The use of probability in public health hospitals as a means to protect and promote public health has become a rising epidemic in society today. The basis for using probability in public health hospitals is the usage of common sense and causal reasoning. Whether to save time and attend to a large number of patients or just out of sheer ignorance, basing the patient’s description on the pattern and frequency of the health events in a given population does not guarantee 100% results.
There are three characteristics of probability, place, person, and time. Probability-based on place includes things like the environment that one is usually located, geographical violation, and urban-rural difference. While on the other hand, the probability of a personal characteristic by demographic factors such as occupation, race, age, sex, socioeconomic, and marital status (Peck & Devore, 2012). The probability of time is characterized by, hourly, daily, a seasonal or annual occurrence. Based on these characterizations, medical practitioners feel they can effectively prescribe a suitable dose for a patient.
In public health practices, when doctors use terms that seem rather obscure instead of basing findings on facts that is when a patient may know that the doctor is using probability.
Or example if someone who smokes enters the doctor’s office with a persistent cough or having difficulties in breathing, the doctor may use the knowledge that is known and end up prescribing something like lung cancer. They would probably feel that since the hospital is public, and most patients cannot afford to pay properly for the medical care, then it would be a waste of both time and energy to do the research. According to Wallis famous quotes, “statistics may be defined as a body of methods for making wise decisions in the face of uncertainty”.
Using statistics and probability as in practice in public health may cause a problem when applied to individuals in a clinical setting. The reason behind it is, the patients in a clinical setting would be prescribed the same medication.
In some cases, this would be Ok, but the same way the medical practitioner feels that there is a probability of those from the same population suffering from the same illness, there could also be a probability that they do not. This may cause problems to those who have a different ailment as it may take longer to be discovered or worse still may not be discovered at all. This puts life in danger and the medical industry to have a offensive name.
Different bodies in the clinical department have different task that they perform. MD, RN, therapist, pharmacists, and public health practitioner deal with different things in the clinical department. For example, the task performed by a pharmacist and a public health practitioner totally differ. A pharmacist provides prescribed medicines, assess the prescription if it is correct and dispense the medication in accordance with the training that they have obtained.
They should advice the patients about the selected dosage and the side effect that it contains. At the same time, they should analyze how the patient is progressing while consuming the medication. Public health practitioner on the other hand, is the one who takes the patient and analyze the illness they have. They also provide diagnosis, preventive health care service and therapeutic assistance (Turnock, 2006).
Probability can be applied in public health by basing facts to a group rather than an individual (Rothstein, 2003). Probability theories create inferential statistics, which has become the main source of information and data in public hospitals. Public health has been based with what the doctors know and what they want to know.
References
Peck, R., & Devore, J. L. (2012). Statistics: The exploration and analysis of data. Boston, MA: Brooks/Cole, Cengage Learning.
Turnock, B. J. (2006). Public health: Career choices that make a difference. Sudbury, Mass: Jones and Bartlett Publishers.
Rothstein, W. G. (2003). Public health and the risk factor: A history of an uneven medical revolution. Rochester, NY: University of Rochester Press.