Pathology slides generated between tissue types

Hello all, I am a resident physician in pathology, and I have a question regarding a quality improvement/research project. Surgical resections for breast cancer are thought to require more pathologist work (i.e. time), due to an increased number of glass slides generated that the pathologist has to look at under the microscope in order to render a diagnosis, than other tissue types. I am trying to compare the # of slides generated between these two groups (assuming it takes the same amount of time to look at a single slide regardless of tissue type, and factoring out case complexity, consultation, other variables).

For example, we found that 580 breast specimens generated 1559 slides, compared to 580 non-breast specimens in the same time period generating only 679 slides. I.e. breast cases generated 2.296x the amount of slides, thus corresponding to more time spent on breast cases than non-breast cases. This may seem silly (or not possible), but is there a simple way to calculate how significant these results are with a p value? Thanks.
If the rates for the two groups were actually the same, you would have expected to see 1119 in each group. So your question is how unlikely is a split of 1559 vs 679 if the groups are in fact equivalent? This is a chi square test whose p value is best expressed simply as p<0.001. kat


Not a robit
I would plug the raw data into a count model (e.g. Poisson regression) with predictor (breat tissue Y/N). At the end you will get a relative rate with 95% CI. You should stop using pvalues while you are early in your career, they are considered a faux pas in medical research these days and will be whittled out in the coming years. You would interpret the relative rate much like an odds ratio. The model would also allow you to control for covariate imbalances between the tissue groups that may influence the diagnosis and outcome (e.g., elevated BMI, etc.).