Introduction
The issue of disparities in health status, access to healthcare and patient outcomes for subgroups of the population has been a concern for public policy for a long time. For example, in 1985, there was a report by the U.S. Department of Health and Human Services that highlighted the disparities in healthcare for subgroups. This report emphasized the need to increase the coordination between federal agencies to cater for disparities, improve research and provide better health for racial and ethnic minorities (Murray, Salomon, & Mathers, 2000). There were extensive calls for policy responses to address the excess number of deaths among racial and ethnic subgroups. There is growing recognition that some of the population subgroups receive suboptimal healthcare and attain poor health outcomes. Today, the common term, “vulnerable populations” refers collectively to social groups with increased comparative risk (exposure to risk factors) or susceptible to health-related problems. The measure of vulnerability may include relatively high mortality rates, reduced access to healthcare, lower life expectancy and decreased quality of life. Vulnerable populations are marginalized and disenfranchised from general society, leading to lower social status and reduced influence in personal, social and political circles(Murray, Salomon, & Mathers, 2000). Undoubtedly, researchers must study vulnerable populations. However, studying them is not a straightforward process. This paper examines the challenges involved in studying vulnerable populations.
Studying vulnerable populations can be a daunting task. There are a number of challenges that face researchers when they study vulnerable populations. Communication sometimes poses barriers between researchers and members of the vulnerable population. The ability to communicate with researchers and provide them with valuable information for their research is very important (Mooney & Fohtung, 2008). Communication barriers may arise from the respondent’s level of development or education, cultural of language differences, health problems, mental or physical disability. Despite being widespread in the United States, the problem of low literacy has been neglected. According to a report by the National Assessment of Adult Literacy, done in 2003, over 44 million Americans are illiterate in the English language. Another 50 million are marginally literate. These statistics imply that over half of the adult population in the United States experiences reading problems (Hahn & Cella, 2003). These problems can pose major challenges to researchers when they are conducting health research on vulnerable populations. In addition to illiteracy, another barrier to research on vulnerable populations is cultural differences. In some cultures, for example, women do not easily engage in conversation with strangers who are men. Any attempts to interact with women and children from these cultures may be problematic from a research standpoint (Hahn & Cella, 2003).
The second factor that causes challenges to researchers is homelessness and incarceration. Studying people who do not have conventional housing can be very difficult because they are not easy to track and monitor (UyBico, Pavel, Gross, 2007). In addition, many homeless and incarcerated people with chronic illnesses are, usually, not in contact with their families, making study very difficult. Studying people requires accessibility. The researcher should be able to observe and interview the individual respondents in their environment. According to UyBico, Pavel, Gross (2007), people who are incarcerated are, usually, not cooperative with researchers.
The third contributing factor to the challenge of conducting research on vulnerable populations is fear of safety of being reported to the authorities some of the vulnerable populations have illegal immigrants such as Latinos and Africans. Any attempt to extract information from them or recruit them for research meets a lot of resistance (UyBico, Pavel, Gross, 2007). This fear rises because some federal and state policies in the recent past have restricted some of the immigrants from accessing healthcare. These actions have lead to increased suspicion among immigrants when approached by researchers for recruitment into health surveys and studies. Another barrier to research that is related to fear includes the lack of confidentiality. Immigrants and other vulnerable populations doubt the commitment by researchers to maintain the confidentiality with their personal information (UyBico, Pavel, Gross, 2007).
The fourth barrier to research on underserved populations is inadequate or inaccurate data collection. The Healthy People 2010 initiative highlighted health disparities along racial, ethnic, sexual orientation, socioeconomic, age, gender, disability status, and urbanicity lines. However, data collection was a major concern for the initiative because the process of assessing health disparities is an issue of paramount importance. Data and measurement problems have been an ever-present challenge for policy-makers and researchers over the years (Bilheimer & Klein, 2012). There have been data limitations regarding race and ethnicity. In addition, there have been challenges of identifying disparities in priority subpopulations (Bilheimer & Klein, 2012). According to Weissman et al., (2011), very large plans may not be equipped with the resources to use in data collection. Large plans have limited contact established with the high number of enrollees. As a result, large plans are, usually, never in touch with the situation at the individual level. Smaller plans, on the other hand, may have the flexibility required to do so. According to Bilheimer & Klein (2010), small sample sizes may also limit the researchers’ ability to measure health disparities even for major ethnic, racial and socioeconomic subgroups nationally.
Disparities measurement should attain the same objectives as the overall quality management. These objectives include monitoring progress, stimulating competition, informing purchasers and consumers and stimulating innovation (Weissman et al., 2011). Case studies on government initiatives, institutions and organizations that have started collecting, analyzing and reporting disparities in quality measures show the incipient progress and provide important lessons. One of the states that have spearheaded disparities measurement and decrease, Massachusetts, has experienced gains as well as setbacks along the way. There are several solutions that may result to improved and more accurate measurements of disparities. The first solution involves using small and focused research plans rather than large plans. Smaller disparity measurement research plans are more accurate than large plans because they establish closer contact with research respondents (Weissman et al., 2011). The data collection methods employed in small research plans are thorough and elicit a higher level of trust in respondents than large plans. Problems of data collection associated with the sample size may be reduced through oversampling, targeted periodic surveys, pooled data, and modeling approaches (Bilheimer & Klein, 2010). Researchers should oversample vulnerable populations of policy interests such as blacks, Hispanics, Asians, and low-income earners. Pooling data involves combining survey data collected over a period of several years to address problems of small data samples. For example, according to Bilheimer & Klein (2010), racial disparities in hospitalizations for amputations among diabetic people have been assessed using three-year period data. However, this approach calls for data collection instruments to be consistent over time (Bilheimer & Klein, 2010).
Secondly, the problem of literacy and communication barriers may be reduced using creative ways. For example, the researchers may involve a local interpreter who is trusted by the local community, and who knows the local culture and language. This approach does not only lead to a higher level of participation at the local level but is also accurate (UyBico, Pavel, Gross, 2007). Another approach would be to involve tape-recorded/ verbal questionnaires as opposed to written ones. A large portion of vulnerable populations may understand a verbal question and respond verbally (UyBico, Pavel, Gross, 2007).
Thirdly, the researcher may overcome the challenge of fear amongst the research respondents by using local leaders and community figures to approach particular communities. The researcher should indicate their ethical stand and promise confidentiality on any information collected (UyBico, Pavel, Gross, 2007). This approach eliminates the fear of being reported to the authorities in the case of undocumented immigrants (UyBico, Pavel, Gross, 2007).
Conclusion
Disparities in healthcare have existed for a long time in the United States. The concept of vulnerable populations emerged from the knowledge that some people are disadvantaged in terms of financial and physical access to healthcare. Researchers have tried to expose these health disparities, albeit with various difficulties. One of the main difficulties includes poor cooperation. Some of the people in the vulnerable populations are illegal and undocumented immigrants (Murray, Salomon, & Mathers, 2000). As such, they fear that researchers will report them to the authorities. Another challenge is a lack of access to respondents. Incarceration and homelessness are responsible for this poor access. The third problem involves illiteracy and communication barriers. Another problem is inadequate and inaccurate data collection. There are various solutions to these challenges. One of these solutions is the use of creative survey methods to collect information such as the use of interpreters. Researchers may also improve data collection and sampling approaches to produce accurate data (Murray, Salomon, & Mathers, 2000). Undoubtedly, research efforts need to be improved to expose healthcare disparities and prompt corrective measures.
References
Bilheimer, L. T., & Klein, R. J. (2010). Data and Measurement Issues in the Analysis of Health Disparities. Health Services Research, 45(5p2), 1489-1507.
Hahn, E. A., & Cella, D. (2003). Health outcomes assessment in vulnerable populations: Measurement challenges and recommendations. Archives of Physical Medicine and Rehabilitation, 84, S35-S42.
Mooney, G., & Fohtung, N. (2008). Issues in the measurement of social determinants of health. Health Information Management Journal, 39(2), 26-32.
Murray, C., Salomon, J., & Mathers, C. (2000). A critical examination of summary measures of population health. Bulletin of the World Health Organization, 78(8), 981-994.
Uybico, S. J., Pavel, S., & Gross, C. P. (2007). Recruiting Vulnerable Populations into Research: A Systematic Review of Recruitment Interventions. Journal of General Internal Medicine, 22(6), 852-863.
Weissman, J. S., Betancourt, J. R., Green, A. R., Meyer, G. S., Tan-McGrory, A., & Zeidman, J. A. (2011). Commissioned Paper: Healthcare Disparities Measurement. Harvard Medical School, 1(1), 1-84.
