Public Health Reporting On the U.S. Healthcare System

The Impact of Public Health Reporting on the U.S. Healthcare System

One of the public health practitioners’ primary roles is to promote individuals’ overall well-being through health improvement, health protection, and service improvement initiatives using populace health surveillance approaches. Every major cause of health deterioration in the U.S, ranging from interpersonal violence to diabetes, ischemic heart diseases, and suicide, is monitored and reported through an extensive public health reporting system (“Public health surveillance,” 2018). Involved stakeholders carry out population surveillance using various public health reporting systems. The data obtained from these reporting systems are then used to make interventions that will improve the target population’s health outcomes.

However, despite having a rigorous population surveillance system, public health officials and other involved stakeholders have been accused of failing to contain and manage public health issues effectively. While these allegations may be factual for the recent COVID-19 outbreak, it is indisputable that these professionals have contributed significantly to the attainment of the U.S populace’s current health status through population surveillance. Given that this approach involves data collection and reporting systems, the paper will also discuss its effect on health information technology.

Background Information

In response to threats and reemergence of health conditions such as influenza, severe acute respiratory syndrome (SARS), and Ebola, the International Health Regulations (IHR) created a legal framework to prevent and protect the public from notifiable diseases. According to Brownson et al. (2018), notifiable diseases relate to health conditions that must be reported to public health authorities because they are a threat to human and animal life. IHR requires all countries to develop and expand their capacity to detect, evaluate, notify, respond, and report any health events identified as a threat to the public’s well-being. Every sovereign state bound by the IHR law is expected to establish a public health reporting framework to reinforce and maintain its national surveillance and reporting mechanisms.

In the United States, several public health agencies such as the Human Health Services and the Center for Disease Control (CDC) are charged with protecting the public from notifiable conditions and adverse health events. One of the strategies used by these organizations to meet this objective is population surveillance. This approach serves two significant purposes: identify key improvement areas and increase the public’s understanding of their communities’ health status. It relates to the process of monitoring the health status of a given populace using a set of evidence-based health indicators. It involves monitoring health determinants, health behaviors, risk factors, and the state of chronic conditions of target groups.

Health determinants are considered crucial only if they cover issues relevant to public health. To conduct population surveillance, data on key health indicators must be collected. Healthcare facilities across the United States submit health-related information to appropriate public health agencies through an established reporting system used to receive and collect data on logistical, financial, and clinical practices and processes from various health settings. These organizations gather information from the healthcare settings at the local, state, and national levels. They later compile, analyze, summarize, and disseminate their findings through various channels.

The Purpose of the Topic

The subject of population surveillance is of critical importance to the health of Americans. The lack of information on the status of a populace’s health may lead to adverse effects on the public. For example, according to Brownson et al. (2018), approximately 6 million children could have been saved yearly if 23 proposed public health interventions had been implemented. On the bright side, California has successfully translated information from proposed public health programs to improve its residents’ health (Brownson et al., 2018). Through a proposed public health initiative, California established an anti-tobacco control program to minimize state-wise smoking rates.

The initiative triggered a significant decline in cigarette use in California and decreased the incidence of tobacco-related deaths from heart disorders. Furthermore, Brownson et al. (2018) revealed a link between tobacco consumption’s decline and the reduced prevalence of respiratory disease-related demises in the state. California used information from populace surveillance programs to develop multilevel interventions and policies, which fostered these outcomes. The success of the California tobacco control project and the debilitating effects of our first illustration imply the importance of population surveillance in influencing health outcomes.

Second, policymakers make important policy decisions at the local, state, and national levels based on population surveillance data. These experts are interested in the hospitals’ quality performance, and to achieve this goal, they typically adopt the public health reporting framework. Evidence shows that policymakers’ interest is always guided by perceived priorities influenced by their constituents’ real-life experiences. According to Brownson et al. (2018), policymakers always base their decisions on health surveillance data deemed relevant to their members. Because population surveillance directly measures what is going on in a given populace, it should be used as a tool to measure the need for intervention and its subsequent impacts.

The Improvement of Quality of Healthcare Services

Public health professionals have been involved in several health initiatives in the United States. Population surveillance has been instrumental in improving the quality of healthcare. A systematic review by Campanella et al. (2016) supports this stance. These researchers reviewed surveys published between 1st January 1991 and 31st December 2014 to establish whether these systems impacted clinical outcomes (Campanella et al., 2016). The evaluated primary clinical outcomes included mortality, cardiac readmission, waiting periods, percutaneous coronary intervention rates, infection rates, hospital rehospitalization rates, and caesarian deliveries. The survey uncovered this approach’s efficacy in improving these measures’ outcomes.

The wide range of reporting systems incentivize optimal performance in clinical quality, patient experience, and the cost of healthcare. These measures translate into three major forms of incentives including financial, public recognition, and public reporting. Financial incentives involve receiving a lump of money from the federal government for fulfilling their requirements. For example, the Medicare Physician Quality Reporting System incentivized physicians who adequately reported on key measures by awarding them with financial bonuses. The public reporting is some form of online report card on the performance of healthcare organizations in improving patient outcomes. A study conducted by Chee et al. (2016) public reporting led improved hospital performance from 2.6% to 4.1% within a two-year time frame.

There are two possible mechanisms through which the reported outcomes result in quality care. First, when information on hospitals’ performance is publicly reported, entities are inspired to take quality initiatives to increase the benefits linked to market shares. Out of concern for the entity’s reputation, the involved parties often take necessary steps to foster better organizational performance. Secondly, care facilities can use published reports to distinguish areas that require improvement and implement appropriate initiatives to achieve better outcomes in the domains specified. Public health reporting systems promote healthcare quality by enhancing providers’ transparency and accountability.

The Argument against this Approach

There is an increasing interest in presenting healthcare providers with the relevant information to improve their clinical performance. Performance measures refer to the metrics used to gauge or evaluate the effectiveness of a program or entity. They indicate objectives a specific project should accomplish and the results or desired outcomes’ achievability. Performance measures also guide resource allocation to ensure the effectiveness and efficiency of established strategies and interventions at the organizational, state, and federal levels. It helps stakeholders focus on key goals; it also justifies budget allocation.

The performance metrics used to evaluate the influence of public health reporting is problematic. Research on outcome management provides at least five insights about measuring and interpreting healthcare quality from outcome indicators. First, healthcare outcomes result from a large matrix of factors that a single or couple of performance metrics cannot comprehensively measure outcomes. According to a study conducted by Chee et al. (2016), the reliability and validity of performance measures used to evaluate clinical performance are questionable. The criticism mainly emanates from questions on the performance metrics’ ability to measure crucial healthcare aspects. Critics argue that performance measures are insensitive to change and do not measure the relevant issues in healthcare (Chee et al., 2016). Concerns also arise on whether the performance measures are resistant to detection bias, patient selection, and coding practices with false favorable scores on performance measures. Because the performance measures are prone to detection bias, variations unrelated to healthcare quality can occur in reported outcomes.

Other studies question whether the selected measures clearly articulate the definitions that foster a common contrasting point among providers in different healthcare settings. Failure to have a standard comparison point that accounts for score variations recorded by healthcare facilities poses several issues. For example, hospitals with limited resources may be disadvantaged in attempting to attain the required healthcare outcomes. Due to restricted resources, their’ capacity to improve their underlying performance will also be constrained. Failure to fulfill regulatory bodies’ requirements can also lead to lower reimbursement, fewer resource incentives, and so forth. While process-oriented measures are equally important, realistically, output measures are more pertinent in assessing process-oriented practices’ efficiency.

An example of a reporting system whose validity is questionable is the Hospital Inpatient Quality Reporting Program. The pay-for-reporting program, which is administered by the Center for Medicare and Medicaid Service’s (CMS), provides incentives to hospitals that report on selected measures. However, this strategy has been criticized for its validity, especially its methodological design (Rau, 2016). CMS postponed its plans to award poor-performing entities a one-star and best performing entities a five star in response to the criticisms. This retaliation came after congress members signed a letter supporting some stakeholders’ concerns on the rating system’s validity (Rau, 2016). Most critics argued that the preliminary rating system is skewed against vulnerable entities with few resources and those that provide care to the most impoverished health populations.

The third concern of the performance is that healthcare providers are likely to partially or wholly focus on care aspects measured by regulatory bodies rather than broader issues that are just as significant in healthcare. In the same regard, quality improvement initiatives will target the measured characteristics at the expense of other unmonitored aspects. Another concern of the performance measures is caused by the unintended workloads that may arise due to regulatory mandates. For example, pay for performance reporting systems mandate nurses to document care relevant to a hospital’s reimbursement on paper charts. Evidence indicates that acute care nurses spend a significant amount of time documenting patient information (Shihundla et al., 2016). This approach also increases practitioners’ clinical workload, which, according to Shihundla et al. (2016), also affects the quality of healthcare services provided adversely. For example, a recent study found that patients admitted for the monitored medical conditions only had their care documented in charts when the nurse-to-patient ratio per hour was lower (Shihundla et al., 2016). The survey showed that nurses would either ignore document patient information or document ineligible, incomplete, and inaccurate patient information due to a high workload. These practices have negative implications on the outcomes of reported measures.

The above studies’ findings raise concerns on whether the reported influence of reporting systems on clinical outcomes is genuine. If the clinical practices and processes’ performance measures are problematic, their consequential results may be deemed ineffective. These findings on performance measures imply that the positive influence of reporting systems on clinical outcomes may not reflect the real situation in clinical settings. However, studies show that the healthcare system is already taking measures to adopt the “next-generation” performance measures. For example, in 2016, the CMS announced plans to eliminate the composite indicators that disproportionately affect disadvantaged healthcare entities (Rau, 2016). The newly-established performance measures are outcome-oriented and developed through a public-private partnership, which helps professionals to account for institutional differences. Additionally, none of the studies refuted the claim that public reporting systems increase transparency and provider accountability. Given that provider accountability is one of the mechanisms used to inspire desired change, it can be surmised that this approach improves healthcare services quality by promoting accountability in the healthcare system.

Improvement of the Health Literacy of the Population

Following the publishing of the IOM report, the role of patients in the healthcare system has changed. Patients are no longer considered payers or recipients of healthcare but key decision-makers. Healthcare providers are now required to incorporate patient choices and decisions in all key clinical decisions. It is considered unethical to force clinical interventions or decisions on patients, even if the interventions are in the patient’s best interest. Given their changed role and position in the healthcare system, patients are as equally in need of decision-making tools and resources as healthcare providers.

Public health reporting systems have promoted the health literacy level of the public. An individual’s health behaviors can be used as a proxy for measuring the health literacy of the population. Healthy behaviors include information-seeking practices, use of preventative care services, adherence to medical advice, etc. A study conducted by Stewart et al (2015) showed that low health literacy levels were associated with negative health behaviors and poor health outcomes. Data by the Center Disease Control shows that the “Behavioral Risk Factor Surveillance System” (BRFSS) has significantly contributed to the public’s behavioral change. In collaboration with other stakeholders, the CDC has reduced smoking rates from 20.9% in 2005 to 13.7% in 2018 (“Current cigarette smoking,” 2020). These statistics are supported by the Healthy People’s initiative data on tobacco use trends in the United States. Tobacco use rates reduced from 20.6% in 2008 to 13.9% in 2018 (“Access to health service,” 2018). Furthermore, approximately 56% of the adult population in the United States is actively attempting to stop smoking compared to 50.2% of adult smokers in 2008 (“Access to health service,” 2020). Taking initiatives to stop smoking is indicative of the health literacy of an individual.

Tobacco smoking is used as a proxy metric for behavioral change because of its role in chronic diseases. The CDC’s chronic disease indicator (CDI) is an integrated approach to disease surveillance that enables public health practitioners to access state-level and metropolitan-level data on the disease risk factors and social health determinants within their localities. The chronic disease indicator comprises 124 measures based on five key domains, including behavioral risk factors (“Behavioral risk factor,” 2020). The health indicators used in the behavioral risk domain include smoking, tobacco use, physical activity, weight status, diet, and nutritional choices. Tobacco, however, is a key metric because it is a predisposing factor in various chronic conditions.

The public health reporting systems have improved the public’s health literacy through two mechanisms: patient education and policy changes that support healthy lifestyles. According to the CDC, all states in the United States use BRFSS data to establish and evaluate health promotion programs (“Behavioral risk factor,” 2020). In Delaware, the data has been used to support legislation that creates healthy lifestyles. In Illinois, two legislations that banned smoking in the public building were supported by BRFSS data. In Nevada, the legislation to control chronic drinking and binge drinking was supported by BRFSS and CDI data (“Behavioral risk factor,” 2020). The measures have been used by Canada, Italy, and Sweden as well as Medicare. BRFSS data are used to inform policy and program development that improves the target populations’ health outcomes. Concerning assurance, the surveillance program conducts a frequent evaluation to ensure that target populations benefit from the implemented public health initiatives (“Behavioral risk factor,” 2020). The program’s data reflect on the socioeconomic disparities and provide insights on new health behavior and policies needed to improve outcomes.

Patient education provides the public with information that can influence lifestyle changes through behavioral change. The CDC, for instance, runs programs such as “Breathe East, Quit Smoking,” “Arthritis on the Rise,” Youth and E-cigarette Use, etc., to help target populations change their health outcomes (“Current cigarette smoking,” 2020). In addition to providing access to population health data, the website acts as a gateway to additional population health management resources. These programs provide the target population with information on strategies they can use to lessen the associated negative condition of interest. The agency develops and disseminates accurate, actionable and evidence-based interventions to promote the health literacy of the target population. Most of the recommended strategies aim to influence a shift in behavior changes. Conclusively, public health reporting systems provide the public with information access to enable them to make informed decisions. Access to information improves the health literacy of a given population, which influences behavioral changes

The Argument Against the Role of Public Health Reporting Systems in Improving Health Literacy

Some studies suggest the status of tobacco use in the U.S is still worrisome. According to the CDC (2020), approximately 13.7% (34.2 million adults) of the U.S. population are smokers. The agency further reports that over 16 million Americans live with a tobacco-related disease (“Current cigarette smoking,” 2020). Other than the high rates of current smokers, it has been reported that health disparities still exist among smokers. A study conducted by Nighbor et al. (2018) showed that the smoking prevalence among rural women was higher than the prevalence rates of women in urban regions. The increased incidence of smoking may be ascribed to genetic, psychological, environmental, and social factors, for instance, educational attainment, income level, and age.

The outcomes of the survey by the CDC replicate findings by other researchers, which demonstrated the prevalence of smoking disparities between rural and urban populations However, none of these studies contest that the U.S. there is a reduction in tobacco smoking rates. In fact, Nighbor et al. (2018) indicates that the smoking rates have reduced over the years. Had the data shown an increase in smoking rates, it would have been surmised that public health initiatives have not made an impact on smoking rates. Since none of the analyzed studies has reported an increase in tobacco rate, the notion that public health agencies have reduced smoking rates holds to be true. Tobacco is a proxy for the patient’s health literacy because anti-smoking initiatives mainly target a behavior change.

Reduced Health Disparities

Public health practitioners have spearheaded the implementation of screening programs that promote equity in healthcare access. Research evidence indicates that low socioeconomic conditions such as unemployment, unsafe working conditions, poverty, and inadequate housing are major risk factors of all health inequalities. These health determinants are not only cumulative and intergenerational but also preventable. One of the public health initiatives is to reduce health inequities driven by social and economic factors. To this end, public health agencies have been developing methods to test and implement evidence-based interventions to reduce health inequities among vulnerable populations.

Healthy People, a disease prevention and health promotion program in the United States, has been focusing on reducing health disparities for the past two decades (“Access to health service,” 2018). In 2010, the initiative announced that its purpose was to achieve total elimination, not just to reduce health disparities (“Access to health service,” 2020). In the past, health initiatives mainly focused on eliminating diseases that disproportionately affect the minority population to achieve health equity. However, the absence of disease does not automatically translate to good health. In this regard, the Healthy People Initiative strives to improve health equity through increasing access to nutritious food, housing, health insurance, clean water and air, and access to culturally sensitive healthcare providers.

Public health initiatives have triggered significant improvements in health equality in the U.S. There has been a remarkable decline in health disparities during the last decade. This stance is supported by a study conducted by Sighoko et al (2017) who reported that there was a significant decline in racial disparities between 1999 and 2013 in the healthcare system. The study attributed the reduction in health disparities to public initiatives (Sighoko et al., 2017). The Healthy People Initiative also supports this stance that health disparities in the U.S. have reduced. For example, in 2008, only 83.2% of people in the United States had medical insurance. Through interventions of the initiative, the number of people with insurance covers has improved from 83.2% to 89% in 2018 (“Access to health service,” 2018). The initiative’s interventions have also reduced the number of people unable to obtain medical care from 4.7% in 2008 to 4.2% in 2018 (“Access to health service,” 2018). Additionally, in 2008, only 76.3% of people had access to a usual primary care provider. About 79.6% of people have access to primary care providers (“Access to health service,” 2018). From the above statistics, it is clear that the U.S. healthcare system has made considerable improvements in reducing health disparities. The Healthy People objectives are prepared and reviewed by lead federal agencies that use population surveillance data to define measures and annual targets.

The Argument against the Role of Public Health in Reducing Health Disparities

Despite the progress of the Healthy People initiative, health inequalities still exist in the United States. A study conducted by the National Academies of Sciences, Engineering, and Medicine et al. (2017) showed that the reported reduction of health inequities does not hold true for all health outcomes. For example, the disparity in HIV/AIDs between African Americans has been significantly increasing over the years (National Academies of Sciences, Engineering, and Medicine et al., 2017). Preterm births, which are predictors of infant mortality, are highest among African American women than women of other minority groupings (National Academies of Sciences, Engineering, and Medicine et al., 2017). While reported statistics on infant mortality rates show a 14% reduction in the incidence of infant mortality from 2004 to 2014, racial and ethnic disparities still exist (National Academies of Sciences, Engineering, and Medicine et al., 2017). Native Americans and Alaskan Natives typically record higher death rates among infants, i.e., 60% high compared to the Caucasian populace (National Academies of Sciences, Engineering, and Medicine et al., 2017). Chronic conditions also disproportionately affect race/ethnic minorities as well as people of low socioeconomic status. Furthermore, as per the CDC report, around 48% females in the Black community and 44% of their counterparts suffer from at least one heart-related illness (National Academies of Sciences, Engineering, and Medicine et al., 2017). Health disparities across ethnic and racial lines still exist in the United States.

The National Academies of Sciences, Engineering, and Medicine notes that population surveillance data on health disparities are faulted for a number of reasons. First, population data on poverty, diabetes, and obesity between blacks and whites is adequate due to the large population size. Given that a small population size translates to a small sample size, health data on racial and ethnic minority groups may not reflect the whole population’s health status.

Additionally, different tribe or racial/ethnic subgroups may be consolidated within one major group, leading to underreporting of disparities in the minority group. The Hispanic group, for instance, has significant tribal variations based on their country of origin. However, population surveillance data reports this population’s health outcome as a single group despite the group’s heterogeneity. An example of this in-group variation can be demonstrated by the National Vital Statistics Survey (NVSS). The organization showed that among Hispanic women, Cuban mothers had better maternal health outcomes than Puerto Rican mothers (National Academies of Sciences, Engineering, and Medicine et al., 2017). Another limitation of the population surveillance data on health disparities is that it underreports on inequities of unique minority populations such as the lesbian, gay, bisexual, transgender, and queer (LGBTQ) community (National Academies of Sciences, Engineering, and Medicine et al., 2017). From the above analysis, it can be deduced that the reporting outcomes of health inequalities is flawed and, therefore, unreflective of the true status of health inequities.

However, the National Academies of Sciences, Engineering, and Medicine and associates’ findings do not antagonize the stance that public health interventions have led to the reduction in health disparities. Concurrently, despite the debilitating state of smoking rates, the organization indicates that the healthcare system had indeed managed to reduce health disparities in the last decade (National Academies of Sciences, Engineering, and Medicine et al., 2017). Therefore, it is unchallenged that public health reporting systems have reduced health disparities in the healthcare system.

The Impact of Public Health Reporting on Health Information Technology (HIT)

Population surveillance involves regular data collection of important health determinants from healthcare settings. Data used for population surveillance is collected through a public health reporting system. Public health reporting systems play a critical role in disseminating information to the public and involved stakeholders on the state of health of the population of interest. The CDC and other public health agencies rely on healthcare settings to initiate case reports. Any inaccurate, delayed, or incomplete reporting on diseases may lead to inaccurate clinical assessments, which, in turn, may lead to inappropriate health intervention and preventive care. Therefore, without a reporting system, adequate and comprehensive monitoring of the population’s health cannot be achieved.

However, public health reporting takes many forms, including journal articles, policy briefs, policy dialogues, brochures, reports, etc. Most recently, websites and media presentations, e.g., film and newspapers have become resourceful in disseminating public health data. However, a commonly cited barrier to the access and use of scientific information is the credibility and trustworthiness of the shared data. Lack of a trusted source of information can lead to public mistrust of the healthcare system. For example, during the recent pandemic, a considerable number of public members believe in the conspiracy theories that the COVID19 pandemic was deliberately planned. These, among other reasons, have led to the mistrust of vaccinations related to the virus. The widespread adoption of technology is also changing how data is collected. For example, the BRFSS currently experiences problems collecting population surveillance data because most residential homes have adopted telecommunication technology (Center for Disease Control, 2020). New telecommunication technology has deemed line telephones largely obsolete which negatively impacts the data collection process. Since the gathering of clinical data is largely done in using electronic approaches, there is an opportunity for automated electronic public health reporting that will promote credibility and foster trust with the public.

Public health reporting systems will influence how HIT will be used in the future. It has been projected that HIT will be the next-generation public health reporting system (CDC, 2018). Public Health Monitoring and Reporting system will adopt a comprehensive and integrative approach (CDC, 2018). This integrative approach means that future population surveillance will collect public health data from multiple sources and subsequently generate and publish the information from a single output system. Based on the strategic plan of CDC (2018), the agency plans to improve population surveillance through emerging tools such as the HIT. The agency reported that it will liaise with HIT vendors and other stakeholders to accelerate the use of HIT as a core data collection tool for population surveillance (CDC, 2018). Currently, the population surveillance and reporting systems are fragmented: i.e., every public health agency administers their reporting system.

However, in the future, Health Information Systems (HIS) will act as a data convergence point that will allow seamless integration of clinical workflows, processes clinical outcomes with reporting systems (“Public health surveillance,” 2018). Instead of recording data using health reporting systems administered by the state, healthcare providers will relay information on clinical processes and outcomes directly to the relevant authorities through HIT. CDC created the Health Information Innovation Consortium (CHIIC) program to spearhead the changes to promote create solutions for population surveillance. In the same regard, CHIIC identified key priority areas for HIT including interoperability, shared services, decision support, data management, and data collection privacy and security. This way, the public will have access to these new-generation reporting systems, neutralizing informational barriers related to mistrust and credibility.

Some public health agencies have already integrated HIT with their reporting systems. The Agency of Healthcare Research and Quality, for instance, implemented a clinical decision support system to facilitate the public’s awareness of notifiable diseases. A one-year post-implementation study showed that the integration of clinical decision support systems with public health reporting significantly improved clinical reporting rates and the completeness of submitted information (“Improving population health,” 2017). A significant milestone for adopting the decision support system was its role in improving case reporting without creating additional workload to healthcare providers (“Improving population health,” 2017). Through HIT, public health officials can improve the efficiency of data collection of crucial population surveillance metrics.


Public health reporting systems provide data on hospital structure, processes, and outcomes. The approach has positively impacted the healthcare system in the United States. This study’s findings show that public health reporting systems have promoted the quality of healthcare systems, improved health literacy, and reduced health disparities in the U.S. The reporting systems have achieved this through various mechanisms, including enhancing accountability, promoting patient education by disseminating public health information, influencing policy changes that promote public health, and supporting health promotion programs. However, public health status improvements are minimal because significant adverse health outcomes characterize the healthcare system despite implementing public health interventions. The arguments made against the topic were mainly based on the stance that health disparities and tobacco smoking are still prevalent in the country.

However, the studies acknowledged that although minimal, there have been improvements in tobacco smoking and health disparities over the last decades. The reporting systems promote transparency and accountability in the healthcare system, which, in turn, enables the delivery of quality healthcare services. When hospital performance is publicly boosted, relevant entities are motivated to improve their clinical processes to achieve optimal health outcomes.

Health literacy levels have been promoted through patient education and influencing policy changes that mandate behavioral change. Several statutes have been passed based on data from population surveillance systems. Therefore, this study underscores public health reporting systems’ effectiveness in promoting the U.S. population’s health outcomes. Healthcare stakeholders can adopt an integrated approach to public health reporting by adopting HIT. Health Information Systems can improve population surveillance reporting without creating additional workload to healthcare providers. Through HIT, public health officials can improve the efficiency of data collection of crucial population surveillance metrics. With the necessary tools and resources, healthcare providers can exercise judgment to provide comprehensive care to patients.


Access to health service (2018). Healthypeople. Web.

Behavioral Risk Factor Surveillance System – BRFSS (2020), Web.

Brownson, R. C., Eyler, A. A., Harris, J. K., Moore, J. B., & Tabak, R. G. (2018). Getting the word out. Journal of Public Health Management and Practice, 24(2), 102–111. Web.

Campanella, P., Vukovic, V., Parente, P., Sulejmani, A., Ricciardi, W., & Specchia, M. L. (2016). The impact of Public Reporting on clinical outcomes: A systematic review and meta-analysis. BMC Health Services Research, 16, 296. Web.

Chee, T. T., Ryan, A. M., Wasfy, J. H., & Borden, W. B. (2016). Current state of value-based purchasing programs. Circulation, 133(22), 2197–2205. Web.

Current cigarette smoking among adults in the United States (2020). Centers for Disease Control and Prevention. Web.

Improving population health through enhanced targeted regional decision support (Indiana) (2017). Agency of Healthcare Research and Quality. Web.

National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice (2017) The state of health disparities in the United States. In Negussie, Y., Geller, A., & Weinstein, J. N. (eds.), Communities in action: Pathways to health equity (pp. 123–170). National Academies Press.

Nighbor, T. D., Doogan, N. J., Roberts, M. E., Cepeda-Benito, A., Kurti, A. N., Priest, J. S., Johnson, H. K., Lopez, A. A., Stanton, C. A., Gaalema, D. E., Redner, R., Parker, M. A., Keith, D. R., Quisenberry, A. J., & Higgins, S. T. (2018). Smoking prevalence and trends among a U.S. national sample of women of reproductive age in rural versus urban settings. PLOS ONE, 13(11), e0207818. Web.

Public health surveillance preparing for the future (2018). Centers of Disease Control and Prevention. Web.

Rau, J. (2016). Rating hospitals by the stars: The feds’ latest plan to measure quality is the most controversial. Washington Post. Web.

Shihundla, R. C., Lebese, R. T., & Maputle, M. S. (2016). Effects of increased nurses’ workload on quality documentation of patient information at selected primary health care facilities in Vhembe District, Limpopo Province. Curationis, 39(1), a1545. Web.

Sighoko, D., Murphy, A. M., Irizarry, B., Rauscher, G., Ferrans, C., & Ansell, D. (2017). Changes in the racial disparity in breast cancer mortality in the ten US cities with the largest African American populations from 1999 to 2013: The reduction in breast cancer mortality disparity in Chicago. Cancer Causes & Control, 28(6), 563–568. Web.

Stewart, D. W., Adams, C. E., Cano, M. A., Correa-Fernández, V., Li, Y., Waters, A. J., Wetter, D. W., & Vidrine, J. I. (2015). Associations between health literacy and established predictors of smoking cessation. American Journal of Public Health, 103(7), e43–e49. Web.

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