Patient Safety
Preanalytical Phase
Vladimir Palicka
Charles University
Hradec Kralove, Czech Republic
International Symposium “Patient Safety”, Prague, April 12, 2013
Preanalytical Phase
The Weakest Point in Quality
Management
International Symposium “Patient Safety”, Prague, April 12, 2013
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
analytics
approx 15 % (7-13%)
preanalytics
approx 62 % (46 – 68%)
postanalytics
approx 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 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
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 !