Patient SafetyPreanalytical Phase

Vladimir Palicka

Charles University

Hradec Kralove, Czech Republic

International Symposium “Patient Safety”, Prague, April 12, 2013

Preanalytical PhaseThe Weakest Point in Quality

Management

International Symposium “Patient Safety”, Prague, April 12, 2013

The value of laboratory testing for diagnostics and therapy

Quantitativeat minimum 80-90 % of all objective data

are results of laboratory or other complementary departments

Qualitativehigh 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

preanalytical errors

misidentification

wrong sampling

pumping with fist

wet skin

tourniquet time

sample mixing (inverting)

time for transport and centrifugation

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 vitroUp to 2% samples are haemolysedAt minimum 50 possible reasons

inherited-acquired haemolytic anaemiahaemoglobinopathias

HELLP syndromedrugs, infection

artificial heart valvestransfusion 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 sampleTemperature discomfortHigh centrifugation force

Long centrifugationTo early centrifugation

Late serum/plasma separationWrong separation barrier

Re-centrifugation of gel-tubesPneumatic 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 humanbuilding 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

Patient Identification Errors

EQA - PAPA

Australia, New Zealand

12-year period

59 participating laboratories

3.9 million specimens

PAPA incident rate: 1.22 %

most significant incident

Patient or Sample Identification !

Quality System Requirements

ISO 15189:2007

SOPs

JCI:

at least two patient identifiers

Bracelets

bar-codes

RFID (radiofrequency identifier devices)

automated systems

The most common system

Patient – Wards

Wrist-bands, electronic order, bar-code sticks

Laboratory

Data terminal

Hand-held bare code scanner

Portable label printer

software

systems for patient identification

barcodes

Bar codes

History: local grocery, 1948

Patent was applied for 1949

Patent issued 1952

Today: more that 2 dozen different linear bar code symbologies

Most frequent used: Code 128, Code 39

Error rate expected 1:400.000 – 1.800.000

Most common sources of errors

Printing defect in the barcode

Suboptimal barcode orientation

Lack of error detection

Scanner resolution

Sasavage N: Clin.Lab.News, 2011, Jan

Errors in bar code technology

More often in POCT

More often on wristband than on paper

Take care about printer heads

Thick black line

Turn the label stock by 90o

Snyder ML, Clin.Chem. 2010, 56:1554

Sasavage N: Clin.Lab.News, 2011, Jan

Sasavage N: Clin.Lab.News, 2011, Jan

Sasavage N: Clin.Lab.News, 2011, Jan

Errors in bar code technology

More often in POCT

More often on wristband than on paper

Take care about printer heads

Thick black line

Turn the label stock by 90o

Quality program

Cleaning and bar code verifier use

Snyder ML, Clin.Chem. 2010, 56:1554

systems for patient identification

barcodes

radio frequency identification (RFID)

biometrics

magnetic stripes

optical character recognition

„smart“ cards

voice recognition

causes of patient misidentification

identical names

China example

60 in-patient sampled

in 32 of them (53 percent)

common full name shared with

1 – 101 other patients

attending the same hospital (Hong Kong)

Lee AC: Int.J.Health Care Qual.Assur.Inc.Leadersh.Health Serv., 2005:18/1:15

Astion M: Clin.Lab.News 20110,Jan

causes of patient misidentification

identical names

wristband „problems“

CAP: 2.6 % errors

(missing wristband, ID, illegible, incorrect)

wristband errors

Join Commission on Accreditation

CAP – Q-Probes

mean wristband error rates

5.4 – 8.4 %

after the introduction of QIM

< 1.0 %

wristband errors

4-years study

464 bed public hospital

bar-coded wristbands

total wristband error rates 10.6-16.5%

training sessions

total wristband error rates 0.4-1.5%

Dhatt GS: CCLM 2001, 49/5: ??

wristband errors

2 hospitals in Sweden (230+152 beds)

295 nurses/phlebotomists

questionnaire

undesirable practice

9.6% not asking name and ID

17% not checking identity

79% not checking wristband during ID

43% using health care card for ID

Wallin O: Scand.J.Caring Sci. 2010, 24/3: 581

Patient Identification Errors

differences between type of labs

transfusion medicine 0.05 %

clinical chemistry up to 1 %

most common reasons

malpractice (low interest), low adherence to QSR

high workflow

wrong technique

What about relabeling

Very strict policy

Blood and urine rarely will be candidates

Sometimes indicated for irreplaceable specimens

(cerebrospinal fluid, bone marrow, surgical)

The risk of recollection is greater than a risk for relabeling…

SOP

Astion M: Clin.Lab.News 20110,Jan

home mesage

identification mistakes are not easily detectable

no immediate harm or signal

many steps – no personal responsibility

mostly not systematic

not considered as the big problem

fear of blame

human factor involved

home mesage

patient identification is common duty of clinicians, phlebotomists and clinical chemists

technical equipment is necessary

(but must be under the control)

ISO, SOP, EQA are extremely important

education and enthusiasm of people is the corner stone

home mesage

before any test we should be sure whom

are we testing !

Patient safety

and proper care

is the target !