Monitoring Socioeconomic Determinants for Healthcare Disparities: Tools from the Public Health Disparities Geocoding Project

Abstract

Adding insult to injury – This well-worn phrase redounds with new ­significance when considering healthcare disparities in the context of social inequalities in health. The very same social groups at greatest risk of being subjected to inadequate access to and unequal treatment in healthcare also endure the greatest risk of poor health status and premature mortality, reflecting the daily toll of discrimination, economic deprivation, political marginalization, and prioritization of economic gain over human needs (Smedley et al., Unequal treatment: confronting racial and ethnic disparities in health care. Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, Board on Health Sciences Policy, Institute of Medicine. Washington, DC: National Academy Press, 2003; Levy and Sidel (eds), Social injustice and public health. New York: Oxford University Press, 2006; Navarro and Muntaner (eds), Political and economic determinants of population health and well-being: controversies and developments. Amityville: Baywood, 2004). Greater need and lesser care nefariously combine to create even more onerous burdens of ­preventable suffering, for it is within the very same bodies that these injuries and insults are integrated and embodied (Krieger (ed), Embodying inequality­: epidemiologic perspectives. Amityville, NY: Baywood Publishing Co., 2004). To right these health wrongs, and to hold accountable the institutions, policies, and priorities that routinely permit or actively benefit from the everyday health inequities so evident within and across countries, data are essential. Information is needed on the magnitude of the problem, on who is most burdened by poor health and healthcare, and whether the disparities are shrinking or expanding. Not that these data can by themselves change anything. Rather, in the hands of those working for health equity, evidence of disparities in health status and healthcare is required to identify who is most harmed, who gains, and what actions need to be taken, by which groups, to make a change for the better. The connections between social determinants of health, health status inequities, and healthcare disparities would seem obvious. After all, our bodies readily make the connections each and every day (Krieger, Embodying inequality: epidemiologic perspectives. Amityville, NY: Baywood Publishing Co., 2004; Krieger, Epidemiol Community Health 59:350–5, 2005; Krieger and Davey Smith, Epidemiol Rev 26:92–103, 2004). Yet, in the United States, we confront a major obstacle to counting for accountability: the lack of routinely available good data on the magnitude of socioeconomic inequities in health status and healthcare, overall and in relation to diverse forms of social inequality variously involving racism, gender, sexuality, age, nativity, and immigration status (Krieger et al., Public Health Rep 112:481–91, 1997; Friedman et al. (eds), Shaping a vision of health statistics for the 21st century, 2002; National Healthcare Disparities Report, 2005; Ver Ploeg and Perrin (eds), Eliminating health disparities: measurement and data needs. Panel on DHHS collection of race and ethnicity data. Washington, DC: National Academies Press, 2004). Although hospital records and public health data systems almost always include data on age and sex (typically construed as biological variables only), numerous reports have documented the poor quality and spottiness of data on race/ethnicity, the paucity if not total absence of socioeconomic information, and the invisibility of data on immigrant status and sexuality (Krieger et al., Public Health Rep 112:481–91, 1997; Friedman et al. (eds), Shaping a vision of health statistics for the 21st century. Washington, DC: Department of Health and Human Services Data Council, Centers for Disease Control and Prevention, National Center for Health Statistics, and National Committee on Vital and Health Statistics, 2002. http://www.ncvhs.hhs.gov/hsvision/. Accessed 3 May 2006; National Healthcare Disparities Report. Rockville: Agency for Healthcare Research and Quality, 2005. http://www.ahrq.gov/qual/nhdr05/nhdr05.htm. Accessed 3 May 2006; Ver Ploeg and Perrin (eds), Eliminating health disparities: measurement and data needs. Panel on DHHS collection of race and ethnicity data. Washington, DC: National Academies Press, 2004). These gaps in the data are not accidental, even if they might not be willful. Instead, they reflect the priorities and frameworks (conscious and unconscious) of the groups who design and implement the data systems (Krieger et al., Public Health Rep 112:481–91, 1997; Desrosières, The politics of large numbers: a history of statistical reasoning (Transl. Camille Naish). Cambridge: Harvard University Press, 1998; Friedman et al. (eds), Health statistics: shaping policy and practice to improve the public’s health. Oxford: Oxford University Press, 2005; Krieger, J Epidemiol Community Health 58:632–3, 2004). Often these data gaps can be explained by the time-disgraced ruse of “no data, no problem”; however, also at play are the vulnerabilities of those who may be targeted for discrimination if they provide information on aspects of their subjugated social position (Ver Ploeg and Perrin (eds), Eliminating health disparities: measurement and data needs. Panel on DHHS collection of race and ethnicity data. Washington, DC: National Academies Press, 2004; Krieger, J Public Health Policy 13:412–27, 1992; Krieger, J Epidemiol Community Health 58:632–3, 2004). In this chapter, our focus on the lack of socioeconomic data in most US medical records and public health surveillance systems (Krieger et al., Public Health Rep 112:481–91, 1997; Friedman et al. (eds), Shaping a vision of health statistics for the 21st century. Washington, DC: Department of Health and Human Services Data Council, Centers for Disease Control and Prevention, National Center for Health Statistics, and National Committee on Vital and Health Statistics, 2002. http://www.ncvhs.hhs.gov/hsvision/. Accessed 3 May 2006; National Healthcare Disparities Report. Rockville: Agency for Healthcare Research and Quality, 2005. http://www.ahrq.gov/qual/nhdr05/nhdr05.htm. Accessed 3 May 2006; Ver Ploeg and Perrin (eds), Eliminating health disparities: measurement and data needs. Panel on DHHS collection of race and ethnicity data. Washington, DC: National Academies Press, 2004) in no way discounts the importance of discrimination – whether in relation to race/ethnicity, gender, sexuality, age, immigrant status, and so on, and within and across socioeconomic strata – in shaping population health (Krieger, Embodying inequality: epidemiologic perspectives. Amityville, NY: Baywood Publishing Co., 2004; Krieger et al., Am J Prev Med 9:82–122, 1993). However, in a context of an all-too-long misguided legacy of interpreting health disparities in these other dimensions as a function of allegedly innate biology, rather than social inequity (Smedley et al., Unequal treatment: confronting racial and ethnic disparities in health care. Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, Board on Health Sciences Policy, Institute of Medicine. Washington, DC: National Academy Press, 2003; Levy and Sidel (eds), Social injustice and public health. New York: Oxford University Press, 2006; Navarro and Muntaner (eds), Political and economic determinants of population health and well-being: controversies and developments. Amityville: Baywood, 2004; Krieger (ed), Embodying inequality: epidemiologic perspectives. Amityville, NY: Baywood Publishing Co., 2004; Desrosières, The politics of large numbers: a history of statistical reasoning (Transl. Camille Naish). Cambridge: Harvard University Press, 1998; Friedman et al. (eds), Health statistics: shaping policy and practice to improve the public’s health. Oxford: Oxford University Press, 2005; Krieger, J Public Health Policy 13:412–27, 1992; Krieger, J Epidemiol Community Health 58:632–3, 2004; Krieger et al., Am J Prev Med 9:82–122, 1993; Krieger and Fee, Int J Health Serv 26:391–418, 1996; Chase, The legacy of Malthus: the social costs of the new scientific racism. New York: Knopf, 1977), it is essential to show the extent to which socioeconomic resources (themselves reflecting the impact of past and present discrimination) are associated with health status and healthcare disparities within and between these different social groups, as well as within the population as a whole. Bringing socioeconomic position into the picture is thus one of several critical steps needed to confront naïve causal narratives of “health differences” premised on biological or cultural determinism. The challenge is both conceptual and empirical. It is in this spirit that the ideas and tools of the Public Health Disparities Geocoding Project are presented (Krieger et al., Geocoding and monitoring US socioeconomic inequalities in health: an introduction to using area-based socioeconomic measures – The Public Health Disparities Geocoding Project monograph. Boston: Harvard School of Public Health. http://www.hsph.harvard.edu/thegeocoding-project/. Accessed 3 May 2006; Krieger et al., Am J Public Health 95:312–23, 2005; Krieger et al., Am J Public Health 93:1655–71, 2003; Krieger et al., Public Health Rep 118:240–60, 2003; Krieger et al., J Epidemiol Community Health 57:186–99, 2003; Krieger et al., Am J Epidemiol 156:471–82, 2002; Krieger et al., Am J Public Health 92:1100–2, 2002; Krieger et al., Am J Public Health 91:1114–16, 2001; Krieger et al., Neighborhoods and health (Kawachi and Berkman eds). New York: Oxford University Press, 147–78, 2003; Subramanian et al., Am J Public Health 95:260–5, 2005; Subramanian et al., Am J Epidemiol 164:823–34, 2006; Rehkopf et al., Am J Public Health 96:2135–8, 2006).