Idea Transcript
Population Health Population health has become a key focus in clinical practice in particular for reaching performance measures for reimbursement. This means that populations are considered in their entirety, as opposed to individuals when deciding on the overall data. While individuals make up the population, the goal is to determine the causes of disease and best treatment options for the majority within a populations vs. individuals. Measurement of key performance or outcome measures can then be a tool for “measuring performance” and deciding on reimbursement. Individual risk factors will always vary. Population health allows for the assessment of key determinants that are likely to affect many people and, therefore, can be prioritized for prevention, control, and process/outcome measurement. Populations versus Individuals For example, smoking has been shown to cause increased risk of lung cancer. However, knowing that the population risk for smokers is 20 times higher than the population risk for nonsmokers does not allow one to say that an individual’s risk of cancer if they smoke is 20 times higher than a non-smoker’s. What the risk says is that groups of individuals who smoke are 20 times more likely to develop lung cancer than non-smokers. The difference is subtle, yet important (Friis and Sellers, 2009). Determinants and Risk Factors Epidemiology science focuses on the causes or determinants of diseases, injuries, or other health states. For infectious diseases, identifying the agent responsible for the disease is important information for designing and implementing control measures to reduce communicability. Although many of the determinants of chronic conditions are behavioral in nature, resulting in a shift in control measures that are used, behavioral factors are also important in infectious diseases. Likewise, infectious agents have been implicated in diseases that may be considered chronic, for example HPV and cervical dysplasias or hepatitis B virus and chronic liver disease. Determinants that increase the probability that disease or health states will develop are called risk factors. The presence of risk factors does not predict that disease will always result but rather identifies the probability that someone might be at risk for developing the health problem. Epidemiological Triangle The classic epidemiology triangle involves a host, an agent, and the environment. Control measures are aimed at interfering with the interactions in order to prevent the spread of disease. The host is the susceptible person that gets the disease. The agent is the source of the infection. It may be a bacterium, a virus, or any other agent that causes illness. The environment represents all of the environmental influences that allow the agent to reach the host. The mechanisms by which these interact will be different for each disease process. However, by identifying the role of each and instituting control measures, the chain can be broken and the disease can be prevented.
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This model works well for infectious diseases (such as influenza, chlamydia, tuberculosis), but does not represent chronic diseases or other health conditions well. The advanced model below was developed to reflect the often complex nature of chronic diseases and conditions that may have multiple causes (rather than a single agent), multiple environmental influences, and affect broad populations. We will be using this advanced epidemiology triangle to identify key influences during our clinical prevention discussion topics on chronic disease states (such as heart disease, COPD, falls, etc). The Advanced Epidemiology Triangle for Chronic Diseases and Behavioral Disorders
Prevention in Public Health Three types of prevention are important in public health. Primary prevention entails preventing the disease or condition before it happens. Examples include health promotion activities that encourage healthy behaviors before a health condition is identified, e.g., exercise to prevent the
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development of heart disease, or adding fluoride to municipal water supplies to prevent dental caries. Secondary prevention is aimed at early detection of a disease or condition so that treatment can begin. Pap smear tests and PSA tests fall within this category. Tertiary prevention is aimed at limiting disability once a disease has already occurred. An example would be physical therapy for a post-polio patient to increase strength and prevent further physical limitations. Epidemic, Pandemic, and Endemic There is some confusion regarding the terms epidemic, pandemic, and endemic. An epidemic is an unusual occurrence of a disease. The incidence or prevalence is higher than would normally be expected. A disease is said to be pandemic when an epidemic occurs on a much larger scale, generally worldwide or over a large region. The epidemic of H1N1 became a pandemic because it reached a global scale very quickly. In contrast, endemic means that a disease is habitually present in a particular region. Many infectious diseases are endemic to certain regions of the globe, resulting in travel alerts aimed at non-indigenous people visiting those areas. For example, malaria is endemic to many tropical regions and cholera is endemic in some countries with poor sanitation. Both malaria and cholera were at one time endemic to the United States, but this is no longer the case.
Sources of Epidemiological Data Providers can access numerous sources to find data pertaining to the epidemiology of health conditions. Before deciding on which source is most appropriate, it is important to know exactly what it is you want to know. Are you interested only in data pertaining to a specific state, such as North Dakota, a country, such as the United States, or are you interested in cross-national comparisons? If you want to know about youth suicide, are you interested in the mortality rate, number of hospitalizations for attempted suicide, or the proportion of adolescents who have considered suicide? Each of these questions can lead you to a different source.
Raw Health Data Raw health data consists of data from the primary source. Examples include birth and death certificates, as well as hospital records and surveys. Other sources include insurance records, clinic records, school health records, and more. Looking at any of these can be very informative
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for understanding complex problems and determining the causes of morbidity and mortality. However, the information can also be overwhelming. If, for example, you want to know how many patients were admitted to hospitals with an underlying condition of asthma, looking at individual health records will only give you an impression of the proportion—you need summary data and data over time to determine whether this is a trend worth addressing. One primary reason for looking at raw health data is to determine completeness of the data. For example, death certificates contain information about whether a death was work-related. However, these data often are incomplete or missing from death certificates. Determining how extensive the problem of missing data is will help you assess the amount of bias that may be present within summary statistics. Summary Health Data Before determining if summary data are useful, it is important to assess their generalizability (or external validity). How well do the data represent the population of interest? If, for example, data are not routinely collected from low income or minority populations or there are systematic errors in recording the data, summary data could be misleading. Summary data generally are comprised of rates and proportions so that they can be compared with previous time periods or other locations, and to describe the population by demographic and other characteristics. In conclusion, chronic diseases are those that typically have a long latency period, meaning they are developed over a long period of time rather than as a result of a single acute exposure. The duration of illness is also typically much longer than an acute illness. The causes are more complex than a single infectious agent. An advanced epidemiology triangle is a great means to briefly organize key factors such as key risk factors that may identify which patients need early screening.
Resources for Epidemiological Data State and federal governments provide access to large amounts of data for epidemiological purposes. One noteworthy example is the North Dakota Department of Health’s flu web site. Visit the flu web site and note the trends. How is this year’s activity in North Dakota different than past years? How does flu activity differ this week from last week? Are there any notable variations in who is getting the flu? http://www.ndflu.com/ Centers for Disease Control and Prevention In the United States, the Centers for Disease Control and Prevention also provide data regarding epidemiological trends. Morbidity and Mortality Weekly Reports is published weekly to describe these trends. You can visit the CDC web site (www.cdc.gov) for additional resources on descriptive epidemiological data. The CDC also provides updates on the nationwide spread of influenza. Visit the link to CDC’s site pertaining to influenza activity.
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http://www.cdc.gov/flu/weekly/summary.htm BRFSS The CDC conducts an annual survey of adults in the U.S. to assess behavioral risk factors. “The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project of the Centers for Disease Control and Prevention (CDC) and U.S. states and territories. The BRFSS, administered and supported by CDC's Behavioral Surveillance Branch, is an ongoing data collection program designed to measure behavioral risk factors for the adult population (18 years of age or older) living in households. The objective of the BRFSS is to collect uniform, state-specific data on preventive health practices and risk behaviors that are linked to chronic diseases, injuries, and preventable infectious diseases that affect the adult population. Factors assessed by the BRFSS include tobacco use, health care coverage, HIV/AIDS knowledge and prevention, physical activity, and fruit and vegetable consumption. Data are collected from a random sample of adults (one per household) through a telephone survey (CDC, 2008).” For more information, visit the BRFSS web site: http://www.cdc.gov/brfss/technical_infodata/surveydata/2010.htm YRBSS Similar to the BRFSS, the Youth Risk Behavior Surveillance System addresses risky behavior in adolescents in grades 9-12. “The Youth Risk Behavior Surveillance System (YRBSS) monitors priority health-risk behaviors and the prevalence of obesity and asthma among youth and young adults. The YRBSS includes a national school-based survey conducted by the Centers for Disease Control and Prevention (CDC) and state, territorial, tribal, and local surveys conducted by state, territorial, and local education and health agencies and tribal governments (CDC, 2009).” Visit the YRBSS web site to learn more about this survey. http://www.cdc.gov/HealthyYouth/yrbs/index.htm International Sources of Data The World Health Organization (WHO) provides access to data so that cross-national comparisons can be made. WHO publishes the Weekly Epidemiological Record, similar to the CDC’s Morbidity and Mortality Weekly Reports, that highlights international trends in diseases and other health conditions. WHO also publishes an annual World Health Report that highlights important health trends. Visit the WHO web site to learn more about the WHO data available. http://www.who.int/research/en/
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Additional References Centers for Disease Control and Prevention (2008). Overview: BRFSS. Retrieved from http://www.cdc.gov/brfss/technical_infodata/surveydata/2008/overview_08.rtf Centers for Disease Control and Prevention (2009). Data and Statistics: YRBSS. Retrieved from http://www.cdc.gov/HealthyYouth/yrbs/index.htm Friis, RH and Sellers, TA. (2009). Epidemiology for Public Health Practice. Sudbury, MA: Jones and Bartlett Publishers. Harkness, GA. (1995). Epidemiology in Nursing Practice. St. Louis, MO: Mosby-Year Book, Inc. Webb, P., Bain, C., and Pirozzo, S. (2005). Essential Epidemiology: An Introduction for Students and Health Professionals. New York, NY: Cambridge University Press. World Health Organization (2009). WHO: Data and Statistics. Retrieved from http://www.who.int/research/en/
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