Net of Information

In order to describe how their public heath system works in the UK they created a web. The web allows for more information than a traditional graphic. You can see which offices work with each other and which groups a central to the system working. The web its also color-coded by employment sector so that the breadth of ways public health is impacted can be showed. I think this graphic is especially clever because they don’t want to let the public slip through the web their weaving and this is clearer because of all the connections between groups.

Fig. 1. Network graph describing the public health workforce in a large UK conurbation, describing employers, employees and board memberships. 

https://www.researchgate.net/figure/223975843_fig1_Fig-1-Network-graph-describing-the-public-health-workforce-in-a-large-UK-conurbation

 

Observational Study

The study I examined is Sex Differences in Reported Pain Across 11,000 Patients Captured in Electronic Medical Records. This study seeks to answer the research question, “Do women feel more, less, or equal pain than men.” The study was a retrospective study analyzing 11,000 patients charts from Stanford area hospitals and clinics divided into groups by gender (56.2% female, 43.8% males). The study excluded children. The cases were stratified by disease and the patient reported pain scores were compared for those diseases with at least 41 patients of each gender.
The researchers collected data from a variety of medical practices in the Stanford area. They then took only the pain scores, disease, and gender from the case. The data was then analyzed using several method including a t-test. Through maintaining a large n, the study was able have a study on a larger scope than any other previous to it. Such a study wouldn’t have been possible to complete experimentally without great cost so a retrospective study was highly useful.
The pain score of the female group was higher for musculoskeletal diseases and respiratory diseases. This supported other gender based pain study’s findings. Several potential problems with this study were that it doesn’t apply to pediatric patients. Additionally, some pain scores started as a 0-5 scale and others as a 0-10 scale in mixing these scores could have caused complications. This study suggests that more research should go into such studies on the experience of pain including tests that are more experimental rather than observational as this one was in order to determine which gender experiences more pain given the same amount of stimulus. Still this study was highly effective due to the very large sample size.

References:
Ruau, David et al. “Sex Differences in Reported Pain across 11,000 Patients Captured in Electronic Medical Records.” The journal of pain : official journal of the American Pain Society 13.3 (2012): 228–34. Web. 22 Sept. 2016.

Why Do We Care about Biostatistics?

The field of biostatistics inhabits a unique niche environment in the field of science which is both extremely useful, but also broadly impactful. Biostatistcs is unique because normally when one thinks of a science involving a high level of math, physics, or possibly chemistry, would come to mind. However, mathematics, statistics in particular, is just as necessary and important in biology. Since biostatistics, as a single region of biology, brings the majority of the mathematics to its greater field, Biostatistics has an even greater importance than the mathematics in a chemistry or physics course. On a more personal note, biostatistics appeals to me a student who is a chemistry major and a biology minor, because it satisfies my desire to quantify, and analyze as I often get to do in chemistry. Further, biostatistics has the added benefit of being about biology which among other subcategories includes medicine, and dentistry the field which I hope to someday research in. Biostatistics is important to me because of its versatility, utility, and applicability to my future.

Biostatistics is used in a wide variety of biological fields from the studying of the largest ecosystems or even concerns of the entire planet all the way down to analyzing the use of a single protein inside an already microscopic cell. Biostatistics is used for a variety of applications, including ecosystem modeling. It has also been used to understand the utility of ecosystems and feedback loops involving the environment. The economic value of the services an ecosystem can provide to humans as opposed to the raw materials we could rob from that environment is a difficult both moral and mathematical problem to solve. Biostatisticians have been able to help prove the innate value of a maintained ecosystem which has led to greater preservation efforts. Similarly, biostatistians have also been able to weigh in on the SLOSS (Single Large or Several Small) preserve debate with some statistics backing up either side of the debate depending on the ultimate goal.

In addition, to these very large scale research questions biostatistians also play a huge role in the portions of biology pertaining to humans. Biostatians work on all parts of the process of health problems in the world today. From determining if a problem is existent and how large it is, to determining which populations are at risk and why, to finding possible targets as well as potential treatments, to evaluating each of those treatments’ effectiveness in cell level testing, animal testing, testing in the human population, and even the final effect of a new medicine on the human population as a whole, biostatistics is important if not necessary. Medical researchers, doctors, and public health officials need biostatistics because they seek to cure illnesses and help save lives, but to know if they are actually being effective they have to do the math. Biostatistians help to find the links between lung cancer and smoking, childhood obesity and diabetes, mosquitoes and certain diseases among other problems. Without statistics the correlation between none of these could be determined, only guessed at. Biostatistics proves medicine makes the world a healthier place.

This leads to why I want to learn about biostatistics.  I aspire to eventually enter the field of academic dentistry (dental research) and just as biostatistics is highly applicable to medicine it is also very important to dentists and the field of dentistry. In fact, it is of such great importance that many dental schools now require a course in biostatistics and how it relates to dentistry. If I wanted to be a general dentist biostatistics would be important for me so that I would know the appropriate way to interpret statistical data when reading about a new technique or product I was considering using on patients. However, as someone who wants to go into the research side of dentistry it is far more important because as a researcher I will not only have to be able to interpret the statistical analysis already done by others and published, I will also need to be able to do such analysis myself. Interestingly, in 2014 there was a survey completed of faculty and post-graduate students at a dental school to see how biostatistics was perceived by dental professionals. In this study it was found that 69.8% of respondents believe knowing biostatistics will help their career. Further 64.3% of the respondents thought biostatistics was a difficult subject. I feel that since biostatistics is eventually going to be an integral part of my future career learning about biostatistics now will both help me eventually be a better dentist and dental researcher. Biostatistics applies to a large number of diverse fields and importantly it is useful in the field I hope to eventually research in, hence, I want to study biostatistics as should many others to whom this course is both useful and applicable.

Works Cited

“Biostatistics and Research Design.” College of Dentistry & Dental Clinics. University of Iowa, n.d. Web. 2 Sept. 2016.

Perception of Dental Professionals towards Biostatistics. International Scholarly Research Notices, 2014, 1–6. http://doi.org/10.1155/2014/291807

Schwartz, M. W., & Mantgem, P. van. (1997). The value of small preserves.

Smith, R. I., Dick, J. M., & Scott, E. M. (2011). The role of statistics in the analysis of ecosystem services. Environmetrics, 22(5), 608–617. http://doi.org/10.1002/env.1107

Uncpublichealth. “Careers in Biostatistics.” YouTube. YouTube, 14 Apr. 2010. Web. 02 Sept.