Pediatric Informatics: Computer Applications in Child Health (Health ...

100 W.H. Drummond et al.
Table 8.2 (continued)
Children’s Hospital
of Pittsburgh
Children’s Hospital
of Seattle
Study results
Methodology Retrospective design Retrospective design
Comparison of “pre” and “post” There are no statistically There are multiple differences
groups
significant differences in the pre and post
between the groups except groups. Most notably age
for the number of patients (90.5 versus 83.25 mos)
with CNS disease
and the incidence
(288 pre, 89 post)
of asthma, cancer,
pneumonia, and sepsis
Mortality rate Mortality statistics
Mortality rate (all patients):
( inter-facility transfers pre 4.22–post 3.46%
to PICU):
Mortality rate (Inter-facility
Pre 2.80% (39/1394) transfers to PICU)
Post 6.57% (36/548) Pre 9.60–post 6.29%
Factors affecting mortality Patients younger, history
of prematurity, direct
admission to PICU
Not evaluated
Adjusted for confounding factors Yes No
Conclusion Unadjusted mortality rate is There is no significant
significantly higher in the change in unadjusted
“post” CPOE group. This mortality between the
conclusion is likely the “pre” and “post” CPOE
result of multiple socio- groups. However, this
technical factors rather comparison of unadjusted
than an isolated CPOE mortality rates may be
system
invalid due to significant
differences between the
pre and post groups, and
the failure to adjust for
confounding factors
attention to recognizing work flow changes needed for system adaptation to
change generated by IT implementation.
One of the fundamental differences between the two PICU CPOE installations
was the substantial preliminary effort by Seattle in building pediatric ICU order
sets. At Pittsburgh, a single order took 1–2 min. In Seattle, an entire “pre-built”
set of admission orders could be entered in 5 min. Even though clearly faster than
Pittsburgh, 5 min is still a fivefold increase in provider effort compared to paper
versions of the same order set. Accounts from both hospitals support the time saving
value of pre-built order sets versus single order entry. In the future, formal time,
effort, and workflow analyses must be used to specify and build more efficient
archival software, better user interface utilities, team workflow support, and