MODULAR ANALYTICS Serum Work Area (in USA Integrated MODULAR ANALYTICS, MODULAR ANALYTICS is a trademark of a member of the Roche Group) represents a further approach to automation in the laboratory medicine. This instrument combines previously introduced modular systems for the clinical chemistry and immunochemistry laboratory and allows customised combinations for various laboratory workloads. Functionality, practicability, and workflow behaviour of MODULAR ANALYTICS Serum Work Area were evaluated in an international multicenter study at six laboratories. Across all experiments, 236000 results from 32400 samples were generated using 93 methods. Simulated routine testing which included provocation incidents and anomalous situations demonstrated good performance and full functionality. Heterogeneous immunoassays, performed on the E-module with the electrochemiluminescence technology, showed reproducibility at the same level of the general chemistry tests, which was well within the clinical demands. Sample carryover cannot occur due to intelligent sample processing. Workflow experiments for the various module combinations, with menus of about 50 assays, yielded mean sample processing times of <38 minutes for combined clinical chemistry and immunochemistry requests; <50 minutes including automatically repeated samples. MODULAR ANALYTICS Serum Work Area offered simplified workflow by combining various laboratory segments. It increased efficiency while maintaining or even improving quality of laboratory processes.

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Hindawi Publishing Corporation

Journal of Automated Methods and Management in Chemistry

Volume 2008, Article ID 498921, 14 pages

doi:10.1155/2008/498921

Research Article

Increasing Efficiency and Quality by Consolidation of

Clinical Chemistry and Immunochemistry Systems with

MODULAR ANALYTICS SWA

Paolo Mocarelli,

1

Gary L. Horowitz,

2

Pier Mario Gerthoux,

1

Rossana Cecere,

1

Roland Imdahl,

3

Janneke Ruinemans-Koerts,

4

Hilmar Luthe,

5

Silvia Pesudo Calatayud,

6

Marie Luisa Salve,

6

Albert K unst,

7

Margaret McGovern,

7

Katherine Ng,

8

and Wolfgang Stockmann

7

1

University Department of Laboratory Medicine, Hospital of Desio, Via Benefattori 2, 20033 Desio Milano, Italy

2

Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02215-5400, USA

3

Gemeinschaftspraxis Dr. med. Bernd Schottdorf u.a., 86154 Augsburg, Germany

4

Department of Clinical Chemistry, Ziekenhuis Rijnstate Arnhem, 6800 TA Arnhem, The Netherlands

5

Department of Clinical Chemistry, Georg-August-University G

¨

ottingen, 37075 G

¨

ottingen, Germany

6

Hospital de la Plana, Vila Real, 1254 Castell

´

o, Spain

7

Roche Diagnost ics GmbH, Sandhofer Street 116, 68305 Mannheim, Germany

8

Roche Diagnostics Operations, Inc., 9115 Hague Road, P.O. Box 50416, Indianapolis, IN 46250, USA

Correspondence should be addressed to Paolo Mocarelli, mocarelli@uds.unimib.it

Received 25 October 2007; Accepted 19 December 2007

Recommended by Peter Stockwell

MODULAR ANALYTICS Serum Work Area (in USA Integrated MODULAR ANALY TICS, MODULAR ANALYTICS is a trade-

mark of a member of the Roche Group) represents a further approach to automation in the laboratory medicine. This instrument

combines previously introduced modular systems for the clinical chemistry and immunochemistry laboratory and allows cus-

tomised combinations for various laboratory workloads. Functionality, practicability, and workflow behaviour of MODULAR

ANALYTICS Serum Work Area were evaluated in an international multicenter study at six laboratories. Across all experiments,

236000 results from 32400 samples were generated using 93 methods. Simulated routine testing which included provocation inci-

dents and anomalous situations demonstrated good performance and full functionality. Heterogeneous immunoassays, performed

on the E-module with the electrochemiluminescence technology, showed reproducibility at the same level of the general chemistry

tests, which was well within the clinical demands. Sample carryover cannot occur due to intelligent sample processing. Workflow

experiments for the various module combinations, with menus of about 50 assays, yielded mean sample processing times of <38

minutes for combined clinical chemistry and immunochemistry requests; < 50 minutes including automatically repeated samples.

MODULAR ANALY TICS Serum Work Area off ered simplified workflow by combining various laboratory segments. It increased

effi ciency while maintaining or even improving quality of laboratory processes.

Copyright © 2008 Paolo Mocarelli et al. This is an open access article distributed under the Creative Commons Attribution

License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly

cited.

1. INTRODUCTION

The clinical laboratory is arguably the frontrunner in apply-

ing scientific discoveries and technical innovations to patient

care. For example, there are not only far more tests read-

ily available now compared to just twenty years ago but also

the tests themselves have increased sensitivity and specificity

(e.g., hs-CRP, ferritin). It has been estimated that about 65%

of medical decisions are based on laboratory tests [1 ].

Paradoxically, the clinical laboratory success has placed

it under even greater pressure to produce more and better

test results, with shorter turnaround times and at lower costs.

As clinical laboratories have evolved, they have relied heav-

ily on automation. By moving from manual assays of single

analytes to random access, multichannel, automated instru-

ments, and more tests can be done, more frequently, with

fewer people. As noted in recent publications, by combin-

ing several of these instruments into a novel single platform

2 Journal of Automated Methods and Management in Chemistry

Rerun lane

Connection to

pre -analytics

Main lane

Connection to

post -analytics

STAT

port

ID

Reader

Processing lane Processing lane

ISE

∗

module D, P, E module D, P, E module

2trays

(2

× 150 tubes)

2trays

(2

× 150 tubes)

Input

buff er

Rerun

buff er

Output

buff er

∗

ISE module is embedded in the core unit

Figure 1: Schematic structure of MODULAR system.

for the clinical chemistry [2 ] and for the immunochemistry

laboratory [3 ], these analysers represented a new degree of

consolidation.

However, there has been little integration of traditional

clinical chemistry (ISE, spectrophotometry, homogeneous

immunoassay) and heterogeneous immunoassay. From an

analytical and technology perspective, the separation of the

two types of analysers may make sense. But, from a medi-

cal perspective, of course, the separation is entirely artificial.

For the patient in the emergency room, the physician needs

to know the troponin and the potassium. For the oncology

patient, the physician needs to know the CEA as well as the

calcium. Does it make sense to draw two tubes of blood to

insure quick turnaround time by running the sample on two

analysers simultaneously? Or, if just one tube is drawn, is it

the only solution to insure quick turnaround time by asking a

technologist to make sure that, as soon as the tube is finished

on the chemistry analyser, it gets placed on the immunoas-

say analyser to be analysed there? With either scenario, there

are inherent ineffi ciencies, as compared to running a single

tube on a single system for all the requested tests. MODU-

LAR ANALYTICS SWA (in USA: Integrated MODULAR AN-

ALYTICS, IMA), thereafter MODULAR system, represents

the integration of comprehensive systems for traditional clin-

ical chemistry and for heterogeneous immunoassays into a

single system for essentially all chemistry analytes.

Here we present the results of our studies at 6 laboratories

with a single system processing a selection of 30 to 50 diff er-

ent tests for clinical chemistry, specific proteins, therapeutic

drugs, and immunochemistry determination.

Our goals were to

(1) evaluate the functionality and practicability of the

analyser;

(2) determine whether improved efficiency would be re-

alized by integrating clinical chemistry with heteroge-

neous immunoassay testing;

(3) test for possible effects on the quality of results (repro-

ducibility, carryover) due to consolidation.

In addition, we predicted that there would be a reduction of

sample splitting, the elimination of multiple user interfaces,

and a reduction of hands-on labour.

Experiments were performed on MODULAR system in

five laboratories over a period of five months. At a sixth site,

a larger hardware configuration was tested afterwards.

2. MATERIALS AND METHODS

MODULAR ANALYTICS Serum Work Area combines pre-

viously evaluated modular systems for clinical chemistry

and immunochemistry: MODULAR ANALYTICS

D,P and

MODULAR ANALYTICS

E [2, 3 ].

The MODULAR system consists of a control unit, a core

unit with a bidirectional multitrack rack transportation sys-

tem, and four kinds of analytical modules—an ISE module

for the electrolytes Na, K, and Cl with a maximum through-

put of 900 tests/hour, a P800 module with a capacity of 44

spectrophotometric tests on board and a maximum through-

put of 800 tests/hour, a D2400 module with 16 spectrophoto-

metric tests and a maximum throughput of 2400 tests/hour,

and an E170 module using the electrochemiluminescence

technology with a capacity of 25 immunochemistry reagents

on board and a throughput of up to 170 tests/hour. The

configurations of MODULAR system are versatile and al-

low customised module combinations for various laboratory

workload patterns. Of the several available hardware combi-

nations, three diff erent combinations of the clinical chem-

istry modules D and P and the immunochemistry module

E were evaluated at the six sites (3

PE,2PPE,and1

DPE); all systems included an ISE module. Figure 1 shows

the schematic structure of MODULAR system.

The instruments used in the diff erent laboratories for

comparison with MODULAR system during the workflow

study were MODULAR ANALYTICS

P, PP, E,Elec-

sys 2010 (Elecsys is a trademark of a member of the Roche

group), Hitachi 747 and 917, all from Roche Diagnostics

(Mannheim, Germany), the BNA II protein analyser from

Dade Behring (Liederbach, Germany), the ADVIA Centaur

and ACS: 180 from Bayer (Tarrytown, NY, USA) and the

AxSYM from Abbott Laboratories, (Abbott Park, Illinois,

USA).

The methods selected for the workflow studies covering

approximately80analyteswith30to50applicationsperlab-

oratory are summarised in Ta bl e 1 . For the imprecision runs

and functionality testing, only a subset of these methods was

Paolo Mocarelli et al. 3

Table 1: List of analytes used during the performance evaluation and within-run imprecision for selected analytes (cells with a CV number:

analytes were used for within-run imprecision, x: analytes were added for the workflow experiments; CS1 control serum PNU from Roche,

HS human serum pool, HU human urine pool, analyte concentrations within or slightly above reference range; CS pool, control serum of a

low- and high-level control).

Assays Method Units Material

Lab 1

CV%

Lab 2

CV%

Lab 3

CV%

Lab 4

CV%

Lab 5

CV%

Lab 6

CV%

Qual-Spec

CV%

∗

Electrolyte assays

NA Sodium (ISE-indirect) mmol/l CS 1 0.3 0.4 0.3 0.3 0.7 0.4 0.3 (0.7)

K Potassium (ISE-indirect) mmol/l CS 1 0.5 0.5 0.3 0.5 0.8 0.4 2.4

CL Chloride (ISE-indirect) mmol/l CS 1 0.4 0.5 0.4 0.4 0.6 0.5 0.7 (1.0)

Enzyme assays

ACP Acid phosphatase U/l x x 4.5

ALP

A Alkaline phosphatase AMP U/l CS 1 0.9 3.4

ALP

I Alkaline phosphatase IFCC U/l CS 1 0.7 x 3.4

ALP

O

Alkaline phosphatase

optimized

U/lCS1x1 x3.4

ALT

I

Alanine aminotransferase

IFCC, wo Pyp

U/l CS 1 2.5 x 2.4 2.4 13.6

ALT

IP

Alanine aminotransferase

IFCC, w Pyp

U/l CS 1 2.5 x 13.6

AST

I

Aspartate aminotransferase

IFCC wo Pyp

U/l CS 1 x 3.3 2.2 2.1 7.2

AST

IP

Aspartate aminotransferase

IFCC w Pyp

U/l CS 1 x 2.1 7.2

AMY

Amylase total EPS

(ethylidene protected

substrate)

U/l CS 1 0.7 x x 0.6 0.6 3.7

P-AMY Amylase pancreatic EPS U/l CS 1 0.8 5.9

CHE

Cholinesterase

(Butyrylthiocholine

substrate)

U/l x x x x 3.5

CK

Creatine kinase, NAC

activated (N-acetylcysteine)

U/l CS 1 0.6 0.8 x x 0.7 x 20.7

CKMB

CK-MB—MB isoenzyme of

creatine kinase

U/l CS 1 2.3 x x x

GGT

γ-Glutamyl transferase

(procedure by

Szasz-Persijn)

U/l CS 1 x x 1.8 1.6 x 1.7 7.4

GLDH Glutamate dehydrogenase U/l x x

HBDH

Lactate dehydrogenase-1-

isoenzyme

U/l x

LDH

O

Lactate dehydrogenase

DGKC

U/lCS1x0.4x0.7 x3.9

LD Lactate dehydrogenase U/l CS 1 1 3.9

LIP Lipase colorimetric U/l CS 1 1 1 0.8 11.6

Substrate assays

ALB

Albumin (BCG, bromcresol

green, plus)

g/l CS 1 x 0.8 x 1.2 1.1 (2.8)

D-BIL

Bilirubin direct

(Jendrassik)

μmol/lCS1xxxx1.8x

T-BIL

Bilirubin total (DPD,

dichlorphenyldiazonium

method)

μmol/l CS 1 x x x x 1.9 x 11.3

CHOL Cholesterol (CHOD-PAP) mmol/l CS 1 0.8 1.0 0.9 0.9 1.1 1.4 2.7

HDL High-density lipoproteins mmol/l CS 1 0.8 0.9 x 0.9 x 3.6

LDL Low-density lipoproteins mmol/l CS 1 0.6 x x

3.3

4 Journal of Automated Methods and Management in Chemistry

Table 1: Continued.

Assays Method Units Material

Lab 1

CV%

Lab 2

CV%

Lab 3

CV%

Lab 4

CV%

Lab 5

CV%

Lab 6

CV%

Qual-Spec

CV%

∗

CREAJ

Creatinine (Jaff

´

e, rate

blanked)

μmol/l CS 1 2.4 1.4 1.9 1.1 1.8 2.2

CREA

Creatinine (enzymatic,

plus)-urine

μmol/l x

GLU

P Glucose (GOD-PAP) mmol/l CS 1 0.8 0.9 2.2

GLU

H Glucose (hexokinase) mmol/l CS 1 0.9 0.7 1.0 1.0 0.6 2.2

FE Iron (FerroZine method) μ mol/l CS 1 0.5 x 0.7 1.2 x x 15.9

LACT Lactate (colorimetric) mmol/l CS 1 0.7 0.9 13.6

TP

Total protein (biuret

reaction)

g/lCS1x0.4xx0.8x1.4

TG Triacylglycerol (GPO-PAP) mmol/l CS 1 1.1 1.3 0.9 1.2 1.2 0.7 11.5

UREA UREA/BUN (UV, kinetic) mmol/l CS 1 1.8 1.4 1.5 1.6 1.3 1.7 6.3

UA Uric acid (PAP, plus) μ mol/l CS 1 x 0.5 1.6 0.6 1.0 1.0 4.2

CO2 Bicarbonate (UV, kinetic) mmol/l CS 1 1.6 2.3 (4.9)

CA

Calcium (OCPC,

ortho-cresolphthalein

complexone)

mmol/l CS 1 0.8 1.1 0.7 0.9 1.1 x 0.9 (1.5)

MG

Magnesium (xylidyl blue

method)

mmol/l CS 1 0.7 0.7 1.0 x 1.1 (2.6)

PHOS

Phosphorus (molybdate,

UV)

mmol/l CS 1 x 1.1 x x 1.4 x 4

Protein assays

GPROT

α1-acid-glycoprotein (TIA,

Tina-quant a)

g/l HS Pool 0.7 x 5.7

ATRYP

α1-antitrypsin (TIA,

Tina-quant a)

g/l x 3.0

MICGL

β2-microglobulin (TIA,

Tina-quant a)

μg/ml x 3.0

ASLO

Antistreptolysin O (LPIA,

Tina-quant a)

IU/ml HS Pool 0.6 1.0

C3c

Complement protein C3c

(TIA, Tina-quant a)

g/l HS Pool x 1.3

C4

Complement protein C4

(TIA, Tina-quant a)

g/l x x

CPLAS

Ceruloplasmin (TIA,

Tina-quant a)

g/l x

CRP

C-reactive protein (TIA,

Tina-quant a)

mg/l HS Pool x 0.8 x x 1.2 1.3 26.3

FERR

Ferritin (LPIA, Tina-quant

a)

μg/l HS Pool 2.3 7.5

HBA1C%

Glycated haemoglobin A1c

(TIA, Tina-quant a)

%HSPool 1.1

HGLOB

Haptoglobin (TIA,

Tina-quant a)

g/l HS Pool 0.9 1.1 x 10.2

IGG

Immunoglobulin G (TIA,

Tina-quant a)

g/l CS 1 x 2.5 2.0 2.6 1.9 1.9 (3.7)

IGA

Immunoglobulin A (TIA,

Tina-quant a)

g/l CS 1 x 1.5 0.8 x 1.1 2.2 (3.8)

IGM

Immunoglobulin M (TIA,

Tina-quant a)

g/l CS 1 x 1.7 1.7 x 1.3 2.3 (5.4)

IGE

Immunoglobulin E (TIA,

Tina-quant a)

μg/l x x

KAPPA Kappa (TIA, Tina-quant a) g/l x

Paolo Mocarelli et al. 5

Table 1: Continued.

Assays Method Units Material

Lab 1

CV%

Lab 2

CV%

Lab 3

CV%

Lab 4

CV%

Lab 5

CV%

Lab 6

CV%

Qual-Spec

CV%

∗

LAMBD

Lambda (TIA, Tina-quant

a)

g/l x

MYO

Myoglobin (TIA,

Tina-quant a)

μg/l x

PALB

Prealbumin (TIA,

Tina-quant a)

IU/ml HS Pool 2.2 5.5

RF

Rheumatoid factor (LPIA,

Tina-quant a)

IU/ml HS Pool 0.5 0.8 0.6 0.9 4.3

TRANS

Transferrin (TIA,

Tina-quant a)

g/l CS 1 x 1.5 1.4 x 1.9 x 1.5

TDM assays

CARB Carbamazepine (CEDIA) μmol/l x

DIG Digoxin (LPIA) nmol/l HS Pool 2.0 3.8 (4.7)

GENT Gentamicin II (CEDIA) μmol/l x

NAPA NAPA (CEDIA) μmol/l x

PHENO Phenobarbital II (CEDIA) μmol/l x

PHNY Phenytoin II (CEDIA) μmol/l x

PROC Procainamide (CEDIA) μmol/l x

SAL Salicylate (iron complex) mmol/l x

THEO Theophylline II (CEDIA) μmol/l x

VALP Valproic Acid II (CEDIA) μ mol/l HS Pool 2.0 6.4

Urine assays

NA

Sodium

(ISE-indirect)-urine

mmol/l

HU

Pool

0.4 0.6 0.4 0.6 14.4

K

Potassium

(ISE-indirect)-urine

mmol/l

HU

Pool

0.4 0.8 0.4 1.2 9.0

CL

Chloride

(ISE-indirect)-urine

mmol/l

HU

Pool

0.8 1.3 0.6 0.6

AMY Amylase liquid-urine U/l

HU

Pool

0.7 x

CREAJ

Creatinine Jaff

´

e(rate

blanked)-urine

μmol/l

HU

Pool

0.8 1.0 1.2 5.5

CREA

Creatinine (enzymatic,

plus)-urine

μmol/l

HU

Pool

0.9 5.5

GLU

H Glucose (hexokinase)-urine mmol/l

HU

Pool

xx

UREA

UREA/BUN (UV,

kinetic)-urine

mmol/l

HU

Pool

1.9 1.2 1.4 1.5

UA

Uric Acid (PAP,

plus)-urine

μmol/l

HU

Pool

0.9 0.9 0.7 x

CA

Calcium (OCPC,

ortho-cresolphthalein

complex.)-urine

mmol/l

HU

Pool

3.0 1.6 x 13.1

MG

Magnesium (xylidyl blue

method)-urine

mmol/l

HU

Pool

1.0 x 19.2

PHOS

Phosphorus (molybdate,

UV)-urine

mmol/l

HU

Pool

1.2 1.6 x 9.0

U/CSF

Protein in

urine/CSF(turbidim., rate)

g/l

HU

Pool

0.8 x 0.7 17.8

MAU

Albumininurine(TIA,

Tina-quant a)

mg/l

HU

Pool

1.3 x 18

Immunochemistry assays

T3 Triiodothyronine nmol/l CS Pool x 1.4 x 0.8 4.0 (4.7)

6 Journal of Automated Methods and Management in Chemistry

Table 1: Continued.

Assays Method Units Material

Lab 1

CV%

Lab 2

CV%

Lab 3

CV%

Lab 4

CV%

Lab 5

CV%

Lab 6

CV%

Qual-Spec

CV%

∗

T4 Thyroxine nmol/l CS Pool 2.7 x 1.5 3.4 (4.1)

FT3 Free triiodothyronine pmol/l CS Pool 1.5 2.0 4.0

FT4 Free thyroxine pmol/l CS Pool x 1.7 x x 0.9 3.8

TSH

Thyroid-stimulating

hormone, thyreotropin

mIU/l CS Pool x 2.1 0.8 1.1 1.1 0.6 8.1

DIGIT Digitoxin nmol/l CS Pool 2.5

DIGO Digoxin nmol/l CS Pool 2.8 3.8 (4.7)

PROBNP

N-terminal B-type

natriuretic peptide

pmol/l HS Pool 0.5

TNT Troponin T μ g/l CS Pool 1.0 1.1

FERR

E Ferritin μ g/l CS Pool x x 2.1 0.9 1.6 7.5

FOLAT Folate nmol/l CS Pool x x x 3.9 1.7

B12 Vitamin B12 pmol/l CS Pool 1.8 x x 2.6

AFP α 1-fetoprotein μ g/lCSPoolxx0.9x1.8

CA

125 Cancer antigen 125 kU/l CS Pool x x x 0.9 1.0 6.8

CA

153 Cancer antigen 15-3 kU/l CS Pool 1.1 x x x 2.6

CA

199 Cancer antigen 19-9 kU/l CS Pool 0.9 x x 12.3

CEA Carcinoembryonic antigen μ g/l CS Pool x x 1.2 1.3 4.6

TPSA

Total prostate-specific

antigen

μg/lCSPoolxx0.5x2.3 9.1

FPSA

Free prostate-specific

antigen

μg/l CS Pool 0.8 1.0 x

CORT Cortisol nmol/l CS Pool 1.6 1.0 x 7.6

DHEA-S

Dehydroepiandrosterone

sulfate

μmol/l CS Pool 2.5 x 1.7

E2 Estradiol pmol/l CS Pool 1.6 1.7 x 1.7 10.9

FSH

Follicle stimulating

hormone

IU/l CS Pool x 0.9 1.3 x 5.1

HCG + β

Human chorionic

gonadotropin + β -subunit

IU/l CS Pool 1.8 1.2 1.2

LH Luteinizing hormone IU/l CS Pool x 1.1 x x 6.2

PROG Progesterone nmol/l CS Pool x 1.2 9.8

PRL Prolactin mIU/l CS Pool x 1.2 x x 3.5

PTH Parathyroid hormone pmol/l x x x

INS Insulin pmol/l CS Pool 2.3 1.6 7.6

TESTO Testosterone pmol/l 1.4 1.6 x 4.4

∗

References [10 , 11 ], values in italics: from Ric

´

os et al. [12 ]; values in parentheses: interim quality specifications.

processed at each laboratory. The reagents for MODULAR

system were the respective system packs from Roche Diag-

nostics. The calibration of the tests was done according to the

requirements set by the manufacturer using the calibration

materials from Roche Diagnostics. The daily quality control

was performed with control sera also provided by the manu-

facturer.

Depending on the analyte, either control material or

human specimen pools were used for the imprecision and

routine simulation imprec i sion experiments. Samples for the

workflow experiments included serum, heparinized plasma

and urine from the daily routine.

The performance evaluation was supported by CAEv, a

program for Computer Aided Evaluation [4 ]. This program

allows the definition of experiments, the sample and test re-

quests, on-line/off -line data transmission, and the immedi-

ate data validation by the evaluators.

3. EVALUATION PROTOCOL

3.1. Within-run imprecision

Two control materials (serum, urine) with diff erent con-

centrations of the analyte (or, for some analytes, a human

Paolo Mocarelli et al. 7

Table 2: Overview of processed workloads at the participating laboratories. (For explanation see materials and methods section, workflow

study.)

Site

SWA

config.

Analytes

processed

Average re-

quests per

sample

Sample distribution

Total number of

samples/ requests

Routine compared

1PE

3onISE

11 (1–36)

CC only: 232

299 samples

Ye s ,

30 on P

Eonly: 18

3281 requests

P800 + E170

11 on E

CC + E: 49

2PPE

3onISE

11 (1–27)

CC only: 381

555 samples

Ye s ,

41 on PP

Eonly: 14

5839 requests

PP + 2

∗

E2010

15 on E

CC + E: 160

4 on E2010

3PE

3onISE

9 (1–35)

CC only: 287

399 samples

No

28 on P

Eonly: 33

3422 requests

17 on E

CC + E: 79

4PE

3onISE

8 (1–21)

CC only: 318

531 samples

No

26 on P

Eonly: 87

4003 requests

16 on E

CC + E: 126

5PPE

3onISE

6 (1–22)

CC only: 369

573 samples

Ye s ,

39 on PP

Eonly: 63

3668 requests

H917 + H747 + 3 instr. with CLIA + RIA

19 on E

CC + E: 141

6DPE

3onISE

9 (1–29)

CC only: 1428

1951 samples

No

12 on D

Eonly: 77

16805 requests

25 on P

CC + E: 446

3onE

(E2010 = Elecsys 2010; Elecsys is a trademark of a member of the Roche group; CLIA = chemiluminescence immunoassay; RIA = radio immunoassay.)

specimen pool at the diagnostic decision level) were used.

The experiment was performed on two days with 21 aliquots

per run.

3.2. Precision in a simulated routine run

Experiments for routine simulation are designed for func-

tionality testing of an analytical system in the clinical labora-

tory. The protocol [5 ] has proven to be a useful tool during

various analyser evaluations [6 ].

This particular experiment tests for potential systematic

or random errors by comparing the imprecision of the ref-

erence results (standard batch, n

= 15) with results from

samples run in a pattern simulating routine sampling (ran-

domized sample requests, n>10). The randomized sample

requests were simulated in CAEv [4 ] according to each labo-

ratory's routine sampling pattern. The samples were control

materials or patient sample pools. The number of requests

varied with module combination, but was aimed at keeping

the analyser in operation for at least four hours. The second

and third of the three experiments processed at each site in-

cluded provocation incidents like reagent or sample shortage,

barcodereaderrors,andvariousreruns.

3.3. Sample carryover

Potential sample related carryover was investigated using a

slightly modified version of the Broughton protocol [7 ]. Only

analytes with a very high physiological concentration range

were tested. Ideally, the ratio of the concentrations of the

high and low samples should be, depending on the analyte,

10

3

to 10

6

. Three aliquots of a high concentration sample

(h

1

, h

2

, h

3

)werefollowedbymeasurementsoffivealiquots

of a low concentration sample (l

1

··· l

5

)oneachmodule.

The sequence h

1

h

2

h

3

l

1

l

2

l

3

l

4

l

5

was repeated five times.

Each sample was measured on the ISE module first, then

on the D and/or P module, and finally on the E170 mod-

ule, thereby insuring that reusable pipette probes were intro-

duced multiple times prior to sampling on the E170 mod-

ule, where disposable (nonreusable) pipette tips are used.

If a carry-over e ff ect from the ISE and D/P module sam-

ple probes exists, the l

1

will be the most influenced, and the

l

5

will be the least influenced aliquot when measured on E-

module. The carry-over eff ects were compared with the im-

precision of the low concentration samples and the diag-

nostic relevance of the respective E-module assays. Potential

sample carryover of the following analytes was tested: AFP,

CEA, ferritin, anti-HAV, HBsAg, hCG + ß, and t-PSA.

3.4. Workflow study

The participating sites performed this study to investigate

whether or not MODULAR system met their routine labo-

ratory specific needs, especially for improved effi ciency. As

shown in Ta ble 2 , module combination, analyte assignment,

tests per sample, numbers of samples, samples per module,

8 Journal of Automated Methods and Management in Chemistry

Table 3: Sample related carryover with high priority test option off . With high priority test option on, sample carryover cannot occur. (For

explanation see results section, sample-related carryover.)

Analyte

Expected

values

10% of lower

decision level

Lower detec-

tion limit

Ratio high :

low

Max. diff low

1

–

low

5

(if > 2SD)

Material

Relevant

Carry-

over, high

priority o ff

Relevant

Carry-

over, high

priority on

AFP < 6.2 μ g/l 0.62 μg/l 0.6 μ g/l 40871 0.62 Native yes No

CEA < 4.6 μ g/l 0.46 μg/l 0.2 μ g/l 16197 7.64 Spiked yes No

PSA <4 μg/l 0.4 μg/l 0.002 μ g/l 756 0.20 Spiked yes No

Ferritin

∼15–400 μ g/l 1.5 μg/l 0.5 μ g/l 969 2.00 Spiked no No

HCG + β< 5 mIU/ml 0.5 mIU/ml 0.1 mIU/ml 117000 1.30 Native yes No

a-HAV < 20 IU/l 2.0 IU/l 3.0 IU/l 1184 0.25 Native no No

HbsAg < 1.0 COI 0.1 COI 285106 0.44 Native yes

No

and tests per module, were very diff erent at each laboratory.

Three methods were used to capture the test requests on sam-

ples so that the same testing could be repeated on MODU-

LAR system. Test requests were either downloaded from the

laboratory's LIS to CAEv, captured directly by CAEv from

several analysers during routine operation or CAEv provided

a "characteristic" request list by simulation based on typical

test frequencies and profiles of the laboratory. In all cases, the

same sample set, usually a predefined substantial portion of

a day's workload was processed on MODULAR system.

Samples were loaded on MODULAR system chronolog-

ically as they appeared in the lab to mimic the laboratory's

routine pattern of receiving samples. All relevant time steps

and workload related activities like sample and reagent han-

dling, instrument preparation, loading and reloading of sam-

ple racks, and technologist time (both hands-on and walk-

away) were measured.

3.5. Practicability

Practicability of the system was assessed throughout the

study. A questionnaire—a supplement to the general ques-

tionnaire [8 ], which was previously used for the assessment

of the single modules—was designed especially for a consol-

idated sample working area. This allowed for a standardized

grading with the main focus on aspects of clinical chemistry

and immunochemistry consolidation and new software fea-

tures.

3.6. Expected performance

The protocol included expected performance criteria which

were agreed upon at the evaluators' first meeting. The criteria

for imprecision were based on state-of-the-art performance,

routine requirements of the laboratories, and statistical error

propagation [9 ].

4. RESULTS

Across all experiments, 236000 results from 32400 samples

were generated using 93 methods.

4.1. Imprecision

The within-run imprecision met the expected performance

criteria at virtually all sites. Typical within-run CVs for the

enzyme and substrate analytes were 1 to 2%, for the ion selec-

tive electrode (ISE) methods 0.5%, for the specific proteins

and drug analytes 1 to 3%, for the urine chemistry methods

1 to 2%, and for the heterogeneous immunoassays (with the

indication: thyroid, cardiac, anaemia, tumour markers and

fertility)1to3%( Tab le 1 ).

4.2. Functionality testing

The six laboratories performed 44668 determinations during

the random part of the routine simulation covering 87 ana-

lytes in 733 series. CVs obtained from the precision in a sim-

ulated routine r un experiment for the various assay groups

(ISEs, enzymes/substrates, urine analytes, proteins/TDMs,

and heterogeneous immunoassays) were summarized in dis-

tribution diagrams for the reference (batch part) and ran-

dom part (see Figure 2 ). Out of all 733 series, 13 (1.8%)

showed higher CVs than the expected limit in the random

part (9 in the enzyme/substrate group, 2 in the urine and the

immunoassay groups). Seven of these CVs were only mod-

erately increased (1 to 2% higher than the limit). Of the

remaining 6 series (5.3 to 22.8% CV), the highest CV was

caused by an unexplainable, nonreproducible outlier with a

very low result in one series of the albumin in urine test. With

the outlier removed, the CV was 1.2%. In all cases, the higher

CVs were observed in only one of the three simulated routine

series per laboratory (with tests like lipase, uric acid, albu-

min in urine and CA125) and there was no association with

any malfunction of the instrument or reagent. A software is-

sue associated with the E-module masking/unmasking dur-

ing a provocation was also identified during these experi-

ments (shift of the results with the FT3 assay).

4.3. Sample-related carryover

Ta ble 3 summarizes the carry-over eff ects seen when the high

priority settings were intentionally turned off for a group

Paolo Mocarelli et al. 9

Electrolytes: 3 analytes, 52 data sets

Distribution of CVs in batch part

0

25

50

75

100

(%)

96%

4%

0. 511 .522 .53 > 3

0

25

50

75

100

(%)

100%

0. 511 .522 .53 > 3

CV (%) CV (%)

Distribution of CVs in random part

(a)

Special proteins/TDMs: 16 analytes, 96 data sets

Distribution of CVs in batch part

0

25

50

75

100

(%)

99% 1%

1234 5678 > 8

0

25

50

75

100

(%)

100%

12345678 > 8

CV (%) CV (%)

Distribution of CVs in random part

(b)

Enzymes/substrate: 26 analytes, 328 data sets

Distribution of CVs in batch part

0

25

50

75

100

(%)

95%

5%

12345678 > 8

0

25

50

75

100

(%)

97%

3%

1234 5678 > 8

CV (%) CV (%)

Distribution of CVs in random part

(c)

Heterogenous immunoassays: 29 analytes, 161 data sets

Distribution of CVs in batch part

0

25

50

75

100

(%)

100%

12345678 > 8

0

25

50

75

100

(%)

99% 1%

12345678 > 8

CV (%) CV (%)

Distribution of CVs in random part

(d)

Urines: 13 analytes, 96 data sets

Distribution of CVs in batch part

0

25

50

75

100

(%)

100%

12345678 > 8

0

25

50

75

100

(%)

98% 2%

12345678 > 8

CV (%) CV (%)

Distribution of CVs in random part

(e)

Figure 2: Precision in a simulated routine run; distribution of 733 within-run CVs in reference (batch) and random parts; replicates n

in reference part 15 as follows: (i) expected performance limit for w ithin-run imprecision (solid line) (ii) expected performance limit for

randomised runs (dashed line).

10 Journal of Automated Methods and Management in Chemistry

0

10

20

30

40

50

60

70

80

Frequency (no. of samples)

0:00

0:10

0:20

0:30

0:40

0:50

1:00

1:10

1:20

1:30

1:40

1:50

2:00

2:10

2:20

2:30

2:40

2:50

3:00

Sample processing time (h:min)

SWA: IC requests only

Routine: IC requests only

SWA: CC requests only

Routine: CC requests only

SWA: CC + IC requests

Routine: CC + IC requests

Figure 3: SPT on MODULAR system and dedicated routine anal-

ysers representing 40% of a daily routine workload.

of tests that were considered high risk for sample carryover.

Only results from laboratories with the highest concentration

ratio (high/low) are included in the table. For the 7 assays for

which we expected to see sample-related carryover because of

the wide dynamic range of the analytes, our testing indicated

potentially clinically relevant problems with 5 (AFP, CEA,

HBsAg, HCG + ß, and t-PSA). By utilizing the "high prior-

ity test" option, samples with requests for these assays, which

also had requests for ISE, D, and/or P module tests, were au-

tomatically processed at the E-module first, eliminating the

possibility for carryover to occur for these samples and tests.

In the other two (ferritin and anti

HAV), neither criterion

for carryover was met (more than 10% of the (lower) medi-

cal decision level, or exceeding the 2 SD value). According to

investigations of the manufacturer, two additional carry-over

sensitive infectious disease assays were identified: anti-HBs

and anti-HBc.

4.4. Workflow

Themodulecombinations(

PE, PPE, DPE)andtest

menu configurations used at the diff erent laboratories were

selected to meet their specific workload demands. An

overview is presented in Ta ble 2 . To reflect true routine con-

ditions, the samples were placed on the system in a se-

quence mimicking the original arrival pattern in the labora-

tory, rather than continuously, to test the system's potential

sample loading capacity. The resulting cumulative through-

put was up to 800 results/hour using

PE module combi-

nations and up to 1580 results/hour for

PPE module com-

binations. A throughput of approximately 2160 results/hour

was yielded on the

DPE module combination in labora-

tory 6. In most of the laboratories, the number of samples

processed was not enough to reach the system's maximum

throughput capacity.

In addition to throughput, we looked carefully at sample

processing time (SPT), the time between sample registration

(barcode reading on the instrument) and the time the last

0:00

0:10

0:20

0:30

0:40

0:50

1:00

1:10

1:20

1:30

Time on analyser from registration

to last result (h:min)

1

11

21

31

41

51

61

71

81

91

101

111

121

131

141

151

161

171

181

191

Diagram shows only a part of the whole workload

Sample number

ISE rerun

Prerun

Ererun

Figure 4: SPT with focus on availability of rerun results.

result for that sample is produced. Note that SPT diff ers from

sample turnaround time (TAT), a commonly used term to

describe the time period from when the samples arrive in the

laboratory and the availability of the last result.

The following mean sample processing times were found

for the diff erent sample groups in five laboratories:

(i) 13–18 minutes for samples with general chemistry

requests only (ISE + P or ISE + P1 + P2),

(ii) 22–28 minutes for samples with immunoassay re-

quests only (E),

(iii) 29–38 minutes for samples with combined requests

(ISE + P + E or ISE + P1 + P2 + E).

The mean SPTs obtained with a

DPE combination were

comparable: 16 minutes for ISE + D + P, 26 minutes for E,

and 27 minutes for ISE + D + P + E.

We compared SPT of MODULAR

PPE with the cur-

rent six dedicated routine analysers for a predetermined time

period, representing approximately 40% of a day's workload

in laboratory 5. Figure 3 shows that the time to results for

samples with clinical chemistry requests on MODULAR sys-

tem is comparable with that of the dedicated routine anal-

ysers (mean time 15 minutes, 80th percentile 20 minutes,

maximum 38 minutes). Samples with combined requests

for both clinical chemistry and immunochemistry were pro-

cessed faster (mean time 34 minutes, 80th percentile 40 min-

utes, maximum 1 hour) than on the dedicated analysers

(mean time 46 minutes, 80th percentile 58 minutes, maxi-

mum 1.8 hours).

Depending on test, module and number of racks waiting

in the rerun buff er, rerun results are reported 10–35 minutes

after availability of first results. An example of typical pro-

cessing times to first results and to final results (including

rerun samples) is shown in Figure 4.

MODULAR SWA supports "reflex testing," if the lab-

oratory information system (LIS) off ers this functionality.

Frequently practiced for certain indication fields, this fea-

ture allows the automatic request of a further analyte, if a

Paolo Mocarelli et al. 11

0:00

0:10

0:20

0:30

0:40

0:50

1:00

1:10

1:20

1:30

Time on analyser from registration

to last result (h:min)

1

16

31

46

61

76

91

106

121

136

151

166

181

196

Diagram shows only a part of the whole workload

Sample number

Reflex testing: TNT + CK-MB

Figure 5: SPT with focus on reflex testing.

predefined concentration or concentration range of the orig-

inally requested analyte is exceeded. Examples are as follows:

If TSH < 0.27 or > 4.2 mIU/L, FT4 is determined in addition,

if PSA > 4.0 μg/L, free PSA is also measured and so on. Even

though it may no longer be as clinically relevant, reflex test-

ing functionality was assessed using a combination of P-and

E-requests: CK

→ CK-MB

(enzymatic)

+TnT.TheSPTforsuch

a sample with two additional reflex tests was increased by 30

to 55 minutes (Figure 5 ).

Does the sample carry-over setting, which tags the assay

in question automatically as high priority by the system, in-

fluence the SPT? We compared samples having combined re-

quests (on P- and E-module) with and without high prior-

ity assays. With auto rerun off, there was no result delay. The

processing times were increased by 10–15 minutes with auto

rerun activated, where processing on P module was delayed

until final E-module results were available.

Maintenance and troubleshooting are activities which

may also considerably influence the daily workflow. For a

modular system, the question arises whether the entire sys-

tem or only the aff ected module is blocked in order to rem-

edy a problem after, for example, a sampling stop alarm. This

type of alarm results in the module discontinuing pipetting

of samples. The diff erent time steps for two such alarms were

monitored on a

PPE combination at one site. For a pro-

voked tip/vessel pickup-error on the E-module, the elapsed

time from getting the alarm, allowing the module to finish

the tests in process, taking the module down, then fixing the

problem, and getting the module back into operation was a

total of 35 minutes; for a provoked abnormal cap mechanism

movement 22 minutes. While the E-module was unavailable,

the ISE and P-modules continued to process samples, and

samples requiring E-module tests were stored in the rerun

buff er to be run automatically when the E-module came back

online.

An important aspect of instrument consolidation on a

single platform is reduction in personnel hands-on time. In

laboratory 5, we compared hands-on time associated with

MODULAR system with that of the 6 existing dedicated anal-

ysers. As shown in Figure 6 , the operators saved about 10

hours based on the sample workload; the main contribution

was sample handling time. MODULAR system was operated

by 1 technologist while the 6 dedicated analysers required 3

persons.

One of the participating laboratories (laboratory 1) sim-

ulated a workflow using MODULAR system as a dedicated

immunoassay analyser. Tests included 24 homogeneous tests

(10 specific proteins, 6 therapeutic drug tests, and 8 drugs

of abuse tests) on P-module and 18 heterogeneous assays

(thyroid, cardiac, anaemia, and tumour markers) on the E-

module, with samples loaded in a simulated routine-type

pattern. The average sample processing times for the vari-

ous request patterns were comparable with those mentioned

previously (< 35 minutes).

4.5. Practicability

With the aid of a questionnaire, the practicability of MOD-

ULAR system was graded as equally good (23% of all scores)

or even better (68%) compared to the evaluators' currently

used routine analysers.

5. DISCUSSION

Overall assessment of the experiments can be rated as posi-

tive. It was the first time that there was an opportunity during

an evaluation to combine various laboratory segments with

an extensive menu for general chemistry, specific proteins,

drugs, and immunochemistry on one platform.

5.1. Imprecision

Since analytical performance was previously verified for the

single MODULAR systems [2, 3 ], this study did not include

extensive analytical performance data. However, one or two

imprecision runs were processed for representative tests from

each analyte group to assure that the system was perform-

ing correctly. Typical within-run CVs of 1 to 3% across the

menu of nearly 90 tests were all within the expected perfor-

mance and can be rated as excellent. We can emphasize here

that the heterogeneous immunoassays performed with the

electrochemiluminescence technology showed reproducibil-

ity similar to the general chemistry tests and well within clin-

ical demands (see Ta ble 1 )[ 10–12].

5.2. Functionality

The overall low CVs for all analyte groups in the simulated

routine imprecision runs proved that general chemistry and

immunochemistry worked very well together, and, that even

under simulated stress routine conditions, there was no in-

dication of systematic or random errors. The 6 high CVs

of the routine simulation experiment occurred in only one

of 3 runs per laboratory, and there was no indication that

the deviant results were reproducible. The routine simula-

tion precision experiments demonstrated good performance

and full functionality of the instrument. Because of the sen-

sitivity of the experimental design, it was possible to iden-

tify one severe instrument problem associated with the E-

module masking/unmasking feature during provocation of

the analyser. The error was corrected with a software upgrade

12 Journal of Automated Methods and Management in Chemistry

0

20

40

60

80

100

120

Time (min)

Maintenance

Reagent

handling

Consumables &

waste handling

Calibration

handling

Quality control

handling

Sample

handling

To t a l

(sum routine

versus SWA)

00:00

01:00

02:00

03:00

04:00

05:00

06:00

07:00

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

Time (h:min)

H747

H917

AxSYM 1 and 2

ACS

RIA (manual)

SWA

Figure 6: Hands-on time on MODULAR system compared to dedicated routine analysers representing 40% of a daily routine workload.

and the correct implementation was confirmed with further

routine simulation runs at all sites. Throughout all other rou-

tine environment testing, the instruments reacted correctly

based on the routine simulation data.

5.3. Sample carryover

MODULAR system runs with new user software, combin-

ing and unifying the functionality and features of the sin-

gle modules and optimizing the processing of clinical chem-

istry and immunochemistry requests. For example, sample

carryover to some sensitive immunoassays cannot occur due

to intelligent sample processing whereby samples with re-

quests for carryover sensitive assays, referred to as high prior-

ity tests, are processed at the immunology module (E) first.

High priority tests are user-definable and do not delay pro-

cessing of other samples, even samples in the same sample

rack. As mentioned in the Results section, processing samples

with high priority requests with "Auto-rerun" activated took

15 minutes longer in comparison to the usual samples. This

however, reduced potential risks and eliminated any manual

operator intervention. If there are only very few specimens

with concentrations above the upper measuring range limit

of the high priority tests, the laboratory manager can decide

to deactivate auto-rerun without any high risk of quality loss

but with acceleration of result availability.

5.4. Workflow

Workflow depends strongly on the laboratory environment,

the sample loading pattern, and on the MODULAR configu-

ration. Our studies show that MODULAR system off ers the

flexibility to fit and meet the requirements of the individual

laboratory. The variations in throughput at the diff erent sites

can be explained by the lab-specific workloads and sample

loading patterns.

The processing times for the sample groups with general

or immunochemistry requests were similar to those known

from the respective stand-alone modules, thus showing that

there was no relevant increase when combining photomet-

ric/ISE and E-modules. In other words, the immunochem-

istry module did not slow down the clinical chemistry mod-

ules. An average processing time of approximately 35 min-

utes for the combined groupwasratedasbeingveryaccept-

able, bearing in mind that those samples were either mea-

sured sequentially on diff erent routine instruments or re-

quired additional hands-on times for splitting/aliquoting in

the routine with the current routine instrumentation. In fact,

when these additional times were included, as done in one

laboratory, the mean sample TAT decreased by three hours

(from 3.5 to 0.5 hours) using MODULAR system.

One laboratory used the

PE combination for simulat-

ing a dedicated immunoassay analyser covering various lab-

oratory segments. In this hospital there is a separate sample

collection and order process for certain analytes, which are

presently performed on a variety of single analysers. There-

fore, sample splitting is not necessary. The current dedicated

analysers for protein determinations, for drug monitoring or

tumour marker measurements could be replaced by a con-

solidated workstation, so that only one operator would be

needed to perform these various immunoassays. The labo-

ratory management assessed a 30 to 50% reduction of man-

power for this work on MODULAR system.

During the daily routine, a certain percentage of as-

says (usually < 5%) need a repetition of the analysis, be-

cause the measuring range or a defined repeat limit based

Paolo Mocarelli et al. 13

on laboratory policy is exceeded. The portion of repeat mea-

surements due to analytical range limitations on MODULAR

system is usually smaller than 0.5% [2 ]. MODULAR system

off ers a user selectable automatic rerun feature, which can be

activated or deactivated for each test.

The advantages of automatic rerun—no need for sam-

ple tracking, retrieval, elimination of manual sample predi-

lution, and no manual reloading—not only increased safety

of results by minimizing possible human error, but also re-

duced processing and hands-on times.

Also, the fact that MODULAR system supports reflex

testing simplifies the workflow. It is not necessary to wait for

the result validation and the confirmation from the ward to

perform the additional reflex assay. This is especially impor-

tant for outpatients since this procedure could avoid a second

hospital visit. Even if samples are held for further tests, reflex

testing is better than the alternatives—measuring for all tests

at the start or manual intervention to locate and transport

the samples. When including the benefits of automatic rerun

analysis and reflex testing , results were available within 30 to

70 minutes.

Since the time of this evaluation, the use of MODULAR

system has confirmed this data during a long period of rou-

tine work. When comparing the hands-on times captured at

the diff erent sites over one to two days, MODULAR system

yielded a clear advantage. Monitoring over an extended pe-

riod would be necessary to obtain more extensive data, but

this exceeded the scope of the study. Nevertheless, it is ob-

vious that there is a potential of saving personnel capaci-

ties since fewer instruments need fewer persons for oper-

ation. MODULAR system requires a skilled operator sim-

ilar in qualification to that of the existing analysers com-

pared in this study. However, this person must also be able to

cope with the validation of a large amount of data produced

within a short time or have autoverification available.

5.5. Practicability

The practicability of MODULAR system met or exceeded the

requirements of all participating laboratories for 91% of all

attributes rated. An opportunity for improvement was seen

in the time required to prepare the analyser for routine use

even though this was one half to three quarters of the time

required for the dedicated routine analysers. Apart from the

QC measurements which were processed directly before rou-

tine sampling start, the flexibility of MODULAR system with

background maintenance features allows other tasks to be

performed at any suitable time throughout the shift. Com-

pletion of initial QC measurements for the extended menu

processed at the diff erent sites took an average 30 minutes.

The main advantage mentioned by the evaluators was the

consolidation eff ect resulting in a simplified workflow with a

reduction of instruments, reduced overall processing time,

reduced hands-on time, and increased effi ciency without in-

creasing staffi ng, yet maintaining or even improving quality.

6. CONCLUSION

Our experience with the MODULAR ANALYTICS SWA in-

dicates that both functionally and practically the analyser is

a favourable addition to the clinical laboratory. Each of the

various module configurations included in this study is eas-

ily and effi ciently managed routine and nonroutine tasks in

the simulated routine scenarios. Overall, samples with com-

bined requests running in routine workloads, from a menu of

about 50 assays, were processed in approximately 35 minutes;

30 to 70 minutes including reruns and reflex testing. We saw

no negative eff ects in the quality or timely reporting of test

results when combining general clinical chemistry with het-

erogeneous immunochemistry assays on the same analyser.

In fact, we found that effi ciency was improved, and, in some

cases substantially decreasing sample turn-around time, op-

erator hands-on time, and personnel, while maintaining or

improving the quality of laboratory processes.

ACKNOWLEDGMENTS

The authors wish to thank all of their coworkers in the re-

spective laboratories and departments participating in the

study for their excellent support. The MODULAR instru-

ment, personal computer with CAEv software, reagents, and

disposables were supplied by Roche Diagnostics for the du-

ration of the study.

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... More importantly, in a tertiary care setup, when at any given time, more than 500 to 700 in-house patients needed 24/7 care, inclusive of efficient turn around time (TAT) testing service from clinical lab, it is imperative to have updated analytical instruments and diagnostic techniques to ensure proficient, quality assured and wide range of services to its customers. However the success of medium-level and tertiary care clinical laboratories in providing superior and improved services 24/7, also placed the laboratories under pressure to do more and thus further enhance their technologies and diagnostic care [1][2][3][4] . In this regard, procuring better, more efficient, analytically advanced and user-friendly instruments is now became a principle, in other words, performance index (PI) for considering a clinical laboratory worthy of referring too [5,6] . ...

... In a routine practice in clinical laboratories, samples needed to be tested simultaneously on several instruments through aliquot preparations, to get a complete profile of patients. Similarly, if a single instrument can generate most of the requested profile of a patient, it still needs to organize its inefficiency, linear analytical steps, different reagents and individual maintenance schedules [1,4,5,10,11] . Procurement of modular system, that can generate maximum number of clinical chemistry profile of a patient within limited time frame, meant both better TAT and efficient delivery, is now been followed, both in developed and developing countries, including Pakistan [2,3] . ...

Inevitably, clinical laboratories are considered a backbone of diagnosis, treatments and management. The present study describes the comparative analysis of analytical precision of iron profile (iron, total iron binding capacity 'TIBC " , Ferritin) on two instruments, the stand-alone conventional Hitachi 912 chemistry analyzer and modular Cobas 6000 c501 system. All standard protocols and procedures were followed for present study with a total of 150 patients (Male = 75, female = 75). For instrumental precision, data originating from our conventional chemistry analyzer instrument (Hitachi 912, Roche Diagnostics), regarding iron, TIBC and ferritin were compared on another instrument, the modular Cobas 6000 c501 (Roche-Diagnostics). The iron profile components were analyzed according to standard methods as per manufacturer advices. Comparative analysis of all three parameters manifested considerably significant correlation regarding instrument to instrument precision and accuracy, which is clearly depicted by more than 90% R 2 in all three parametric regression viz in males: Iron; R 2 = 0.977, TIBC; R 2 = 0.985), Ferritin; 0.979 and in females: Iron ; R 2 = 0.937, TIBC; R 2 = 0.987, Ferritin; R 2 = 0.987. The analytical data showed appreciable regression R 2 correlation of 0.94 to 0.987 depicting efficiency of analytical testing, compatibility and precisions of all three parameters, iron, TIBC and ferritin on both instruments.

... As expected, the processing speed is driven by the number of CC modules. After 1 h, ~3000 requests are ordered on both configurations including one cobas c 701 or cobas c 702 module (3,4), ~3500 requests on the configuration that also includes a cobas c 502 module (1), and ~4100 requests on the dual cobas c 701 configuration (9). Similarly, the SPTs differ on configurations using a single versus dual highthroughput CC modules for similar workloads (SPT of 18 min for workload 9 using dual cobas c 701 modules versus 28 min for workload 3 using a single cobas c 701). ...

Clinical laboratories need to test patient samples precisely, accurately, and efficiently. The latest member of the Roche cobas modular platform family, the cobas 8000 modular analyzer series allows compact and convenient consolidation of clinical chemistry and immunochemistry assays in high-workload laboratories with a throughput of 3 to 15 million tests annually. Here we present the results of studies designed to test the overall system performance under routine-like conditions that were conducted at 14 laboratories over 2 y. Experiments that test analytical performance of the new module were integrated with overall system functionality testing of all modules in different configurations. More than two million results were generated and evaluated for ~100 applications using serum/plasma, urine, or EDTA blood samples. During the workflow studies, eight configurations of the possible 38 combinations were used, covering all available analytical modules. The versatility of the module combinations makes the system customizable to fit the needs of diverse laboratories, allowing precise and accurate analysis of a broad spectrum of clinical chemistry and immunochemistry parameters with short turnaround times. This new system will contribute to the ability of clinical laboratories to offer better service to their customers and support vital clinical decision making.

  • Alfonso Javier Benítez Estévez Alfonso Javier Benítez Estévez
  • José Luis Bedini Chesa

Desde el año 1994 en que apareció la monografía con el título "Selección y Evaluación de Sistemas Analíticos" ha variado mucho el panorama de dichos Sistemas Analíticos, principalmente teniendo en cuenta las normativas referentes a la certificación o acreditación de los Laboratorios Clínicos. La actualización de dicha monografía ha requerido una profunda revisión para poder proporcionar al profesional del Laboratorio Clínico y en particular a los socios de la SEQC de una herramienta práctica de ayuda en la selección y evaluación de dichos Sistemas Analíticos para cada laboratorio en particular. Han colaborado las Comisiones de Metrología y de Gestión de la SEQC para los temas dedicados a los protocolos de evaluación y estudio de costos respectivamente. Con todo ello, la Comisión de Instrumentación y Sistemas Analíticos de la SEQC pretende que la monografía sirva de ayuda y guía para la toma de decisiones correctas ante la perspectiva de renovaciones o cambios tecnológicos en el Laboratorio Clínico.

Unlabelled: The goal of this study was to compare the effects of liposomal and free glucocorticoid formulations on joint inflammation and activity of the hypothalamic-pituitary-adrenal (HPA) axis during experimental antigen-induced arthritis (AIA). A dose of 10mg/kg liposomal prednisolone phosphate (PLP) gave a suppression of the HPA-axis, as measured by plasma corticosterone levels in mice with AIA and in naïve mice. In a subsequent dose-response study, we found that a single dose of 1mg/kg liposomal prednisolone phosphate (PLP) was still equally effective in suppressing joint inflammation as 4 repeated once-daily injections of 10mg/kg free PLP. Moreover, the 1mg/kg liposomal PLP dose gave 22% less suppression of corticosterone levels than 10mg/kg of liposomal PLP at day 14 of the AIA. In order to further optimize liposomal glucocorticoids, we compared liposomal PLP with liposomal budesonide phosphate (BUP) (1mg/kg). At 1 day after treatment, liposomal BUP gave a significantly stronger suppression of joint swelling than liposomal PLP (lip. BUP 98% vs. lip. PLP 79%). Both formulations also gave a strong and lasting suppression of synovial infiltration in equal amounts. However, at day 21 after AIA, liposomal PLP still significantly suppressed corticosterone levels, whereas this suppression was not longer statistically significant for liposomal BUP. Conclusion: Liposomal delivery improves the safety of glucocorticoids by allowing for lower effective dosing. The safety of liposomal glucocorticoid may be further improved by encapsulating BUP rather than PLP.

  • Christopher P Price Christopher P Price

Laboratory medicine has evolved from basic scientific observation and good experimental practice, with a strong emphasis on establishing the mechanisms of disease processes, linked with biomarker discovery, and development of analytical technologies. That evolution is set to move on apace with the mapping of the human genome. However, laboratory medicine is not solely based on robust basic science, but also on the translation of that knowledge into establishing the clinical utility of a marker, translation into evidence of the impact on health outcomes, as well as transformational change to integrate this new knowledge into the delivery of better care for patients. This translational research and the focus on transformational change are crucial in demonstrating value-for-money in the laboratory medicine service.

  • W Bablok
  • R Barembruch
  • Wolfgang Stockmann
  • D Vondersehmitt

The evaluation of new reagents and instruments in clinical chemistry leads to complex studies with large volumes of data, which are difficult to handle. This paper presents the design and development of a program that supports an evaluator in the definition of a study, the generation of data structures, communication with the instrument (analyser), online and offline data capture and in the processing of the results. The program is called CAEv, and it runs on a standard PC under MS-DOS. Version 1 of the program was tested in a multicentre instrument evaluation. The concept and the necessary hardware and software are discussed. In addition, requirements for instrument/host communication are given. The application of the laboratory part of CAEv is described from the user's point of view. The design of the program allows users a high degree of flexibility in defining their own standards with regard to study protocol, and/or experiments, without loss of performance. CAEv's main advantages are a pre-programmed study protocol, easy handling of large volumes of data, an immediate validation of the experimental results and the statistical evaluation of the data.

MODULAR ANALYTICS (Roche Diagnostics) (MODULAR ANALYTICS, Elecsys and Cobas Integra are trademarks of a member of the Roche Group) represents a new approach to automation for the clinical chemistry laboratory. It consists of a control unit, a core unit with a bidirectional multitrack rack transportation system, and three distinct kinds of analytical modules: an ISE module, a P800 module (44 photometric tests, throughput of up to 800 tests/h), and a D2400 module (16 photometric tests, throughput up to 2400 tests/h). MODULAR ANALYTICS allows customised configurations for various laboratory workloads. The performance and practicability of MODULAR ANALYTICS were evaluated in an international multicentre study at 16 sites. Studies included precision, accuracy, analytical range, carry-over, and workflow assessment. More than 700 000 results were obtained during the course of the study. Median between-day CVs were typically less than 3% for clinical chemistries and less than 6% for homogeneous immunoassays. Median recoveries for nearly all standardised reference materials were within 5% of assigned values. Method comparisons versus current existing routine instrumentation were clinically acceptable in all cases. During the workflow studies, the work from three to four single workstations was transferred to MODULAR ANALYTICS, which offered over 100 possible methods, with reduction in sample splitting, handling errors, and turnaround time. Typical sample processing time on MODULAR ANALYTICS was less than 30 minutes, an improvement from the current laboratory systems. By combining multiple analytic units in flexible ways, MODULAR ANALYTICS met diverse laboratory needs and offered improvement in workflow over current laboratory situations. It increased overall efficiency while maintaining (or improving) quality.

  • H Baadenhuijsen
  • P M Bayer
  • H Keller
  • H T Phung

We conducted an European multicentre trial to assess the performance of the new Boehringer Mannheim/Hitachi 717 analysis system. The photometer response was linear up to an absorbance of 2.8. The maximal CV of photometric imprecision was 0.5% for the wavelength pair 340/405 nm within the absorbance range 0.9 to 2.4. For the 13 analytes in our study, mean within-run imprecision was less than 2%, and mean between-day imprecision less than 2.5%. The results obtained with the Hitachi 717 instrument correlated closely with those of comparison instruments. Linearity for the various tests was high and exceeded the manufacturer's claims. No drift was detected during an 8-hour work period; carry over could not be detected under the chosen experimental conditions. The new instrument was readily accepted by the evaluators because of its ease of handling and simple daily maintenance.

  • C. Ricós, V. Alvarez, F. Cava, J. V

A database with reliable information to derive definitive analytical quality specifications for a large number of clinical laboratory tests was prepared in this work. This was achieved by comparing and correlating descriptive data and relevant observations with the biological variation information, an approach that had not been used in the previous efforts of this type. The material compiled in the database was obtained from published articles referenced in BIOS, CURRENT CONTENTS, EMBASE and MEDLINE using ?biological variation & laboratory medicine? as key words, as well as books and doctoral theses provided by their authors. The database covers 316 quantities and reviews 191 articles, fewer than 10 of which had to be rejected. The within- and between-subject coefficients of variation and the subsequent desirable quality specifications for precision, bias and total error for all the quantities accepted are presented. Sex-related stratification of results was justified for only four quantities and, in thes...

Analytical performance and practicability of the new Boehringer Mannheim/Hitachi 747 analysis system were assessed in a multicentre evaluation involving four laboratories. The analytical performance was evaluated according to a protocol similar to the ECCLS guidelines and comprised 13 analytes including enzymes, substrates and electrolytes. About 65,000 results were obtained within three months. The evaluation was planned and supported by a program system called "Computer Aided Evaluation". Acceptance criteria have been established for judging the results. The median of the within-run coefficients of variation (CVs) in control sera of all methods was below 1%, being far below the acceptance limit of 2%. The median of CVs of between-days imprecision was below 2% (acceptance criterion 3%). The high degree of precision prompted us to set up a biometrical model suitable for the differentiation between deviant points, outliers and measurements that can still be explained by the system performance. No relevant drift effects were observed during eight hours. The methods were linear over a wide range, avoiding rerun analysis in most cases. No sample-related carry-over was found. Reagent-dependent carry-over outside the acceptance limits was measured from uric acid to phosphorus to a slight extent, and from triacylglycerols to lipase, as well as from total protein to bilirubin to a perceptible degree. It can be avoided by separating these reagent combinations in the channel arrangement. Taking a systematic deviation of more than 10% as unacceptable, four of the 13 analytes suffered from interference by haemoglobin, one by bilirubin and one by turbidity. The Boehringer Mannheim/Hitachi 747 analysis system is capable of determining serum indices which in combination with the interferogram allow an assessment of the interference. With the exception of chloride the recovery of the assigned values for all control sera showed values between 95 and 105%. Out of 40 method comparison studies for enzymes and substrates, 31 yielded regression equations with less than 5% proportional errors and less than 5% constant errors. Deviations exceeding these acceptance criteria can be explained by differences in the reagent formulation, in the method employed or in calibration. The agreement of the ISE method comparisons was within a +/- 5% deviation over a wide analytical range. Practicability of the Boehringer Mannheim/Hitachi 747 analysis system was assessed with the help of a questionnaire, in which properties of the instrument were quantified, thus permitting a relatively objective rating. The 190 questions were placed in 14 groups, each dealing with an attribute of the instrument.(ABSTRACT TRUNCATED AT 400 WORDS)

  • C G Fraser
  • Per Hyltoft Petersen
  • C Ricós
  • Rainer Haeckel Rainer Haeckel

A Working Group of the European Group for the Evaluation of Reagents and Analytical Systems in Laboratory Medicine proposes, after detailed study of the advantages and disadvantages of available strategies, the following quality specifications for analytical systems for clinical chemistry. Total imprecision should be: (a) less than one-half of the average within-subject biological variation, or (b) less than the state of the art achieved by the best 0.20 fractile of laboratories, whichever is the less stringent. The second approach may be used when data on biological variation do not exist. Inaccuracy should be: (a) less than one-quarter of the group (within- plus between-subject) biological variation, or (b) less than one-sixteenth of the reference interval, when data on group biological variation do not exist, or (c) less than twice the ideal imprecision, if the above specifications are too demanding.

  • P.M.G. Broughton
  • A. H. Gowenlock
  • J J McCormack
  • D.W. Neill

A revised scheme is described for evaluating automatic instruments used in clinical chemistry. Procedures are outlined for the assessment of mechanical and electrical features, and measurement of the accuracy and precision of individual units. Methods are given for the measurement of analytical precision, carryover, cross-contamination, accuracy, and linearity. The safety of equipment and methods of assessing costs are discussed, and the importance of subjective features is noted. The general principles of the evaluation scheme should be applicable to other types of equipment.

  • R W Forsman

Market forces have dramatically influenced the environment in which healthcare is delivered, but these changes do not need to be interpreted negatively by community laboratorians. Only total vertical integration of laboratory medicine can control episode-of-care cost. Opportunities also exist for horizontal integration with community partners to provide geographical coverage and to compete favorably for managed care contracts. Lowering cost through "economies of scale" may apply to the procurement of supplies and equipment, but the delivery of services must be considered in the context of their overall effect on episode-of-care cost. Laboratory services may make up 5% of a hospital's budget but leverage 60-70% of all critical decision-making such as admittance, discharge, and medication. Laboratory outreach can help the medical center's financial stability by: (a) providing tests and service that can reduce or avoid a hospital stay; (b) using the additional volume of testing to distribute existing fixed costs and lower unit cost; and (c) adding revenue as a direct contribution to margin. To successfully compete for contracted managed care services, the laboratory must network with other providers to demonstrate comprehensive access and capacity. Community hospital laboratories perform 50% of all laboratory tests in this country and have adequate excess capacity to fulfill the remaining community needs.

A database with reliable information to derive definitive analytical quality specifications for a large number of clinical laboratory tests was prepared in this work. This was achieved by comparing and correlating descriptive data and relevant observations with the biological variation information, an approach that had not been used in the previous efforts of this type. The material compiled in the database was obtained from published articles referenced in BIOS, CURRENT CONTENTS, EMBASE and MEDLINE using "biological variation & laboratory medicine" as key words, as well as books and doctoral theses provided by their authors. The database covers 316 quantities and reviews 191 articles, fewer than 10 of which had to be rejected. The within- and between-subject coefficients of variation and the subsequent desirable quality specifications for precision, bias and total error for all the quantities accepted are presented. Sex-related stratification of results was justified for only four quantities and, in these cases, quality specifications were derived from the group with lower within-subject variation. For certain quantities, biological variation in pathological states was higher than in the healthy state. In these cases, quality specifications were derived only from the healthy population (most stringent). Several quantities (particularly hormones) have been treated in very few articles and the results found are highly discrepant. Therefore, professionals in laboratory medicine should be strongly encouraged to study the quantities for which results are discrepant, the 90 quantities described in only one paper and the numerous quantities that have not been the subject of study.

  • Francisco L Redondo
  • Pilar Bermudez
  • Claudio Cocco Claudio Cocco
  • Wolfgang Stockmann

The new selective access analyser Cobas Integra 800 from Roche Diagnostics was evaluated in an international multicentre study at six sites. Routine simulation experiments showed good performance and full functionality of the instrument and provocation of anomalous situations generated no problems. The new features on Cobas Integra 800, namely clot detection and dispensing control, worked according to specifications. The imprecision of Cobas Integra 800 fulfilled the proposed quality specifications regarding imprecision of analytical systems for clinical chemistry with few exceptions. Claims for linearity, drift, and carry-over were all within the defined specifications, except urea linearity. Interference exists in some cases, as could be expected due to the chemistries applied. Accuracy met the proposed quality specifications, except in some special cases. Method comparisons with Cobas Integra 700 showed good agreement; comparisons with other analysis systems yielded in several cases explicable deviations. Practicability of Cobas Integra 800 met or exceeded the requirements for more than 95% of all attributes rated. The strong points of the new analysis system were reagent handling, long stability of calibration curves, high number of tests on board, compatibility of the sample carrier to other Roche systems, and the sample integrity check for more reliable analytical results. The improvement of the workflow offered by the 5-position rack and STAT handling like on Cobas Integra 800 makes the instrument attractive for further consolidation in the medium-sized laboratory, for dedicated use of special analytes, and/or as back-up in the large routine laboratory.