Siegel and Nolan [1] argue for expanding requirements for collection of data on racial and ethnic groups and for implementing incentive programs to encourage healthcare plans and providers to address healthcare disparities. It is difficult to argue against the former recommendation, for properly analyzed data can be of great use. The fact is, however, that data on health and healthcare disparities have almost invariably been badly analyzed as a result of the failure to recognize the way standard measures of differences between rates are affected by the overall prevalence an outcome (as discussed in the references 2-5 below and the 100 or so references on the Measuring Health Disparities page (MHD) of jpscanlan.com [6]). Most notably, researchers rely on relative differences in experiencing favorable or adverse outcomes without recognizing the pattern whereby the rarer an outcome the greater tends to be the relative difference in experiencing it and the smaller tends to be the relative difference in avoiding it. Researchers using other measures of disparities also do so without recognizing how the measures tend to be affected by the overall prevalence of an outcome. –¶Two observations of the authors involve matters that illustrate key measurement issues. First, the authors note that “[b]ecause so many uninsured people are members of minority groups, expanding coverage will mean reducing disparities in coverage.” Because increases in overall levels of an outcome tend to reduce relative differences in experiencing the outcome, the authors are probably correct that increasing insurance coverage will decrease disparities in coverage (if measured in terms of relative differences). But the National Center for Health Statistics recommends that all disparities be measured in terms of relative differences in adverse outcomes (here, failure to be covered), and as things like insurance coverage become more widespread relative differences in failing to experience them tend to increase (as pointedly illustrated in reference 5). –¶Second, the authors note as a precedent for requiring collection of race/ethnic data the fact that since 1990 almost all entities providing home loans have been required to keep such information on loan applicants. The collection of that data led to the situation where – even as regulators were encouraging lenders to relax their lending requirements because of the impact of such requirements on minorities – banks with liberal lending policies and high overall acceptance rates (and small racial disparities in acceptance rates) were singled out as litigation targets because they tended to have large relative differences in rejection rates.[3,7] –¶The amount of research into health and healthcare disparities (and many other areas) without an understanding of certain fundamental statistical principals suggests that the collection of data on race/ethnicity may in fact prove very detrimental, at least with respect to resources wasted in the flawed analysis of such data. That said, however, in the hope that eventually there will be a better understanding of how to analyze the data than currently exists, probably it is better to have the data than not to have the data. –¶The authors’ recommendation of incentive programs, however, is another matter. As discussed on the Pay for Performance sub-page of MHD [8] and the references therein, there is too little understanding of how to measure disparities to actually tie an entity’s revenues to someone’s perception of whether disparities at the entity are large or small or are increasing or decreasing. –¶References: –¶1. Siegel B, Nolan L. Leveling the field – ensuring equity through National Health Care Reform. N Engl J Med 2009;361:2401-2403. –¶2. Scanlan JP. Can we actually measure health disparities? Chance 2006:19(2):47-51: http://www.jpscanlan.com/images/Can_We_Actual... –¶3. Scanlan JP. Race and mortality. Society 2000;37(2):19-35 (reprinted in Current 2000 (Feb)): http://www.jpscanlan.com/images/Race_and_Mort... –¶4. Scanlan JP. Measurement Problems in the National Healthcare Disparities Report, presented at American Public Health Association 135th Annual Meeting & Exposition, Washington, DC, Nov. 3-7, 2007: http://www.jpscanlan.com/images/ORAL_ANNOTATE... –¶5. Scanlan JP. Study illustrates ways in which the direction of a change in disparity turns on the measure chosen. Pediatrics Mar. 27, 2008 (responding to Morita JY, Ramirez E, Trick WE. Effect of school-entry vaccination requirements on racial and ethnic disparities in Hepatitis B immunization coverage among public high school students. Pediatrics 2008;121:e547-e552): http://pediatrics.aappublications.org/cgi/ele... –¶6. Measuring Health Disparities page of jpscanlan.com: http://jpscanlan.com/measuringhealthdisp.html –¶7. Scanlan JP. Getting it straight when statistics can lie. Legal Times Jun 28, 1993: http://jpscanlan.com/images/Getting_it_Straig... –¶8. Pay for Performance sub-page of Measuring Health Disparities page of jpscanlan.com: http://www.jpscanlan.com/measuringhealthdisp/...