The book under review is integral in expanding a learners understanding of how statistics and statistical methods are applied in the healthcare setting. Chapters three and four of the course book have provided us with deeper insights into statistics in healthcare management. The three chapters focus more on the application of biostatistics in public health management rather than introducing the concepts. In chapter three, we focused on the process of quantifying the extent of diseases. In this chapter, we explored the concepts of prevalence and incidence by contrasting and comparing the two concepts. This also included actual application of the two conceptions in the process of quantifying the extent of diseases by studying how they can be computed. In the same chapter, we learnt different methods of comparing the extent of disease between groups. In chapter four, we differentiated dichotomous, ordinal, categorical, and dichotomous variables. This included learning statistical methods of comparing the extent of disease through relevant computations.
Critique of the Articles’ Content
The articles content is insightful on the grounds that it comprises of both descriptive and illustrative methods of delivering content to the learner. Moreover, the content is summarized into precise and clear text and mathematical calculations thus making it more comprehendible. For instance, the first article makes it easier to compare and contrast prevalence and incidence. As illustrated in the first article, prevalence is the number of people suffering from a disease at a particular time. This is obtained computationally by getting the ratio of the number of people with the disease to that of the total of the baseline. The ration can then be converted into percentages for easier interpretation. On the other hand, incidence is the likelihood of contracting a particular disease when living among people with the disease ( Sullivan, 2011) . Cumulative incidence can be computed by obtaining the ratio of people who contract a disease to that of people at risk of contracting the same disease.
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Due to the assumption that statistical variables have a specified level of measurement, ordinal and categorical variables are important in biostatistics of healthcare management. For example, categorical variables have more than one categories that are not ordered intrinsically. This way, these variables can be useful when creating samples based on variables such as gender and marital status. On the other hand, ordinal variables like categorical variables have more than one categories but can be used in sampling where they are ordered clearly ( Stommel & Dontje, 2014) . For example, they can be used in categorizing health status of individuals on an ordered scale of say poor to excellent where each category is assigned a specific value.
After learning the content of the articles, I realized that my initial knowledge regarding comparing the extent of disease between groups was not quite comprehensive. For example, without prior knowledge of prevalence, incidence and their associated ratios, it is hard to compare the extent of disease between groups. These computational ratios enhance the process of comparing the extent of disease between groups by providing simplified values ( Sullivan, 2011) .
Conclusion
The articles make the learner enlightened on ways to calculate different ratios that are important in exploring the impacts of diseases on a particular group of people living in a specified region at a particular time. Additionally, the learner is equipped with skills to compare the extent of disease between different groups of people. This is possible through application of computations involving prevalence and incidence with deep knowledge of variables such as dichotomous, ordinal, categorical, and dichotomous variables.
References
Stommel, M., & Dontje, K. J. (2014). Statistics for advanced practice nurses and health professionals . New York, NY: Springer Publishing Company.
Sullivan, L. M. (2011). Essentials of biostatistics in public health . Sudbury, MA: Jones & Bartlett Learning.
