DQ Reponse: Data Collection, Misrepresentation, Situations

DQ Response
Your Name
September 17, 2016
Your Institution of Affiliation
Response to M.B’s post
I totally agree with your article about the need for strong statistical data in data analysis and decision making. I know that all of us are aware of the fact that most people neglect the numbers presented to them and instead they follow their instincts. Yes, subjective (and instinctive) thinking and decision making works most of the time in our daily lives. But, I believed that this method of using trial and error in order to learn should be discouraged in a field where human lives are at stake. The field of healthcare should mostly be based in objective, logical, fact-based, and scientific decision making to prevent, if not mitigate, the possibility of something going wrong. Aside from that, what strikes me the most regarding your comments is the example that you’ve given the quantity of abortion procedures in relation to the total services offered. Surely, providers should be more careful in the data that they consume. According to Alok Jha (2012), a correspondent of The Guardian, ‘false positives’ are now endangering the validity of research studies. From the perspective a healthcare provider, this is surely daunting since negative conseuquences might arise from this,
Response to L.G’s post
I can imagine the frustration that you are feeling and your sense of trepidation due to inaccuracies and misrepresentation of the data that the hospital where you work from gets. However, you’re right to be worried. We all know how important logical, scientific, and objective thinking is for our field. We just cannot take any chances and play a game of pin-the-tail-on-the-donkey and wait until we hit the right mark. However, what strikes me most in your post is your example on ‘intended misrepresentation’. As a health-care provider, I believe that your hospital (just like any other hospitals and health organizations) should promote delivering healthcare and healthy practices with great enthusiasm and organization. Careful representation should always be done despite a patient’s socioeconomic status. At first glance, simple and small scale misrepresentation might seem unimportant. However, According to Villasenor (2014), small problems like this would become more persitent and problemetic when repeated due to the phenomenon of Binomial distribution...