Stats
Using APR-DRGs for risk adjustment (May 24, 2006).
Category: Covariate adjustment
The 3M company, famous for Post-It notes, among other things, has a
division for health information systems. One of their products is software
that produces classifications called "All patient Refined Diagnosis Related
Groups" or APR-DRGs. These APR-DRGs are computed from information typically
collected as part of the billing process. Patients in a common APR-DRG
represent a reasonably homogenous set of patients with respect to type of
condition and severity of disease.
This product has both financial and research applications. In the research
realm, you might want to define a narrow group of patients with a reasonably
homogenous risk profile. This would allow you to use stratification or
matching on the APR-DRG so as to improve the precision of the findings.
You might also have an observational study where you know that there are
some imbalances with respect to prognostic factors. You could use the APR-DRG
as a covariate to insure that any differences in risk are adjusted for in the
analysis.
There is an increasing demand for "report cards" for physicians and
hospitals that will allow patients to make informed decisions about where
they get their health care from. These report cards need careful adjustment
for risk levels, because there is a well established tendency for the better
individuals and groups to get referrals for the more complex and difficult
patients. If you don't perform an appropriate risk adjustment, you end up
seeing the worst outcomes among the very best groups and individuals.
I hesitate to recommend commercial products, because most researchers are
starving for funding, but this product looks pretty good. I had to use it for
a research study a while back, and may end up using it again.
The 3M Health Information System group has a web page at
and the description of the APR-DRG system is at
Here's an example of a publication that examines APR-DRGs and shows that
this grouping can account for about 16% of the variation in length of stay.
This web page was written and was last modified on
09/24/2007.
