For example, let us assume there are two hospitals, call them A and B. Hospital A administers opiate analgesics to 80% of all incoming patients, black or white, who present with symptoms of appendicitis. Clearly, no racism is present.
Hospital B administers opiate analgesics to 20% of all incoming patients, black or white, who present with symptoms of appendicitis. Clearly, no racism there, either.
Now, Hospital A is in a majority white community, where 90% of the patients are white; Hospital B is in a majority black community, with 90% of the patients being black.
Therefore, from Hospital A we have 72 white patents and 8 black patients (of 100) being administered opiates. From Hospital B, we have 2 white patients and 18 black patients being administered opiates.
However, when we combine the data, 74 white patients were administered opiates, but only 26 black patients. From two sets of data which clearly show no racism, we get a combined set which shows tremendous racism.
The difference is due to the hospitals, not due to racism.
Since the data from the study does not separate out the hospitals, there is no way to tell for sure if the difference is actually due to racism, or just due to the fact that different hospitals may have different policies on administering opiates.
Excellent and EXACTLY what I was hoping for on the thread.
You make a great point, and I believe the authors of this study cherry-picked the data just like that to fit their hypothesis.
There are just too many variables in real world medicine to accurately study this, especially with such a huge sample size - the variables would increase with all the different facilities, clinical presentation, physician diagnoses, wait times, transfer times, etc. the list could be endless almost.
Mrs. AV