I'm hoping to get some feedback on a project I'm working on in terms of the methods we're using. I'll give a brief description of our project:

We're looking at patient volume for about N=9000 physicians. For each physician, I have the number of patients and days worked under two different conditions. Condition A is volume under 'A-Type Days' and Condition B is the volume under 'B-Type Days'. For each condition, I have the number of patients they saw (sum total) and the number of days over a single year. For example, I might have the following information for a given physician:

Worked a total of 25 "A-Type Days" and saw 100 Patients over this time. Therefore their A-Type average number of patients would be 100/25 = 4.

For the same physician, they may have worked a different number of "B-Type Days". For example, they could have worked a total of 3 "B-Type Days" and a total of 27 Patients in that time. Their B-Type average would then be 27/3 = 9.

I'm wondering how I could compare the average difference between the averages. My intuition tells me to use a paired T-Test to compare the difference in averages. I would therefore be evaluating the "average average difference" in patients from A-Type to B-Type.

Is this kosher? If not, would there be an alternate strategy? I'm able to extract the individual level data for each physician to see on which days how many patients they saw - right now I just have it in aggregate form.

Thanks for insights

cheers,