This distinction highlights the deeper significance of the 1995 sarin attack in the Tokyo underground: for the first time a terrorist organization turned to a warfare agent (p. 172). Unknown potential threats of the emergence of dual-use technologies such as synthetic biology and nanotechnology pose additional security and containment challenges.  Nanoscale-manipulated biological agents evading current detection capabilities and the unpredictable dissemination patterns of synthetic microorganisms is a major challenge. As a proactive posture to a rapidly changing global environment, the US National Strategy for Countering Biological Threats is emphasizing prevention while continuing to support the national preparedness goals and response/recovery capabilities. The study Perkins & Nordmann (2012) aim to enhance the collective capability of the United States and the international community to address emerging health security threats. The study emphasized the need to increase our knowledge of health effects of various types of nanomaterials, and how to assess, control, and prevent harmful exposure, taking into consideration the numerous gaps that currently exist with regard to the distinct behavior of nanoparticles compared to the same chemical or material at “macro-scale”.
  2. Mass-casualty Terrorism: A large scale bio-terrorist (BT) disaster would create a public health disaster in which the number of victims would exceed existing health care resources. It is an intentional disaster with the objective of causing fear, illness and death. The study of the Committee on Research and Development for improving Civilian Medical Response to Chemical and Biological Terrorism Incidents—suggest that in most cases, the United States will have some or little capability for BT mass casualty management, and triage at four levels of medical care. The four levels of medical care are local responders, initial treatment facilities, state, and federal. At the time of the study, existing conventional management and triage protocols for disasters is not fit for casualty management needs for a large-scale BT event. The three phases of management and triage process after BT event are discovery phase, epidemiological analysis phase, and lateral decision-making/triage management phase. The discovery phase of a BT event will most likely occur in an emergency department, doctor’s office or clinic (Burkle, 2002). Assumptions about the nature of the event will initially guide triage and management during the discovery phase. Syndromic surveillance is an essential component of the discovery phase base on signs and symptoms and supporting public health information. The early clinical manifestations of disease caused by most BT agents could be non-specific, or certain syndromes would be a characteristic of a potential BT attacks. Awareness of these syndromes by practitioners is significant to early discovery of an exposure. The syndromic events are a perfect determinant for surveillance to control the spread of an infectious pathogen. Agent-based models (ABM) can be used to establish structured epidemiological description of a population or infected individuals and local interaction. Agent-based Model (ABM) algorithm allows one to keep the number of active (Exposed and Infectious) agents low at the beginning of the epidemic process and thus decreases the computational burden. As the number of activated agents increases, and increases the amount of required computational resources. Using ABM, an individual is considered to be in one of the following four states: (1) Susceptible (can contract the disease given the contact with an infected individual), (2) Exposed (contracted the diseases, but is in a latent state without showing symptoms), (3) Infectious (showing symptoms and capable of infecting others), and (4) Recovered (obtained permanent immunity and cannot infect others). When an infected individual passes infection to a Susceptible individual, a corresponding susceptible agent is activated (Bobashev et al., 2007). Epidemiological analysis phase is of paramount importance in recognition of an epidemic caused by terrorism. An epidemiological investigation must occur in tandem with case definition development, once an abnormality is evident, whether it is a single or unexplained disease cluster, or mass illness event. The visual representation of a quantitative evaluation using epidemic curves will be initially useful to obtain answers to questions concerning origin, propagation, incidence, prevalence and modes of transmission. Details on unique characteristics of the BT agent can also be achieved through curve analysis. In this phase, mathematical models of disease is also essential to link the biological process of transmission and the emergent dynamics of infection at the population level. At the minimum, a team effort is significantly will dictate the success of lateral decision-making/triage management phase. Emergency managers (local and FEMA), Department of Justice (FBI), political authorities (mayor, governor), technical experts, tactical field scientists with expertise in epidemiology and infectious disease) will make up the lateral decision making at the local level. At the hospital level, the triage officer will be composed of pharmacists, infectious disease specialists, administrators, pulmonary care technicians and auxiliary hospital personnel.
  3. Gross Violations of the Biological and Toxin Weapons Convention (BTWC):  The 1972 Biological and Toxin Weapons Convention was formed as a result of the end of the Cold War and the first Gulf War. The gross violations of BTWC is of great concern, and had been violated for the two decades following its entry into force that led to a six year international negotiations of a compliance protocol. A number of BTWC signatories are suspected to be involved in illegal activities. President George W. Bush withdrew from these negotiations in 2001 and has declared BWC to be “inherently unverifiable”.

Dramatic Advances in Biotechnology: In 1999, the biotechnology industry in the United States doubled in size, and its globalization is being driven not only by national decisions, but also by biotechnology firms. Growing apace in the knowledge and techniques in genomics, and genetics, giving scientists the ability to locate specific genes and identify their associated genes through genetic sequencing. Bio-informatics have supported the collection and dissemination of vast quantities of data, making it easier for knowledge and technology to be misused. Growing international subcontracting, transfer of knowledge to other entity could be the first probable breach enabling terrorists to develop new forms of bioengineered weapons to augment or replace existing capabilities. Detection, mitigation and remediation from exposure to agent strains could become much more difficult if they were modified to hide telltale signatures (Rappert, 2003). In the mid-1990, Russian scientists made detection tests for anthrax ineffective through genetic engineering techniques.  The impact of biotechnology on the threat of biological warfare is graphically represented in figure 1 (Petro et al., 2003, p. 163). The graphical representation of figure 1 depicts the timeline of relative threat level presented by traditional, genetically modified traditional and advanced biological agents. Dramatic advances in biotechnology will lead to a new class of advanced biological warfare (ABW) agents developed to bring forth novel effects. Biological research will bring new agents and delivery system that will provide a multiplicity of new options, expanding the paradigm of biological warfare.The implications of these four trends led to a re-conceptualization of the bio-terrorist threat away from misplaced analogies to nuclear or chemical weapons, and towards placing the threat in the context of the public health measures needed to combat disease (Chyba & Greninger, 2004).

Contributing Factors

The individual, interpersonal and environmental contributing factors that open the probability of biological and chemical threats could be trace to the lack of verification measures and the widespread availability of the general materials, equipment and biological knowledge necessary for weapons development. BTWC has no criteria to differentiate offensive from defensive development, production or stockpiling activities. Unless otherwise justifiable, all biological agents and toxins are banned, but it has long been a cause of concern of reported violation of BTWC by some member State Parties and countries. It has been a topic of much debate about the feasibility that individuals, sub-state groups, terrorists the capacity to develop bio-weapons. A genetically engineered infectious agent could have a probable effective means of systematic dispersal by trafficking an individual physically carrying a deadly agent or infected with deadlier viral strain that rapidly spread to a target population. With existing knowledge and technology, studies shows that terrorists or anyone can make biological weapons without obtaining a natural virus. American scientists Jeronimo Cello and colleagues at the State University of New York at Stony Brook synthesized a polio genome from scratch by stringing together commercially available strands ofDNA purchased over the Internet in accordance with the map of the RNA polio genome, which is published onthe Internet (Selgelid, 2007). Through gene splicing, the survivability of a bacterium across a range of environmental conditions could be improved. The ease to conceal legitimate biological research further energize other countries, and terrorist organizations to continue to pursue biological warfare.

Prevention

The theoretical framework of emerging biotechnologies will lead to the development of new biological agents. Technologies developed across multiple disciplines in the biological sciences will have a profound global impact and concurrently have the potential to revolutionize biological warfare by facilitating an entirely new class of fully engineered agents referred to as advanced biological warfare (ABW) agents (Petro et al., 2003). The Biological Weapons and Toxins Convention (BWTC) have done little to prevent foreign bio-weapon programs. Compounded by the possibility of terrorist organizations’ intention or capability to acquire bio-weapons—bioterror threat represents a significant challenge to our leaders, and agencies responsible for directing biodefense efforts. Prevention will be dependent upon counter proliferation, environmental detection, and medical countermeasures. The aim of the creation of a national biodefense strategy is to focus largely on addressing existing threats posed by a select group of naturally occurring pathogens and toxins. Petro et al. noted that agents traditionally associated with biological warfare likely will remain the predominant threat over the next 10 years. The implications of current and emerging biotechnologies on development of new biological agents should be considered and factored into any long term biodefense strategy (p. 161).

Public Health Policy Implications

 Dual-use research that can be used for both good and harmful purposes is plagued with ethical challenge and debates on the needs of relevant policy developments. The growing debate on “the dual-use dilemma” in life sciences research stressed the essential need of safety and security guidelines on biosecurity. Life sciences community and the security community share the common goal of protecting our Nation’s human, animal, plant and environmental health. These communities recognize this inherent tension between the need to protect the conduct of biological research from unnecessary restrictions, and mitigate potential threats to the greatest extent possible. I believe that a comprehensive review of U.S. terrorism policy, organizational structure, and preparedness are essential to respond with the shifting nature of biological research impacting existing offensive capability, and scientific advances that will be more available and applicable over the next 5 to 25 years. The National Research Council (NRC) recommended the increased education of the scientific community about the dual-use dilemma. The recommendations include that the significance of the role of institutional biosafety committees. The expanded role of institutional biosafety committees must include the function to review of research proposals for dual-use risks including environmental dangers. NRC recommendations also include self-governance of the scientific community as opposed to governmental censorship in matters related to publication of dual-use research findings.  The National Science Advisory Board for Biosecurity (NSABB) was established to provide guidance to the government regarding the oversight of dual-use research. The public health community, law and policymakers, and society in general need to address a series of critical choices (Hodge Jr., 2002). The critical and most important choice are not to decide where the power to protect the health public lies or which level of government has the primary power to act, but to decide the center of leadership during a bioterrorism event.

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Figure 1

PreGenomic