All posts by Ulysses Labilles, DMD, PhD

”Every dream comes from a speck of hope. It is through hope where we gain our strength to make a change."

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.

A Very Simple Concept of Peace

Last Christmas Eve, I received a wonderful and encouraging letter from the President. My daughter Abby opened it with excitement, and after reading his letter, she asked if she could keep it. We may all have something to say regarding what are happening around us, and we may all have our default someone to blame, but in the eyes of a growing citizen of this great country of ours, what is paramount is learning respect and love for our country. In the eyes of a child, a leader is someone who will make her/his place in this world a better place to live. They do not know about political parties, politicians at each other’s throat, but just a very simple concept “Peace.” After watching the movie “Unbroken” last night, she told me that she need to write the President a thank you letter. I told her that I already did via e-mail. Then she said, I need to thank him too since like Louis in the movie, he does not give up to something what is right. Enjoy what is left with the Holiday Season everyone.

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 Summer Phenomenon

For 26 days in 2011, every place in Texas showed higher concentrations of lung-damaging ozone than allowed by federal air-quality standards, especially in Dallas. The federal standard set in 2008 is 75 parts per billion. The spike in ozone which is particularly a summer phenomenon is exacerbated by trucks carrying drilling materials that emit nitrogen oxides, and natural gas escaping from pipelines or storage tanks that emit volatile organic compounds, or VOCs. Known ozone “precursors” such as nitrogen oxides and VOCs can react with each other to form ozone when aided by sunlight. The most difficult environmental issue North Central Texas face today is air quality. Dallas Forth Worth (DFW) region meets the standard for five of six criteria air pollutants defined by the EPA. The six pollutants are carbon monoxide, lead, nitrogen dioxides, ozone, particulate matter, and sulfur dioxide. The only air pollutant for which DFW do not meet the National Ambient Air Quality Standard is the ozone. In hot summers, combination of nitrogen dioxides and VOCs and concentrations of traffic and industry, Dallas is an ideal incubator for the creation of ground-level ozone.

Discussion

Under the Clean Air Act, ozone pollution has long been regulated because of its tremendous hazards to the public. Under the Clean Air Act, ozone poses tremendous hazards to the public health and the environment. High ozone levels lead to respiratory distress and disorders; decreased lung function; increases in the emergency room visits and sick days. To address the serious problem of ozone, the Clean Air Act provides a multi-step process for ensuring that all areas of the country achieve acceptable ozone levels. EPA establish nationwide air quality standards for ozone (called National Ambient Air Quality Standards), which are required to be strong enough to protect public health with an adequate margin of safety. The next step, EPA designate areas of the country that meet the standards, and those who do not. The last step, requiring states to submit plans for achieving and maintaining compliance with EPA’s ozone standards — with especially strict requirements for areas that currently do not meet the standards. The U.S. Environmental Protection Agency (EPA) updated its ozone air quality standards in March 2008. The EPA towards the end of 2012 promised the DFW residents for stronger protections against the harmful public health and environmental impacts of ground-level ozone. The agency announced on January 7, 2012 about its determination that Wise County, Texas contributes to high ozone levels in nearby Dallas-Fort Worth. This action required polluters in Wise County  to do their fair share to reduce ozone levels in Dallas-Fort Worth. Wise County was included in the DFW ozone designation due in large part to the emissions of nitrogen oxides, and volatile organic compounds from a recent boom in oil and gas production in the area. According to the Technical Support Document (TSD), the final area designations in the Dallas-Fort Worth (DFW) area for the 2008 ozone national ambient air quality standards are based on several factors and indicators. The population density and degree of urbanization were analyzed. TSD stated: EPA evaluated the population and vehicle use characteristics and trends of the area as indicators of the probable location and magnitude of non-point source emissions. These include ozone precursor emissions from on-road and off-road vehicles and engines, consumer products, residential fuel combustion, and consumer services. Areas of dense population or commercial development are an indicator of area source and mobile source NO2 and VOC emissions that may contribute to ozone formation that contributes to nonattainment in the area. Rapid growth in population or vehicle miles traveled (VMT) in a county on the urban perimeter signifies increasing integration with the core urban area and indicates that it may be appropriate to include such perimeter area(s) as part of the nonattainment area.

Conclusion

It is very important to recognize the effect of ozone to a population, especially adults and children who are already had chronic respiratory diseases such as asthma. Exposure may compromise the ability of the body to fight respiratory infections. Bell et al. (2004) a multisite time-series study of 95 large US urban communities throughout a 14-year period  found that widespread pollutant such as ozone adversely affects public health.

References

Area Designations for the 2008 Ozone National Ambient Air … (n.d.). Retrieved from http://www.epa.gov/airquality/ozonepollution/designations/2008standards/documents/R6_DFW_TSD_Final.pdf

Bell, M., McDermott, A., Zeger, S., Samet, J. & Dominici, F. (2004). Ozone and Short-term Mortality in 95 US Urban Communities, 1987-2000. JAMA;292(19):2372-2378. doi:10.1001/jama.292.19.2372.

Dallas Fort-Worth Breathes Easier Following EPA’s Decision … (n.d.). Retrieved from http://blogs.edf.org/energyexchange/2013/01/16/dallas-fort-worth-breathes-easier-following-epas-decision-on-wise-county-ozone-petitions/

Green Dallas…building a greener city! (n.d.). Retrieved from http://www.greendallas.net/air_quality.html

Labilles, U. (2013). Obstacles of Disease Surveillance Interoperability: A Challenge to Public Health. (Unpublished,  PUBH-8115-1/HUMN-8115-1-Soc Behave Cultural Fact in Public Health. 2013 Spring Qtr. WK7Disc) Walden University, Minneapolis.

 

 

 

 

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/

Bridging the Technology Gap and Geographic Divide

This morning, I attended a webinar on the transitioning to ICD-10 CM and its impact on Public Health Surveillance presented by Peter Hicks of Centers for Disease Control and Prevention (CDC). While its benefits and challenges were discussed, the question to ask is the cost implications of the transition. Another question to ask is its compatibility to existing health information technology. I believe at this point, we need to embrace its advantages, and explore the merging of this initiative on its potential for higher quality and patient-centered care. Setting this topic aside for future dialogue, let me follow-up last week’s discussion on the true, meaningful use of personal health records (PHR), and health information exchange (HIE). In this milieu, let me discuss the promise of telehealth on higher quality and patient-centered care. The geographic separation between regional multi-site healthcare system in which one site is 32 miles or even 51.4 miles away is no longer a logistic problem using telehealth. The quality of care of the traditional model, where health care takes place when the patient and the provider are together at the same time and place can be amplified by current modern system of healthcare. It is important to acknowledge the importance of modern telecommunications and information technologies in providing management flexibility to providers, administrators and managers. It bridges the geographic separation between the patient-provider and management-staff, and allow us to challenge the notion of location and time. Video conferencing can be used to communicate with the provider, where the patient is located one part of the state and the physician is located at another part, or to show new Mohs technicians to perform cryotomy or frozen section immunohistochemistry. In this model, we can remotely monitor patient’s physical condition. Telehealth in concert with disease-specific surveillance data can assess the need for community outreach to educate and inform about the significance of the intervention.

The ability to capture and transmit images using the internet, teleconsultation can be used as an additional approach to teaching new surgical techniques, unbiased by doctrine or surgeon’s experience, enabling accurate quantitative criteria to evaluate the effectiveness of surgical cuts. In the context of cutaneous surgery, whereby contemporary research tools may become one of the criteria in the designing and performing of operations—telemedicine could be an innovative teaching platform presenting systematic pursuit of accurate, optimal cutting patterns and new surgical techniques. This capacity, when used in combination with digital pathology, could offer an alternative method to comply with Clinical Laboratory Improvement Amendments (CLIA) proficiency testing compliance on sharing Mohs slide images with another laboratory to confirm the quality of test of patient frozen section samples. In a multidisciplinary approach, it could bridge the consultation with dermatopathologist on the critical success of a high-quality Mohs surgery program. The dermatopathologist can play a role in quality assurance by reviewing Mohs slides at regular intervals to satisfy the requirement for proficiency testing. Teleconsultation and digital pathology can help assess margins in rare and difficult tumors. Moreover, consultation with dermatopathologist helps in ruling out residual disease or for further immunohistochemistry studies, as well as consultation to assess perineural involvement and uncertain frozen section diagnosis of unusual proliferative lesions. High ground such as remote monitoring of the progress of surgical repairs; we need to acknowledge the challenge in which many of these technologies can impact privacy and security. Telemedicine network structure may have an advantage over competitive hospital- or university-based networks, but the challenge will always be funding and organizational support.

References

Edwards, M. A., & Patel, A. C. (2003). Telemedicine in the state of Maine: A model for growth driven by rural needs. Telemedicine Journal and e-Health9(1), 25-39.

Labilles, U. (2014). Telehealth: Bridging the Geographic Challenge. (Unpublished, PUBH-8270-2. Health Informatics and Surveillance. 2014 Spring Qtr. WK8Disc) Walden University, Minneapolis.

Laureate Education, Inc. (Executive Producer). (2011). Introduction to health informatics and surveillance: Telehealth. Baltimore, MD: Johnson, K. & Speedie S.

Sanders, T. B., Bowens, F. M., Pierce, W., Stasher-Booker, B., Thompson, E. Q., & Jones, W. A. (2012). The Road to ICD-10-CM/PCS Implementation: Forecasting the Transition for Providers, Payers, and Other Healthcare Organizations. Perspectives in health information management/AHIMA, American Health Information Management Association9(winter).

Terry, N. P. (2012). Anticipating Stage Two: Assessing the Development of Meaningful Use and EMR Deployment. Annals Health L.21, 103.

Tilleman, T. R. Optimization of Incisions in Cutaneous Surgery including Mohs’ Micrographic Surgery.