Public Affairs in Health (PAH)

Best Practice

Health Disparity/Equity: Operationalizing Terms of Use

Doresa A. Jennings PhD, M.Ed

Abstract

This paper proposes the need for and the opportunities of operationalizing terms normally found when evaluating and reporting results of public health practices that deal with health disparity/equity. The purpose of this paper is to put forth a framework in an effort to garner consensus in the use of terms often seen in the evaluation of programs with a focus on health disparity/equity, especially within the area of health communications. The terms dealt with in this paper are: fairness, health equity, health disparity, underserved populations, health access, and health outcome.

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Introduction

According to the White House (2009), President Obama supports legislation to encourage research that will examine gender and health disparities. A focus on the issue of health disparities in research should increase in the very near future. It is also reasonable to guess there may be health disparities/health equity reporting requirements for organizations that receive federal, state, and/or local dollars for health research and services. With the increased focus in these areas, it is the author’s desire to propose a standardization and operationalization of terms commonly associated with this very important area of research. This is especially true in health communications, a public health area often noted for its work in health disparities and health equity (Thomas, 2005).

If we begin to see in health communication a resurgence of articles and study results focusing on health disparity and associated topics, it will be much easier to interpret, utilize, and expand on the knowledge if there is an agreement on the meanings associated with and the parameters defined by those terms. To start with, defined consensus on the operationalization of terms within public health communications could be a useful start to this endeavor. While consensus is never easy (and in some ways, limited by time), it can make the research of the area of concentration more impactful and make the specific research more meaningful to the broader field of public health.

The terms this paper will be focus on are: fairness, health equity, health disparity, underserved populations, healthcare access, and health outcome. These particular terms were chosen due to their frequency of use in research proposals, journal articles, and official releases from public health organizations, especially in health communication(s). Without agreement on terms, it can undermine data results and reduce confidence in analysis. Lack of confidence in analysis can cause a hindrance in the ability to help intended audiences. One reason the operationalization of terms of use is so important in health communications is the nature in which results are disseminated and utilized. The very nature of health communications brings with it a broad distribution of the research it produces, from historical professional public health audiences and clinicians, to release of information to the general public from press releases, various print and television media, websites, and even blogs. Messages have the potential to reach such a wide array of audiences that ensuring the messages are encoded with the proper terms and generate appropriate decoding are key.

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Terms and Their Use

Fairness — when the concept of “equity” is examined and put forward, a common term recently used in the media as well as federal and other governmental entities is that of fairness. While the term fairness can be seen in releases of data from public health organizations throughout the world, it is not always fully defined in a measurable way. One aspect not always defined is the fairness of what? Are we looking at the fairness of the opportunity to have health care choices or the fairness of the actual health outcome? According to Webster’s Dictionary (2008), fairness is defined as being free from bias, dishonesty, or injustice. However, something can, in fact, be free from bias and still not meet the criteria often being examined in the public health area. It is proposed in this paper that when the term “fairness” is often utilized by public health organizations, especially in the establishment of new public health rules, programs, or policies to promote health outcomes in for specific groups or populations, a more appropriate term of distributive justice would probably best be utilized. Distributive justice deals with what is “fair” or “right” with respect to the allocation of goods in a society which, for our intents and purposes, would be health care (Phelps, 1987).

According to the Standard Encyclopedia of Philosophy (2007), principles of distributive justice are normative principles designed to guide the allocation of the benefits and burdens of economic activity. In the public health, the economic activity would be those funds designated specifically for the relief of health inequity seen in various populations. Taking the conversation away from “fairness” in terms of equal distribution of resources, to that of distributive justice more rightly shows the funding of activities whose purpose is to expressly deal with an unequal burden of disease and/or lower health status.

Health Equity — a situation in which, regardless of individual behavior, individuals have access to equal opportunities for positive health outcomes. Oftentimes, this term is used when a more appropriate term of “health inequity” is meant. According to the Center for Health Equity (2009) health inequities are a subset of health inequalities or disparities involving circumstances that may be controlled by a policy, system, or institution so that the disparity is avoidable. In other words, health inequity is a situation in which, regardless of individual behavior, an individual would not have access to positive health outcomes than can be reasonably expected given their situation.

An example of health inequity would be an environment in which access to a high quality hospital or clinic is not available within a reasonable distance. Another example would be an environment in which access to high quality, healthy foods is not available within a reasonable distance. Examining the concept of health equity when evaluating public health programs or policies, the author proposes using the term health equity when explaining how on par health outcomes are across groups and health inequity when examining the differences between groups.

Health Disparity — a situation in which health outcomes are unequal and the divide can be made by factors such as race, socioeconomic status, or location (Carter-Pokras and Baquet, 2002). While we would expect to find differences in health outcomes amongst individuals – when these differences can be traced to an individual’s race, socio economic status, or location – we must begin to examine if this is an illogically occurring health disparity. For instance, obesity is seen in greater numbers for individuals, regardless of race, of lower socioeconomic status. Due to the fact that this is an illogical divide (as many individuals of varying socioeconomic status theoretically should have access to the same foods, health messages, doctors, etc.) The question that needs to be examined is “why” we find greater obesity in certain segments of the population, thereby uncovering a health disparity needing to be addressed. The author proposes that the health disparity be defined in terms of the measurable health issue rather than a general demographic term. Utilizing this health term will allow the intervention to be more easily evaluated for effectiveness and generalized to appropriate demographic populations.

Underserved Populations —generally “groups” that have less access to healthcare than their comparative numbers in the general population would expect. These groups often consist of: low-income individuals, uninsured persons, immigrants, racial and ethnic minorities, and the elderly. The author proposes using this term when the group can be easily defined and readily compared to a larger population. The author also proposes defining “underserved”in measurable terms so that health communication interventions can be evaluated on their effectiveness of closing this service gap.

Healthcare Access — the amount of opportunity a person has to access healthcare and other health needs (like prescription and over-the-counter medications). Healthcare access is not limited to having health care facilities in the area, but whether or not individuals can actually attain the services of those facilities. However, there are some situations where facilities are not within the reach of certain populations.

Health Outcome — the outcome one would expect for a given condition given proper health treatment (AcademyHealth, 2004). The reason this concept is often reviewed when looking at disparities in public health is because we often see health outcomes not expected for certain groups. We would not normally expect to see a difference in outcomes to health treatments of individuals statistically traced to socioeconomic status. However, differences in health are seen throughout the U. S. and that can be traced to socioeconomic status. Health outcome helps us to closely examine what is the “expected” health result versus what is the “observed” health result (O’Donnell, n.d.).

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Defining Populations

Another proposed area for making evaluations more understandable and useful for a variety of public health audiences is that of more defined populations. Often times broad populations are defined with one title including such groups as: minorities, women, and low socioeconomic status. The author proposes that it would be useful to be clear in terms of what individuals are included in the terms being used. When referring to “minority,” does this include all nonwhite individuals or specifically African-Americans and Hispanics? It is also important to determine specifically who is included in the population. Is a researcher dealing with all African-Americans or only those African- Americans that fall within a specific socioeconomic status? It is equally important to be clear on who is “not” included in the defined population as it is to be clear on those that will be examined.

One way of gaining consensus in population definitions would be the utilization of already established demographic groupings. Some well noted organizations with clearly defined demographic groupings include: the United States Census Bureau, the United Nations, and the U.S. State Department. Utilizing an already established demographic groupings chart will allow for a more cohesive understanding of the data being presented. This consensus is particularly useful when evaluating the results of public health campaigns for wider dissemination.

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Parameters

One thing the individual researcher must be conscious of in the area of health equity research is that of parameters. Many of our definitions deal with populations groups (i.e. minorities, low socioeconomic status, etc.). While defined populations have been common in research for hundreds of years, our demographic terms can encompass a wide range of individuals whose individual experiences vary widely. We can also enter situations in which individuals fall within several of our chosen populations, which can begin to hinder our analysis efforts. For instance, at what point (if any) would socioeconomic status play a larger role in health outcome than ethnic/racial status? We also encounter individuals who fall within our chosen populations on one factor (i.e. racial/ethnic status), but within our control group in another factor. This can lead us, again, to have interpretation issues with our data. For instance, would an African-American with a multimillion dollar net worth have health outcomes more similar to the group labeled “minorities” or the group labeled “higher socioeconomic status?” What about a Caucasian male living well below the poverty line? When establishing our population groups for study, we want to be cognizant to set our parameters to clearly include those groups who are truly targeted for the public health intervention or health communication campaign message. The first benefit the setting of proper parameters would have is not diluting our groups to the point of covering up true impact of our campaigns (i.e. setting the parameter of low-income minorities as opposed too broad minority category). Parameters allow us to focus our results so that those who wish to duplicate our success or avoid our failures can have a more defined scope from which to concentrate. With limited dollars available for public health interventions, scoping succinct groups will give us more efficient campaigns to produce and implement.

We have seen throughout the field of public health that very successful programs in one area can have considerably less success when trying to be implemented on a broader scale. Having more focused parameters will help organizations make better decisions on where programs may have the greatest impact.

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Conclusion

The goal of this paper was to help start the conversation on ways to operationalize and standardize terms when evaluating public health programs that focus on health equity/health disparity. The intent of this paper is not to set the standards to be applied across the field of public health, rather as a call for researchers to stringently apply the use of terms and parameters to their research. By having congruence of terms, published work can be more readily acted upon by others in the field of public health. Consistency of terminology allows limited dollars to be more efficiently utilized by not duplicating mistakes and also promotes better analysis of the data. Health communications is a field of public health that is increasing in size and impact, so having consensus on terms will do us all a great service. The more meaningful we make our terms in the health communications, the more widespread our work can be utilized, even outside of our field. In the past five to ten years, the importance of health communications to overall public health activities has become more evident and making our research available to the widest possible audience will ensure our most successful programs have the ability to be implemented on the widest possible and appropriate level. Having very well defined and meaningful terms will be a great start to this important process. Will there be risks to our field if there is a move to more consensus based terms of use in our research? Yes. The biggest reason is that many of these terms are “legacy” terms, meaning they have been used so often that can have meanings (although diverse) already associated with them. However, clearly defining the terms, thereby making them understandable to persons within and outside of health communications, can help to overcome this risk.

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Corresponding Author

Dr. Doresa Jennings works as a Health Communication Specialist/Issues Manager for the Coordinating Center for Health Information and Service at the Centers for Disease Control and Prevention. She has a PhD in Communication Studies with research experience and interest in health communication, intercultural/inter-racial communication, and organizational change. Dr. Jennings can be reached at 404.498.6415 AZV6@CDC.GOV

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References

AcademyHealth. (2004). Health Outcomes Core Library Project. The National Information Center on Health Services Research and Healthcare Technology, National Library of Medicine.

Carter-Pokras, O., & Baquet, C. (2004). What is a health disparity? Public Health Reports, v. 117, (pp. 426-434).

Hegtvedt, K. A., Markovsky, B. (1995), “Justice and Injustice”, in Cook, Karen S.; Fine, Gary Alan; House, James S., Sociological Perspectives on Social Psychology (1 ed.), Boston, MA: Allyn & Bacon, 1994, pp. 257-280.

Konow, J. (2003): “Which is the fairest one of all?: A positive analysis of justice theories,” Journal of Economic Literature, vol. 41, no. 4, (pp. 1188-1239).

Leventhal, G. S., Karuza, J., Fry, W. R. (1980), “Beyond Fairness: A Theory of Allocation Preferences”, in Mikula, Gerald, Justice and Social Interaction: Experimental and Theoretical Contributions from Psychological Research, New York, NY: Plenum, pp. 167-218.

O′Donnell, O., van Doorslaer, E., Wagtaff, A., Lindelow, M. (n.d.) Analyzing Health Equity Using Household Survey Date: A guide to techniques and their implementation. World Bank Institute.

Phelps, E. S. (1987): “Distributive Justice,” The New Palgrave: A Dictionary of Economics, v. 1, pp. 886-88.

Silow-Carrol, S., Alteras, T., Stepnick, L. (2006). Patient-Centered Care for Underserved Populations: Definitions and Best Practices. The W. K. Kellogg Foundation.

Tackling Health Inequities Through Public Health Practice: A handbook for action. (2006). Richard Hofrichter (Ed.). The National Association of County & City Health Officials and The Ingham County Health Department. Stanford Encyclopedia of Philosophy. (2007). http://plato.stanford.edu/entries/justice-distributive/ . Accessed on March 20, 2009.

The Center for Health Equity. (2009). http://www.louisvilleky.gov/Health/equity/ . Accessed March 5, 2009. Thomas, S. B., Fine, M. J., Ibrahim, S. A. (2004). Health Disparities: The Importance of Culture and Health Communication. American Journal of Public Health 94/12 (pp. 2050)

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