Introduction
The concept of population health management refers to understanding and managing health outcomes at the population, rather than the individual level. Cousins et al (2002) highlight that risk levels for different ailments and conditions can vary by populations, so breaking down a population demographically can help to understand how risk varies. Their study showed that predictive modeling can be used to identify risk levels for different conditions among different populations. This underlying logic is the basis for the concept of population health management. If risk levels vary by population, then it can be easier to understand underlying causal or contributing factors. From there, tactics can be developed to help deal with those risk factors, addressing them and therefore reducing the risk of that condition among that particular population. Population health management is, therefore, a powerful tool to improve health outcomes, because it leads to more preventative approaches, rather than treating a condition once it is already occurring.
The Underlying Logic of Population Health Management
Kapp, Oliver and Simoes (2010) explore the concept of population health management in their study. They surveyed women in Missouri to understand some of the underlying lifestyle factors for cancer. Their study showed, among other things, that certain segments of the population were less aware of lifestyle factors that contributed to cancer than other segments. First, they were able to do this by targeting a fairly narrow segment of the population – women in a certain part of Missouri between the ages of 35-49 who had not had a personal history of cancer. Their study then gathered some demographic information, including education level. From this, they were able to determine that education level in particular has an influence on the degree of knowledge that the respondents had regarding lifestyle influences on cancer.
Lifestyle factors are by no means the only contributing factors to whether a women gets breast cancer, but there are lifestyle factors that contribute. The underlying logic of the Kapp study is that some lifestyle factors are preventable. Where there is higher awareness of lifestyle factors that a person can control, they are more likely to do so, and this can explain why some conditions occur more in certain segments of the population. The United States has relatively poor health outcomes for a developed nation, and while there are any number of reasons for this, lifestyle habits among the nation's poor and undereducated are definitely a contributing factor – obesity is in particular a driver of poor health outcomes, and is almost entirely controllable for most people.
Cramm and Nieboer (2016) further explore the issue of population health management. They argue emphatically that disease management is not the solution to public health issues. By tackling disease on the level of the individual, that person already has the disease. First, when looking at statistics, outcomes don't change much once a person has something, other than when treatment is improved. Advances in treatment, however, are typically diffused across the developed world quickly, so the United States cannot gain much advantage statistically by innovating treatments. The only true way to improve health outcomes on a broad level, they argue,...
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