2006 OPEN FORUM Abstracts
K.I.S.S. CORRELATION SPREADSHEET FOR BLOOD GASES
Scott
Steimke, RCP, Coastal Communities Hospital, Santa Ana, CA & Michael H.
Terry, RCP, RRT, Loma Linda University Medical Center, Loma Linda, CA.
Purpose: Respiratory Care Departments frequently are responsible for the analysis of
blood gasses but Respiratory Care Directors often struggle to find resources
for information about these requirements. Some labs are currently only running
the traditional QC programs, proficiency studies (With CTS or other organizations)
and whole blood correlation studies. Recently regulatory agencies have asked
some blood gas labs to present their analytical comparisons of their reportable
ranges and of their correlation studies. Good Laboratory Practice and CLIA '88
require comparative studies to define inter-instrument and inter-method
performance in the analysis of any analyte. CLIA '88 states this must be
evaluated at least every six months The comparative method however, is not
defined. Both JCAHO and CAP laboratory inspectors have asked to see linear
regression used for these comparisons. This abstract presents a simple
spreadsheet to collect, analyze and report this data.
Method: Duplicate analysis is performed on the two
instruments for comparison throughout the six month period and entered on the
data spreadsheet, (a minimum of twenty samples per reporting interval is
required). The statistical analysis is performed automatically and dynamically.
Thresholds for agreement in slope, intercept, correlation and R2
should be set in consultation with the Laboratory Medical Director. The chart
worksheet presents the information graphically and this is printed and
presented for review by the Medical Director every six months. In the event an
institution has more than two instruments for comparison, all instruments
should be compared to the primary instrument as designated on their proficiency
testing system.
Results:
A copy of this spreadsheet is available on request.
Conclusion: Blood
gas laboratory managers should become familiar with linear regression for
comparing instruments. This simple spreadsheet can be used as a template to
satisfy this requirement.