laboratory management and quality assurance

LABORATORY MANAGEMENT LABORATORY MANAGEMENT and QUALITY ASSURANCEand QUALITY ASSURANCE

Introduction

“The analytical laboratory provides qualitative and quantitative data for use in decision-making. To be valuable, the data must accurately describe the characteristics and concentrations of constituents in the samples submitted to the laboratory. In many cases, because they lead to faulty interpretations, approximate or incorrect results are worse than no result at all.”

– HANDBOOK FOR ANALYTICAL QUALITY CONTROL IN WATER AND WASTEWATER LABORATORIES, EPA 1979

Quality Assurance - Defined

“Quality Assurance (QA) is a set of operating principles that, if strictly followed during sample collection and analysis, will produce data of known and defensible quality.”

“The Accuracy of the analytical result can be stated with a high level of confidence.”

– STANDARD METHODS, 18th EDITION, 1992

Outline

• Laboratory Management

• Introduction to Quality Assurance Concepts

Laboratory Management

• Who should be involved in laboratory management and quality assurance?


• Everyone involved with the lab:– Person sampling– Person running the test– Person washing the glassware– Person doing maintenance on the instruments– Person interpreting the results


• Quality Assurance Program– Staff Organization and Responsibilities– Sample Control and Documentation– SOP for Analytical Methods & Procedures– Analyst Training Requirements– Equipment Preventative Maintenance– Calibration Procedures– Corrective Actions– Internal Quality Control Activities– Performance Audits– Data Assessment for Bias and Precision– Data Validation and Reporting


• Keys to Quality Assurance Program:– Documentation– Communication– Training– Cross-Training– Updating

Sample Control and Documentation

• A record keeping system (paper trail, chain of custody) should track samples before, during, and after analysis.

• Everyone involved needs to understand and utilize the system.

Sample Control and Documentation

• Efficiently process information through lab system while minimizing actual time spent recording data

• Keep it simple!– Collect only the information you need

Suggested Information - Field

Date

Conditions

Collected By

Site

Code

Comments:

Hayfield Site Influent

04-15-02 8am

HS IN 1 Jim S.

Sunny, 75F

pH adjusted to <2 with nitric acid

Grab sample

Suggested Information - Lab

• Date of analysis

• Laboratory technicians performing the analysis

• Results (including units)

• Analytical comments: based on need to know– Dilutions– Interferences encountered

SOP for Analytical Procedures

• Describes method in enough detail that an experienced analyst could obtain acceptable results.

SOP for Cleanliness

• Labware cleaning procedures should be documented and all persons involved should be trained.

http://ecommerce.hach.com/webapp/commerce/command/ExecMacro/prodlgimage.d2w/report?image=Lp-FlasksVolumetric.jpg

Routine Cleaning Procedure

• Rinse glassware with tap water.• Clean glassware with a solution of water and

laboratory detergent.• Rinse the glassware with an acidic solution

– 1.0 N HCl– 6N HNO3 for regulatory reporting of heavy metals

• Rinse glassware at least 3X with DI water.

Routine Cleaning Procedure (cont.)

• Glassware should be stored in a manner that prevents contamination from dust particles.

• Prior to analysis, rinse the glassware with sample to prevent contamination or dilution.

SOP for Instrumentation Maintenance

• Preventative maintenance is the key to optimal instrument performance.– Follow any maintenance program and guidelines

suggested by the instrument manufacturer.– Instrument manual

• Reduces instrument downtime

• Service Contracts with Manufacturers

Analyst Training

• Sample Logging and Preservation

• Method SOPs

• Measuring– Use of Volumetric glassware

(pipettes, graduated glassware)

• Weighing / Use and care of Analytical Balance

• Washing and Care of Glassware

• Operation of Analytical Instrumentation

• Data Handling and Reporting

• Quality Control Activities

• Safety

QUALITY ASSURANCE QUALITY ASSURANCE CONCEPTSCONCEPTS

Quality Assurance

Quality Control

• Certification of Analyst Competence

• Recovery of Known Additions

• Analysis of Standards

• Analysis of Reagent Blanks

• Calibration with Standards

• Analysis of Duplicates

• Maintenance of Control Charts

Quality Assessment

• Performance Evaluation Samples

• Performance Audits

Certification of Analyst Competence

• Demonstration of acceptable precision and accuracy for each analyst

• Minimum of four replicate analyses on a known standard– Look for acceptable accuracy and precision– Acceptable limits vary per analytical method

• ‘Demonstration of Capability’

What is Accuracy?

• Accuracy is the nearness of a test result to the true value.

What is Precision?

• Precision is how closely repeated measurements agree with each other.

• Although good precision suggests good accuracy, precise results can be inaccurate.

Imprecise and inaccurate

Precise but inaccurate

Accurate but imprecise

Precise and accurate

Quality Assurance

Quality Control








Quality Assessment



Standards

• What is a standard?– Solution containing a known amount of a

specific substance– Example – 1.00mg/L iron standard

Standards

• How are standards used?– Instrument calibration– Instrument verification/accuracy check– Analyst training

Standards

• Analysis of Known Standard Solutions – Am I running the test correctly?– Verifies instrument, technique, and reagents

Standards

• Analysis of Known Standard Solutions – – How often?– Daily, every Sample ‘Batch’?

• National Institute of Standards and Technology– “NIST”

Standards

• Recovery of Known Additions – – Is my sample compatible with the test?– Identifies interferences and percent recovery

• Standard Addition

• ‘Spiked sample’

33

= 1.00 mg/L

50 mg/L Iron Standard

1.20 mg/L 1.39 mg/L 1.58 mg/L

Correct??

1.20 mg/L 1.40 mg/L 1.60 mg/L

34

X 100 = 100 %1.20 mg/L

1.20 mg/LX 100 = 99 %

1.39 mg/L

1.40 mg/LX 100 = 98.7 %

1.58 mg/L

1.60 mg/L

Calibration with Standards

• Some instruments have built-in calibration curves, not necessary to calibrate

• Instrument without preprogrammed calibration curves– Prepare curve daily - OR– Whenever a new lot of reagents is prepared

Calibrations

mg/L

ABS

pH Calibration Curve

mVmV

pHpH

0

+180

-1804 7 10

Standards

• “It’s what I always get”• “It meets the permit limit”• “I did”:

– what the manual said– what tech support said– what you told me

• “It’s the same number the City of ____ gets”

• “I got what I expected”• “I’ve run standards”• “It’s a XXX brand instrument,

the best!”• “After 20 years you get a feel

for it” • “I’m a chemist” • “It’s the same answer the lab

got”

Quality Assurance

Quality Control








Quality Assessment



Reagent Blanks

• Some reagents contribute color to a sample– Quantifies amount of reagent contribution to color

formation– Monitors of purity of reagents

• On each new lot of reagents

• 5% of samples (Standard Methods)

Reagent Blanks

Quality Assurance

Quality Control








Quality Assessment



Analysis of Duplicates

• Assesses precision

• 5% of sample need to be Duplicates – (Standard Methods)

Quality Assurance

Quality Control








Quality Assessment



What is a Control Chart?

• Quality control (QC) measuring device that visually represents the QC data

• Information in a control chart can aid in determining:– Probable source of measurement variability – Whether or not a process is in statistical control

How do Control Charts Work?

• If the chart displays other than random variation around the expected result, it suggests a problem with the measurement process.– Control limits are plotted on the chart, to assess whether

this has happened. The measurement results are expected to remain within these limits.

Normal DistributionNormal Distribution(Standard Deviation around the Mean)

+2s+2s +3s+3s+1s+1s-1s-1s-2s-2s-3s-3s MEAN

Confidence LimitsConfidence Limits

+2s+2s +3s+3s+1s+1s-1s-1s-2s-2s-3s-3s 10.00

68%


+2s+2s +3s+3s+1s+1s-1s-1s-2s-2s-3s-3s 10.00

95%


+2s+2s +3s+3s+1s+1s-1s-1s-2s-2s-3s-3s 10.00

99%

Control Charts

• A control chart is essentially a normal distribution flipped on its side

• A control chart is a plot of: – Test units on the vertical scale– Sequence of time on the horizontal scale

Control Chart

+3s+3s

+2s+2s

+1s+1s

Mean

-1s-1s

-2s-2s

-3s-3s

Control Chart

+3s+3s

+2s

+1s+1s

Mean

-1s-1s

-2s

-3s-3s

Upper Warning Limit

Lower Warning Limit

Control Chart

+3s

+2s+2s

+1s+1s

Mean

-1s-1s

-2s-2s

-3s

Upper Control Limit

Lower Control Limit


• Warning Limits– Set at ±2s– Standard Methods suggests:

• If 2 of 3 points are outside warning limits, analyze another sample. If it is within warning limits, continue. If it is outside warning limits, stop and troubleshoot.


• Control Limits– Set at ±3s– Standard Methods suggests:

• If any point is outside control limits, analyze another sample. If it is within control limits, continue. If it is outside control limits, stop and troubleshoot.


• A standard is measured regularly, and the results are plotted on the control chart.

• Control chart is a graph of concentration versus time.

+3s+3s

+2s+2s

+1s+1s

Mean

-1s-1s

-2s-2s

-3s-3s

UC L

LC LLW L

UW L

Control ChartControl ChartIron Standard, FerroVer ProcedureIron Standard, FerroVer Procedure

TimeTime

Constructing a Control Chart

• A control chart can be constructed in a variety of ways:– Graph paper– Spreadsheet problem, such as Excel


• Analyze 10-15 replicates of a standard.

• Determine the mean and standard deviation.– Calculate ±2s and ±3s

• Construct the control chart around the mean value– Use ±2s as the warning limits– Use ±3s as the control limits

Example – Iron Standard Replicates

Sample mg/L Iron

1 1.003

2 1.010

3 0.995

4 1.007

5 0.993

6 1.018

7 1.000

8 0.986

9 1.014

10 1.005

11 0.990

12 1.000

13 0.982

14 1.000

15 0.997


• Calculate:– Mean– Standard Deviation (±1s)– ±2s– ±3s


• Calculate:– Mean 1.000– Standard Deviation (±1s) ±0.010 (0.990-1.010)– ±2s ±0.020 (0.980-1.020)– ±3s ±0.030 (0.970-1.030)

+3s+3s

+2s+2s

+1s+1s

Mean

-1s-1s

-2s-2s

-3s-3s

UC L

LC LLW L

UW L


TimeTime

1.00 mg/L

1.02 mg/L

0.98 mg/L

1.03 mg/L

0.97 mg/L


First, set up a spreadsheet

with columns for UWL, LWL, UCL, LCL, and sample

results


Fill in values for UWL, LWL, UCL, LCL, and sample

results

+3s+3s

+2s+2s

+1s+1s

Mean

-1s-1s

-2s-2s

-3s-3s

UC L

LC LLW L

UW L


TimeTime

1.00 mg/L

1.02 mg/L

0.98 mg/L

1.03 mg/L

0.97 mg/L


Fill in values for UWL, LWL, UCL, LCL, and sample

results


Highlight data and create a

graph


Iron Control Chart

0.95

0.97

0.99

1.01

1.03

1.05

1 2 3 4 5

Sample

mg

/L I

ron

0.95

0.97

0.99

1.01

1.03

1.05

UWL

LWL

UCL

LCL

mg/L iron

Format graph as necessary

Example Control Charts

• Control Analysis Results – Week 1

Sample mg/L Iron

Mon 1.003

Tues 0.995

Wed 1.006

Thurs 0.988

Fri 0.992

Sat 0.992

Sun 1.004


Iron Control Chart - Week 1

0.95

0.97

0.99

1.01

1.03

1.05

1 2 3 4 5 6 7

Sample

mg

/L I

ron

0.95

0.97

0.99

1.01

1.03

1.05

UWL

LWL

UCL

LCL

mg/L iron

Week 1 results display normal,

random variation between the

UWL and LWL.



Sample mg/L Iron

Mon 1.008

Tues 1.000

Wed 0.996

Thurs 0.993

Fri 0.989

Sat 0.988

Sun 0.983



0.95

0.97

0.99

1.01

1.03

1.05

1 2 3 4 5 6 7

Sample

mg

/L I

ron

0.95

0.97

0.99

1.01

1.03

1.05

UWL

LWL

UCL

LCL

mg/L iron

Week 2 – Three or more points in one direction

indicates a possible bias in

analytical results.

Investigate!



Sample mg/L Iron

Mon 1.012

Tues 1.000

Wed 1.015

Thurs 0.986

Fri 0.994

Sat 0.968

Sun 0.997



0.95

0.97

0.99

1.01

1.03

1.05

1 2 3 4 5 6 7

Sample

mg

/L I

ron

0.95

0.97

0.99

1.01

1.03

1.05

UWL

LWL

UCL

LCL

mg/L iron

Week 3 – Data has a high

degree of scatter to the LCL. Investigate!

Quality Assurance

Quality Control








Quality Assessment



Performance Evaluation Samples

• Standards provided by an outside agency– ‘Blind’ Samples

Performance Audits

• Inspection to document sampling handling from receipt to final reporting of results– To detect any variations from SOPs– Checklists developed for each analysis type

• Sample entered in log book?

• Meter calibrated?

• Standard Analyzed?

• Etc., etc…..

LABORATORY MANAGEMENT LABORATORY MANAGEMENT and QUALITY ASSURANCEand QUALITY ASSURANCE

References

• Standards Methods• “Handbook for Analytical Quality Control in Water and

Wastewater Laboratories”– EPA 1979

• Hach Water Analysis Handbook• “An Introduction to Standards and Quality Control for the

Laboratory”– Barbara Martin, Hach Company

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