1. Day to Day Management of Quality Control
Donna Walsh M.S. MT(ASCP)
Deaconess Hospital
Boston, MA

2. Why We Do Quality Control
Clients of laboratories services see the test results we produce as information and expect that information to be flawless, a very tall order. Statistical Quality Control practices is one of the tools of the trade utilized to approach reasonable levels of flawlessness.

3. Why We Do Quality Control
We are all familiar with classical approaches to quality control and the frustrations involved when these approaches fail and we need to troubleshoot methodology before releasing results.

4. Goal and Objective
This talk will review the basics of statistical quality control and some 'nuts and bolts' solutions to common QC problems.
Case studies will be used to illustrate effective strategies.

5. Goals of those Attending Today
Improving Day to Day QC Decisions & Documentation and Review of QC
Trying to get the days work reported out

6. Health Care Today Emphasis today is on cost containment
Laboratories have become cost centers as opposed to revenue centers.
QC costs involve cost of QC material (special controls can be very costly)
QC costs involve rework of out of control runs. (labor, reagent and control cost)

7. How Did We Get Here?
Levy-Jennings Plots were adapted from industrial use and have been in use to this very day since the 1960’s

8. Classic Quality Control
Principles of Statistical QC
Control Solutions are used to make Control Measurements
Control Measurements validate Unknown Measurements
Statistical Measurements Provide Guidelines for Acceptable Control Measurements

9. Classic Quality Control
Example:

10. Youden Plots
Looking at two controls at once

11. Ever Seen a QC Chart Like This?
Dot chart of the 90’s

12. Multi-rule Quality Control
Based on the concept that improved error detection is provided by selecting multi-rules over single-rule control procedures.
Widely used multi-rule control procedure is the one recommended by Westgard

13. Westgard Multi-Rule Quality Control Scheme
data No
12s
IN-CONTROL ACCEPT RUN No No No No No
13s
22s
41s
R4s
10X
Yes
Yes
Yes
Yes
Yes
OUT-OF-CONTROL REJECT RUN

14. Available Options Classic QC Multi-Rule very visual
tedious manual record keeping
often available as an on-line QC package for many automated systems
Multi-Rule
better error detection
more cumbersome for operator
easily adaptable to computer analysis

15. Practical “Nuts & Bolts” Options
Include Analytical Performance in Control Parameter (mean & SD) Decisions
Use NCCLS EP-5 to evaluate precision.
Adapt Control Measurement Frequency to Testing Needs
Set Medically Useful Control Procedures
Controls Levels at Medical Decision Points
Consider Control Measurements Quality Checks
Keep track of lot numbers, calibrations & maintenance procedures
Use this procedural information to assign causes to failures of quality checks

16. Case Studies .... practical QC
Incorporating NCCLS EP-5 data into QC decisions

17. Case Studies .... practical QC
Adapt Control Measurement Frequency to Testing Needs
NCCLS EP-5 calls for 2 replicates per run, 2 runs per day for 20 day. Adapt to testing situation - Example: Stat Lab has three shifts and three controls for Oximetry
Adopt CLIA definition of 24 hour = one run and assay 3 reps, for assay of new lot of control
Implement different QC levels on each shift for periods of stable operation.

18. Practical ‘Nut & Bolts’ HINT
Many of today's testing procedures have much improved analytical performance. You can take advantage of this improved accuracy and precision in the design of your QC protocol.

19. Case Studies .... practical QC
Set Medically Useful Control Procedures
Example: Digoxin

20. Case Studies .... practical QC
Set Medically Useful Control Procedures
Example: pH Reference Range is (range = 0.07)
Control Material A; standard deviation = ; /- 2 sd = 0.056
Control Material B; standard deviation = ; /- 2 sd = 0.020
Control Material B is more costly than Control material A
But it is costly to walk
too fine a line...

21. Practical ‘Nut & Bolts’ HINT
Set the % CV tight or use a control protocol that has improved precision at Clinically Significant Decision Levels
Or put differently, make sure you have an appropriate target for the situation.

22. Case Studies .... practical QC
Consider Control Measurements Quality Checks
Keep track of lot numbers, calibrations & maintenance procedures
Use this procedural information to assign causes to failures of quality checks
Best way to document assignable causes of mean & sd changes
lot numbers

23. Case Studies .... practical QC
Example: Preventative Maintenance Appropriate for Workload
Drugs by Fluorescent Polarization

24. Case Studies .... practical QC
Increase PM frequency

25. Case Studies .... practical QC
Example: new lot number of reagent

26. Case Studies .... practical QC
Example: new lot number of reagent
shift in QC values correlated with change in lot of reagent.
check to see if there is a shift in unknowns (samples) or standards
matrix effect if shift is only in control samples
adjust QC mean to account for shift and avoid unnecessary repeat work.
Lot numbers
xx0226
xx0228

27. Case Studies .... practical QC
Long standing shifts may not be obvious until a lot change causes a shift out of control
Check Year to Date and or lot to date QC for any shifts or trends.
lot change

28. Case Studies .... practical QC
Example: Glucose - shift in current month away from year to date when new electrode used.

29. Case Studies .... practical QC
Example: Change in QC post calibration of new lot of Calcium
Lot related shift post cal on Recal on 5-20 due to bias in pt. checks
calibration done

30. Case Studies .... practical QC
Example of shift with no assignable cause
Lithium by ISE
Trouble shooting
- new control
- recalibration
- new electrode
- fresh reagents
NOTHING
WORKED!!!

31. Case Studies .... practical QC
Lithium Statistical QC information

32. Practical ‘Nut & Bolts’ HINT
Running control samples is a check on quality; they do not control quality. You must do that yourself.
There is NO such thing as a QC Crystal Ball
REPORT RESULTS!

33. Recommendations View the test results we produce as information
Include Analytical Performance in Control Protocols
Set Medically Useful Control Procedures
Make use of on-line QC packages
facilitates statistical quality control calculations
provides visual dot charts for operators

34. Recommendations Consider Control Measurements Quality Checks
Keep track of information that could validate a change in the statistical QC parameters
Change QC parameters promptly when the situation warrents
Use Patient Check Data to help in QC decisions

35. Benefits Accurate and Reliable Reporting of Patient Test Data
Well Documented Quality Control Program
Day to Day and Cumulative QC data will be more useful.