Preanalytical Phase

Quality Control

Vladimir Palicka

Charles University

Hradec Kralove, Czech Republic

VIth National Conference of Clinical Laboratory, Borovec, Bulgaria

Preanalytical Phase

The weakest point in quality

management

Vladimir Palicka

Charles University

Hradec Kralove, Czech Republic

VIth National Conference of Clinical Laboratory, Borovec, Bulgaria

The influence of the laboratory

on health care

60 – 70 %

of the most important clinical decision-making

(admission, diagnostics, discharge, medication)

is based on laboratory test results

The value of laboratory testing for

diagnostics and therapy

Quantitative

at minimum 80-90 % of all objective data are results of laboratory or other

complementary departments

Qualitative

high quality information only are of value, the others are dangerous

The value of laboratory testing for

diagnostics and therapy

Quantitative

at minimum 80-90 % of all objective data are results of laboratory or other

complementary departments

Qualitative

high quality information only are of value, the others are dangerous

To err is human:

building a safer health system

Kohn LT, Corrigan JM, Donaldson MS

National Academy Press, Washington, DC,

2000

Errors in medicine

10-20 % of errors negatively influence health

care quality

> 3 % of errors are of direct influence on

patient safety

„the more tests, the more errors“

Laboratory error

A defect occurring at any part of the

laboratory cycle, from ordering tests to

reporting results and appropriately

interpreting and reacting to these

ISO/PDTS 22367

negative/risky trends for quality

Consolidation pre-analytical phase

Decentralization (POCT) analytical quality

Outsourcing pre- and post-analytical

Downsizing, shortages total quality

positive trends for quality

Integration of automatization and informatics

improved process control

Standard Operation Procedures

reduction of errors in all phases

Improved contact with clinicians

pre- and post-analytical phase

Errors in laboratory medicine

analyticsapprox 15 % (7-13%)

preanalyticsapprox 62 % (46 – 68%)

postanalyticsapprox 23 % (18 – 45%)

Total Testing Process Improvement

prevalence of errors was reduced by

automation

improved laboratory technology

assay standardization

informatics

but mostly in analytical part !

Most common reasons of

pre-analytical errors

Haemolysis

Misidentification

Sampling error (wrong tube, inappropriate

amount of the sample)

Clotting

Sample and/or request missing

Wrong patient preparation

Preanalytical errors

Retrospective analysis

2001-2005

4.715.132 samples in 105 labs

The most common reason for sample

rejection

Missing sample (37.5%)

Haemolysis (29.3%)

(serum 38.6%, plasma 68.4%)Alsina J: CCLM 2008, 46: 849

Prevalence of preanalytical

problems

Absolute prevalence 0.20 – 0.75 %Inpatients 0.60 – 2.80 %

Outpatients 0.04 – 0.30 %

Haemolysis 39.0 – 69.0 %

Clotting 5.0 – 12.0 %

Insufficient volume 9.0 – 21.0 %

Inappropriate tube 5.0 – 13.0 %

Misidentification 1.0 - 2.0 %

External Audit

University Hospital

1.600 beds, all kinds of clinical medicine

Big laboratory focused on biochemistry

Independent body and organization

Focused on preanalytical phase and

cooperation with clinics

Complemented by data analysis

Frequency of preanalytical errors

• 5581 request in one week controlled

• Daily „refuse“ frequency was 8-10 samples i.e. 0.6-1.1%

Reason

for

refuse

Mis-

identification

Wrong

sample

Time over

the limit Haemolysis

Number

of

samples

26

0,47%

7

0,13% 0

14

0,25%

Sampling siteDept ACV

(elbow)

%

Hand

back

%

Collection

from line

%

Unknown

site

%A 80 20 0 0

B 80 20 0 0

C 87 8 0 5

D 100 0 0 0

E 67 33 0 0

All wards 84 12 0 4

Peculiarities during blood collection

Tourniquet time and releaseDept Released

before/during

first tube

%

Released

later than the

first tube

%

Tourniquet

time

≤ 60 s

%

Tourniquet

time

> 60 s

%

A 0 100 0 100

B 0 100 80 20

C 19 81 38 62

D 0 100 0 100

E 33 67 0 100

All wards 16 84 37 63

Tourniquet time

Tubes correctly inverted

Tube

type

Correctly

%

Incorrectly

%

Not at all

%

Unknown Recommended

Coag 0 57 29 14 3-4

ESR 0 57 29 14 8-10

Serum-

gel

0 82 18 0 5-6

EDTA 0 78 19 3 8-10

All

tubes

0 76 22 2

Time between collection and centrifugation

Dept Collection – Arrival to Lab Collection - Centrifugation

Aver min max Aver min maxA 60 28 93 71 47 104

B 12 2 27 19 11 34

C 24 6 116 28 18 131

D 85 85 85 100 100 100

E 34 33 36 43 42 45

All

wards

30 2 116 37 11 131

preanalytical errors

misidentification

wrong sampling

pumping with fist

wet skin

tourniquet time

sample mixing (inverting)

time for transport and centrifugation

some more preanalytical

problems

mislabelling

some more preanalytical

problems

mislabelling

detection of abnormal samples

Haemolytic specimen

Lipaemic specimen

Icteric specimen

Detection of inappropriateness

Visual inspection of lipaemic, icteric and/or

haemolysed samples is

highly unreliable

and should be replaced by automated

systems (serum indices)

Haemolysis

upper „reference limit“ for free Hb

plasma 20 mg/l

serum 50 mg/l

Visible haemolysis after centrifugation

free Hb > 300 mg/l = 18.8 mmol/l

(approximately 0.5% of Ery are lysed)

Haemolysis - reasons

in vivo – in vitro

Up to 2% samples are haemolysed

At minimum 50 possible reasons

inherited-acquired haemolytic anaemia

haemoglobinopathias

HELLP syndrome

drugs, infection

artificial heart valves

transfusion of incompatible blood

Haemolysis – common reasons

in vivo – in vitro

Wet skin at sampling site

Thin needle (usually < 21 G)

Difficult venipucture

Fragile veins

Vacuum in tube is too high

Wrong amount of blood for the amount of

additive (anticoagulant)

Haemolysis - reasons

Inappropriate shaking the sample

Temperature discomfort

High centrifugation force

Long centrifugation

To early centrifugation

Late serum/plasma separation

Wrong separation barrier

Re-centrifugation of gel-tubes

Pneumatic sample transporting

Haemolysis

The most common reasons of the

wrong samples

Frequency

40 – 70% of all rejected samples

(5-times more than any other reason)

Haemolysis according dept

Lippi G, CCLM 47: 616, 2009

Haemolysis

increased concentration/activity:

AST, ALT, CK, LDH, lipase

creatinine, urea, Fe, Mg, P, K

decreased concentration/activity:

ALP, GGT

Alb, bilirubin, Cl, G, Na

Special care: newborn bilirubin !!

Haemolysis

Immunoassay

False negative troponin T

False increase of troponin I

False increase of PSA

Negative bias: testosterone, cortisol, FPIA

Impossibility to measure:

insulin, glukagon, CT, PTH, ACTH, gastrin

In the case of haemolysis

a) Correction of result(s)

b) Release of results with flags and

comments

c) Information of ward and new-sample

request

In the case of haemolysis

a) Result correction

Methods with known interference (nm)

rejected

Release „unaffected“ results, only

Potassium results corrected by

recalculation

Should we correct the results ?

Haemolysis: potassium

Linear correlation

Should we use the „index“ or measured

concentration ?

different analyzers – different indexes

different calculation of corrected K =

K measured – (Hb mmol/l x 5.2)

K measured– (Hb mmol/l x 10)

Bland-Altman: uncertainty ± 0.4 mmol/l

In the case of haemolysis

a) Result correction

Methods with known interference (nm)

rejected

Release „unaffected“ results, only

Potassium results corrected by

recalculation

incorrect, error is too big !

intravascular haemolysis ?

In the case of haemolysis

b) Release of results with flags and

comments

Many types of comments

Wrong decision is quite common

Credibility of lab decreases

Extreme situations?

In the case of haemolysis

c) Information of ward and new-sample

request

Nonconformity notification

Laboratory book and hospital rules

Quick reaction is necessary

New sample request

In the case of haemolytic

sample

Information to ward

Consultation

New sample request

To err is human

building a safer health system

Kohn LT, Corrigan JM, Donaldson MS

National Academy Press, Washington, DC,

2000

To err is human

to delay is deadly

Consumer Reports – Health

Safe Patient Project.org

System fragility

Fragility of the whole system depends on

Number of barriers

Effectivity of barriers

Emmentaler cheese effect

Error prevention

High-quality sampling tubes and high quality

sampling procedure

Education of staff (wards and laboratory)

Approved and accepted rules (Laboratory Book)

TQM – systematic error detection

Quick and good cooperation with clinicians

Perfect documentation of errors (and reaction!)

Preanalytical error prevention and

management

Wrong samples detection:

- Detection system with many barriers

- Information technology

- Permanent monitoring of wrong samples,

their numbers, reasons and places to

occur

Improvement of pre-analytical phase

patient identification

blood collection

sample handling

specimen acceptance/rejection

application of pre-analytical workstations

(preparation, centrifugation, aliquoting, pipetting, sorting)

better communication with clinics

There is no worse loss

than a lost time

Michelangelo Buonarroti (1475-1564)