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

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.

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.

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.

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

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)

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

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

Classic Quality Control Example:

Youden Plots Looking at two controls at once

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

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

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

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

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

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

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.

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.

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

Case Studies .... practical QC Set Medically Useful Control Procedures Example: pH Reference Range is 7.37-7.44 (range = 0.07) Control Material A; standard deviation = 0.014; +/- 2 sd = 0.056 Control Material B; standard deviation = 0.005; +/- 2 sd = 0.020 Control Material B is more costly than Control material A But it is costly to walk too fine a line...

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.

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

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

Case Studies .... practical QC Increase PM frequency

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

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 5-1-95 xx0226 5-15-95 xx0228

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

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

Case Studies .... practical QC Example: Change in QC post calibration of new lot of Calcium Lot related shift post cal on 5-10. Recal on 5-20 due to bias in pt. checks calibration done

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!!!

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

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!

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

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

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.