Daria Pašalić
Department of Medical Chemistry, Biochemistry and Clinical Chemistry
Zagreb University School of Medicine
Šalata ul 2.
10 000 Zagreb, Croatia
Phone +385 (1) 4590 205; +385 (1) 4566 940
E-mail: dariapasalic [at] gmail [dot] com

Useful links

P01-1 (Oral presentation)

Miler M, Šimundić AM, Štefanović M, Ferenec-Ružić D, Kvaternik M, Topić E, Vrkić N. P01-1: How to provide comparability of results from two analytical systems? Biochemia Medica 2009;19(Suppl 1):S105-S106.
University Department of Chemistry, Sestre Milosrdnice University Hospital, Zagreb, Croatia
Corresponding author: marijana [dot] miler [at] gmail [dot] com
Introduction: Each accredited laboratory according to HRN EN ISO 15189 standard should provide comparability of results if the examinations are performed using different procedures or equipment. The comparability is relevant because allows fast and accurate results reporting regardless to the analytical system used, to the best for the patient care. The aim of this study was to present a model in University Department of Chemistry, Sestre milosrdnice University hospital, which provides emergency tests results comparability of Olympus AU 2700 and AU 640 analyzers on daily basis.
Materials and methods: Olympus AU2700 served as the reference analyzer, and Olympus AU640 for the comparison of the results. Commercially available control samples Control serum 1 and 2 (Olympus, Hamburg, Germany) were used for the following analytes: ALT, AMIL, AST, total and direct bilirubin, Ca, CK, CK-MB, Cl, glucose, potassium, creatinin, LDH, sodium, total protein, urea. CRP concentration was determined from commercially available control ITA Control serum level 1 and 2, and urine amylase and glucose were determined from Urine chemistry control 1 and 2 (Bio-Rad Laboratories, Irving, CA, USA). Results were compared during the representative period of 60 days.
The biases of comparative analyzer were calculated according to the following equation: (100-(concentration AU640/concentration AU2700)x100). Values are expressed as percentages with maximum allowed bias defined according to Croatian Society of Medical Biochemists external quality assessment criteria. All observed biases were within the acceptance limits.
Results: Average biases for all analytes ranged from 0% to maximum 16.5% for low control samples, and between 0 and 12% for high controls.The highest bias in low levels control samples was observed in direct bilirubin (4.2%) and minimum bias in Na (1.2%). In high controls, CK-MB activity bias was the largest (4.6%) and Cl the smallest (1.0%).
Conclusions: Our model continuously provides comparability and analytical quality of emergency laboratory test results.
P01-2 (Oral presentation)
Nikolac N, Šimundić AM, Čipak A, Štefanović M, Vukasović I, Vrkić N. PO1-2: Turn-around-time in emergency biochemistry laboratory. Biochemia Medica 2009;19(Suppl 1):S106.
University Department of Chemistry, Sestre Milosrdnice University Hospital, Zagreb, Croatia
Corresponding author: nora [dot] nikolac [at] gmail [dot] com
Introduction: Assuring and continuous monitoring of turn-around-time (TAT) is essential for adequate patient care and should be kept under 1 hour in emergency laboratories. Automation and informatization of work processes in hospitals and laboratories should decrease laboratory TAT. Careful monitoring and reporting of TAT should have the same effect.
Aim: We aimed to investigate whether there is a difference in TAT in emergency biochemistry laboratory accredited according to standard HRN EN ISO 15189 in three different periods: initial period (period I., September 2008), after implementing hospital information system in some hospital wards (period II., January 2009) and after implementing system of daily reports on TAT within laboratory (period III., April 2009).
Materials and Methods: Data on TAT for emergency biochemistry laboratory are collected using self-made application in Microsoft Access 2003 program. Recorded parameters were: total sample number, average TAT, average TAT excess and proportion of samples that exceeded TAT (number of outliers).
Results: Total sample number in periods I., II. and III. was 10,816, 11,354 and 10,570. Average TAT was 42, 43 and 38 minutes and average TAT excess was 21, 22 and 16 minutes. Total number of outliers was: 910 (8.4%), 951 (8.4%) and 715 (6.8%). There was a statistically significant difference in number of outliers (P < 0.001; Chi-square). Post hoc testing revealed that there was no difference between periods I. and II., while there was significantly less outliers in period III. (P < 0.001; z-test).
Conclusion: Implementing of hospital information system did not decrease laboratory turn-around-time; however the decrease is recorded after implementing application for reporting on TAT within laboratory.
Buljanović V1, Patajac H2, Petrovečki M3. PO1-3: Break-even analysis for a clinical biochemistry laboratory with a real model and simulated model of increased laboratory test volume. Biochemia Medica 2009;19(Suppl 1):S107.
1General Hospital Našice, Našice, Croatia
2Adris group d.d, Rovinj, Croatia
3University School of Medicine, Rijeka and Dubrava Clinical Hospital in Zagreb, Croatia
Corresponding author: vikica [dot] buljanovic [at] os [dot] t-com [dot] hr
Introduction: A break-even point for a biochemistry laboratory is an economic expression referring to the volume of testing at which laboratory revenues equal expenses and the profit is zero. In other words, gains equal losses. If a break-even point is determined for the volume of a clinical laboratory testing within one-year period, then it may also be determined in a simulated model of increased volume of testing over the same period of time. It is a business aspect of laboratory work.
Methods: A specialized clinical biochemistry laboratory was used as a model for a break-even analysis for 2007. To carry out the analysis, the revenue that covered the expenses had to be determined. At that point, the gain equaled zero. Laboratory test fees were the revenues, whereas the resources needed to operate the laboratory were the expenses.
Results: In 2007, the total laboratory revenue was 6.15 million HRK. The break-even point was achieved at 83% of the current volume of business. It meant that the laboratory had to make 5.10 million HRK in revenue to break even. The volume of laboratory work could be realistically increased by 10%. In case of the 10% increase in the volume of work, the revenue would amount to 6.77 million HRK and the break-even point would be achieved at 76% of the maximum volume of business.
Conclusion: The break-even point of 76% falls within the area of high proportion of utilization. This proportion shows that high utilization of laboratory work is needed to achieve positive results. It also shows that a relatively small decrease in the volume of laboratory tests would produce negative business results. If the laboratory services were offered on the market, the laboratory would be unlikely to withstand the pressure of competition if its volume of work decreased.