This Article Focuses on Determining How Economic Status, Geographic Location, Ethnicity

This article focuses on determining how economic status, geographic location, ethnicity, foreign-born individuals, and being in the elderly population effects travel to an emergency department (ED). Shen and Hsia (2010) analyzed the change in driving times from 2001 to 2005 in communities within the continental United States. Vulnerable populations were of particular focus, meeting criteria of lower economic status and being an ethnic minority. Zip code-level data was used from the 2000 census to identify the communities to study. Additionally, Shen and Hsia (2010) calculated the driving time between each community and the nearest ED. Using three classifications of, “did not increase, increased by less than 10 minutes, or increased by 10 or more minutes,” Shen and Hsia (2010) would make connections between geographic region and driving times to the nearest ED to examine any changes over the course of the study.

A total of 28,520 zip codes were used in the study sample with a population size of 272 million people. Shen and Hsia (2010) found that more than 95 percent of the total studied population had the same or improved access to an ED during the study time. However, the change in access to an ED was not the same throughout all regions of the United States. First, the Midwest saw the smallest change in deteriorating access for both urban and rural communities. Secondly, the South had more communities that experienced an increase in driving time by more than 10 minutes. Also, urban communities that saw an increase in drive time to an ED were more likely to be poorer and had a higher number of unemployment in the community. Interestingly, urban communities that experienced an increase in drive time to the nearest ED, those patients had better access to other healthcare resources like more hospitals and more federally qualified health centers. Concluding, rural communities with lower income status saw deterioration in access to an ED compared with higher-income rural communities. Within the lower income rural communities, if there was a higher population of Hispanics, the Hispanic population was 2.67 times more likely to experience increased driving time.

The use of the stacked bar graph was more appropriate for this study’s comparison of access to EDs, compared to two pie charts, because the variables in this study were dichotomous. As stated by Sullivan (2012), “Dichotomous variables often are used to classify participants as possessing or not possessing a particular characteristic, having or not having a particular attribute” (p. 37). In this study, the variables are regarding increase in driving times based on demographic and economic status. Also, Sullivan (2012) indicates that bar charts are the best forms of representing dichotomous variables.

When Shen and Hsia (2010) discuss the relative risk ratio of low-income communities in urban areas, the exposed population was the residents in the low-income community who experienced higher driving times and the unexposed, or reference, group were those living in high-income communities who experienced no change in driving time. The relative risk ratio of communities with a high share of foreign-born members in rural areas was .70. The exposed population in this ratio is the population of foreign-born individuals who live in rural areas that experienced an increase in drive time to an ED. The unexposed population would be the low share of foreign-born population. In other words, the reference group would be the communities who have a lower population of foreign-born individuals who saw no increase in driving time to the nearest ED. This risk ratio indicates that foreign-born individuals living in rural areas were .70 times more likely to see an increase in drive time by 10 minutes.

References

Shen, Y. & Hsia, R. Y., Changes in emergency department access between 2001 and 2005 among general and vulnerable populations.American Journal of Public Health, 100(8),1462-1469. doi:10.2105/AJPH. 2009.175828.

Sullivan, L.M., (2012).Essentials of biostatistics in public health. (2nded.).Burlington, MA: Jones & Bartlett Learning.