BOOKS OF RtfiDIfGS - PAHO/WHO

C- ' MIX DEFINITION BY DRG
TABLE 11.
- 56 -
No. of Per Cent
Variable Groups Reductiba
age 3 1 ..05
oper2 1 0.0
dxl 1 0.0
%ex I 0.0
down ofthe surgical groups on the basis of
secondary diagnosis. Moreover, in light of
one of the major objectives of' keeping the
total number of classes low, additional
groups formed at this stage of the partitioning
of Urinary Calcultus patients would be
of questionable value. Therefore, the 2
surgical grotups were not divided further
but were considered terminal groups.
Step 5
The 2 subgroups formed from the nonsurgical
cases on the basis of presence or
absence ofother díagnoses were evaluated
to determine if they should be partitioned
further or left intact as terminal groups.
The algorithm was applied and produced
the results shown for the nonsurgical cases
without multiple diagnoses. The algorithm
produced the results listed in Table 11 for
the nonsurgical cases with multiple
diagnoses.
With respect to the nonsurgical cases
without multiple diagnoses, both sets of
groups font - - ,n the basis of age and secondary
sa ,ncal procedure, respectively,
MEDICAL CARE
were determined unacceptable. In each
instance, more than 95 per cent of the ob.
pervations fell into the first group, leaving
the second group with fewer than 25 cases.
For the nonsurgical cases with multiple
diagnoses, the 3 groups formed using age
levels were considered as potential sub..
groups. The age levels detining the bound.
aries of the groups were 66 and 70. This
partition was rejected for reasons similar to
those above, namely, the lopsided distribution
ofl cases in thle groups. Almost 90 per
cent of the observations had an age under
66.
Thus, the nonsurgical groulps with aind
without multiple diagnoses were consíidered
terminal groups.
We conclude, then, that specific surgical
procedures and the presence of multiple
diagnoses were ímportant variables in
predictir.g length of stay for urinary calculus
patients. The 4 DRGs formed were
significantly different (a = 0.01) with respect
to their average lengths of stay and
are clinically interpretable. To be sure, by
overruling some ofthe partitions suggested
by the algorithin, a certain anmoulnt of
explanatory power was sacrificed. But, the
trade-off was generating a reasonable
number of subgroups or DRGs which
could be interpreted from a medical
perspective. Figure 2 presents a descriptive
summary ofthe length-of-stay distributions
for the groups formed as part of the
partitioning process in this example.