Vulnerable populations at risk for health care

In the aftermath of a presidential campaign in which health care was a major issue, we are all acutely aware that our health system has flaws.

The CDC estimates that some 53 million people in the United States were uninsured for some period of time in 2007. That is more than 17 percent of the population.

Something needs to be done, but what? As always, an effective solution has to stem from an accurate perception of the problem. In this case, that perception involves an understanding of vulnerable populations.

Vulnerable populations are groups that are more susceptible than the general population to risk factors that lead to poor health outcomes. Common risk factors include race/ethnicity, socio-economic status, cultural factors and health insurance.

Researchers at the Bloomberg School of Public Health have focused their efforts on understanding the factors that lead to health disparities in our country. In a paper published this month in the Journal of Public Health Management and Practice, Leiyu Shi and his colleagues from the Bloomberg School, along with Jenna Tsai from Hungguang University in Taiwan, presented a new model of vulnerability that provides more insight into the causes of the vast differences in health between sectors of our population.

Their General Vulnerability Model builds on previous efforts that incorporated community and personal risks into evaluation of vulnerability. The General Vulnerability Model seeks to assess both overarching risks and specific risks in order to gain a full understanding of levels of vulnerability.

Older models tended to isolate specific risks, therefore disregarding the impact of multiple risk factors, which are presented in this paper as fundamental to an accurate depiction of the overall problem of health disparity.

Why go into so much detail about what makes a particular person or population more vulnerable than another? In understanding how individual factors combine to produce levels of vulnerability that can be more than just the sum of their parts, professionals can decide which groups are the neediest and direct energy and funds toward intervention in those specific areas, and therefore, can take the most efficient steps toward decreasing disparities.

Furthermore, researchers can determine which trends apply across the spectrum of vulnerable groups and which vary by race or ethnicity, which can also aid in designing interventions.

Shi and his group found that having multiple risk factors leads to worse health outcomes than having just one risk factor and that certain combinations of risk factors are much more dangerous than others.

In all cases, measures of health worsened with increasing number of risk factors. In a specific case, measuring factors that lead to having unmet health care needs, chances of having unmet needs doubled when going from zero risk factors to one, but tripled when going from one risk factor to two.

Particular pairings of risk factors were far more damaging than other combinations. Only 54 percent of people with vulnerability profiles of having no regular source of care and no insurance were screened for high blood pressure in a year, while 86 percent of people whose vulnerability profile included low income and low education were screened.

Health outcomes can vary drastically by the number of vulnerability factors and between different sets of vulnerability factors. Awareness of this hierarchy in vulnerability could lead to highly focused interventions that are more effective in decreasing overall disparities, which could help the 53 million uninsured.

For example, showing that lack of insurance is a more serious risk factor than others for chances of getting blood pressure screening highlights the issue of insurance as an area of focus for increasing overall equality of health. Identifying which factors are the most important can lead us to better strategies to decrease health disparities.