Results of Patient Blood Pressure and MD Decision
Using the data collected for ten patients by a local hospital, including the frequency of their visits, blood pressure, first assessment, second assessment, and final decision, I was able to create five vectors.
Freq <- c(0.6, 0.3, 0.4, 0.4, 0.2, 0.6, 0.3, 0.4, 0.9, 0.2)
bloodp <- c(103, 87, 32, 42, 59, 109, 78, 205, 135, 176)
first <- c(1, 1, 1, 1, 0, 0, 0, 0, NA, 1)
second <- c(0, 0, 1, 1, 0, 0, 1, 1, 1, 1)
finaldecision <- c(0, 1, 0, 1, 0, 1, 0, 1, 1, 1)
With these vectors, I made a side-by-side box plot comparing the low and high blood pressures, then a histogram of the frequency of each blood pressure range.
R Code:
boxplot(bloodp ~ finaldecision,
main = "Patients BPs & MD’s Ratings",
names = c("Low","High"),
xlab = "Final Decision",
ylab = "Blood Pressure")
hist(bloodp,
main = "Histogram of Patient's Blood Pressure",
xlab = "Blood Pressure")
The outcome from the box plots shows that blood pressure distribution generally aligns with the emergency unit's decision regarding immediate care for the patient. Most patients who had a higher blood pressure received a high final decision, meaning the patient has a higher chance of needing immediate care, while those with a lower blood pressure received a low final decision. I can also see that the IQR and outliers of the high final decision box plot are more spread out compared to the more compressed box plot for low blood pressure. This goes to show that while a higher blood pressure is usually the cause for immediate care regarding these patients, someone with a lower blood pressure could receive a high final decision too.
The histogram shows that 60% of the patients had a blood pressure between 50 and 150, 20% on the lower end between 0 and 50, and 20% on the higher end between 150 and 250. With the histogram being right-skewed, it makes sense that as a patient's blood pressure increases, the head of the emergency unit would decide those patients may require immediate care, resulting in a high final decision.


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