School this week was nicely short with us only having three days of actual class, but with that limited time, we still got some good things done. That being our telehealth lab, telehealth is is when the physician who provides a diagnosis is in a remote location and is questioning the patient through a screen. During this process, a nurse will take all the vitals and administer the test that the doctor orders. In the two telehealth scenarios, we did I performed as a nurse and another questioner behind the screen. In the first scenario, the patient had mono, which we couldn’t really figure out, as we weren’t digging deep enough with our questioning. The two tells were supposed to be the lymph nodes of the patient and also her swelling spleen. The second patient we were able to determine that they had asthma. This was determined based on the fact that the patient was a 30-year-old man and was in session because of over-exerting himself while running which had been his chronic position for months. My patient profile is a little more focused on the person themselves, as it is a simple covid diagnosis, but the patient is Amish so it’s more of a test to see if my classmates could ask the right questions in the right way. Driving the telehealth robot was probably the most fun part of the situation.
An example of a telehealth robot
Last week we had an assignment on big data in order to increase of knowledge of it. Essentially big data is large cogilations of data that is stored and traded between companies and organizations usually to push marketing. In the medical field, it can used to study how effective medicines and treatment plans usually are, but its main debates involve the collecting of people's private data from things like smartphones and watches.
More big data info: Big data refers to structured and semi-structured sets of data collected by different organizations for several different reasons. Big data is defined by three V’s: the volume of data, the variety of data types stored, and the velocity at which it is collected and processed. Big data analytics can be used in healthcare to personalize medicine by finding the best patient-specific treatment. This process reduces waste of resources and also lessens the cost of healthcare. While it has many uses on a personal scale big data’s values can also ascend to predicting epidemics and curing diseases. Data can be collected from devices like smartphones and watches, to draw a personalized picture of an individual in order to provide a more comprehensive healthcare package. The accumulation of data will be combined with thousands of others data to single out threats effectively and how certain genetic factors can affect one's life. A hurdle that big data must overcome is how this data is split up. Since data is collected by many different corporations and hospitals there is so much data that is separated and not shared effectively. Other obstacles to overcome in the implementation of big data include the creation of an infrastructure to house all of this converging data and educating people on how to take part in this revolution in healthcare, which can be seen as a violation of one's privacy rights.
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