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Systemy automatycznej dystrybucji leków (unit dose) w szpitalach w Polsce oraz w wybranych krajach świata

100%

Żuk A., Stępniak P., Bialik W.

Annales Academiae Medicae Silesiensis

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2017

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vol. 71

304-313

EN

Implementing automation and information technology in medicine and pharmacy can reduce the number of medical errors. The automated medicine dispensing system Unit Dose, a computerized system of doctor’s orders and a barcode system to identify a single medicine dose with the patient are modern technologies that avert medical errors. Errors in pharmacotherapy are dangerous for the life and health of patients. The system of distributing medicines in which the hospital pharmacy fills orders for medicines for the hospital ward and not for the individual patient is still dominant in Poland. This system is insecure and poses a risk of generating errors in the administration of medications, in the documentation of medical recommendations and evaluation of the process of pharmacotherapy, especially in financial terms. For a several years now, hospitals in Poland have been introducing the Unit Dose medicine distribution system which enables the creation of electronic doctor’s orders and supervision of these orders by a pharmacist in the hospital pharmacy in terms of interaction between drugs and maintaining a proper drug dosage regimen, as is the case in hospitals around the world where such distribution systems have been used for years. A medicine distribution system is an important element necessary to ensure efficient functioning of the hospital. The Unit Dose medicine distribution system increases the safety of pharmacotherapy and reduces the cost of treatment. It also allows clinical pharmacists working in hospital pharmacies to directly influence the applied pharmacotherapy and work in the hospital ward. The Unit Dose medicine distribution system is the future of Polish and world hospital pharmacy.

PL

Implementowanie automatycznych i informatycznych technologii w medycynie i farmacji może zredukować liczbę błędów medycznych. Nowoczesnymi technologiami, pozwalającym ich uniknąć, są system automatycznego dozowania leków unit dose, wprowadzenie elektronicznych zleceń lekarskich, a także system kodów kreskowych, umożliwiający zidentyfikowanie pojedynczej dawki leku i pacjenta. Błędy w farmakoterapii są niebezpieczne dla życia i zdrowia pacjentów. W Polsce wciąż dominuje system dystrybucji leków, w którym apteka szpitalna realizuje zamówienia na leki dla oddziału szpitalnego, a nie dla indywidualnego pacjenta. System ten jest mało bezpieczny i stwarza ryzyko generowania błędów podczas podawania leków, dokumentowania ordynacji lekarskich oraz oceny procesu farmakoterapii, szczególnie pod względem finansowym. Od kilku lat w szpitalach w Polsce wprowadza się system dystrybucji leków unit dose, który umożliwia tworzenie elektronicznych zleceń lekarskich oraz ich kontrolę przez farmaceutę w aptece szpitalnej pod względem występowania interakcji między lekami i zachowania właściwego schematu dawkowania, jak ma to miejsce w szpitalach na świecie, gdzie od dawna stosowane są takie systemy dystrybucji. Sposób dystrybucji leków jest ważnym elementem, potrzebnym do zapewnienia sprawnego funkcjonowania szpitala. System unit dose zwiększa bezpieczeństwo farmakoterapii i zmniejsza koszty leczenia. Umożliwia również farmaceutom klinicznym pracującym w aptekach szpitalnych bezpośredni wpływ na stosowaną farmakoterapię i pracę na oddziale szpitalnym. System dystrybucji leków unit dose to przyszłość polskiej i światowej farmacji szpitalnej.

2

Smooth muscle contamination analysis in clinical oncology gene expression research

100%

Markowska M., Stępniak P., Wojdan K., Świrski K.

Acta Biochimica Polonica

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2014

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vol. 61

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issue 2

333-340

EN

Gene expression profiling is one of the most explored methods for studying cancers and microarray data repositories have become a rich and important resource. The most common human cancers develop in organs that are walled by smooth muscles. The only method of sample extraction free of unintentional contamination with surrounding tissue is microdissection. Nevertheless, such an approach is implemented infrequently. In the light of the above, there is a possibility of smooth muscle contamination in a large portion of publicly available data. In this study, 2292 publicly available microarrays were analysed to develop a simple screening method for detecting smooth muscle contamination. Microarray Inspector software was used to perform the tests since it has the unique ability to use many selected genes and probesets in a single group as a tissue definition. Furthermore, the test was dataset-independent. Two strategies of tissue definition were explored and compared. The first one depended on Tissue Specific Genes Database (TiSGeD) and BioGPS web resources, which themselves were based on meta-analysis of thousands of microarrays. The second method was based on a differential gene expression analysis of a few hundred preselected arrays. The comparison of the two methods proved the latter to be superior. Among the tested samples of undefined contamination, nearly half were identified to possibly contain significant smooth muscle traces. The obtained results equip researches with a simple method of examining microarray data for smooth muscle contamination. The presented work serves as an example of how to create definitions when searching for other possible contaminations.

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Microarray Inspector: tissue cross contamination detection tool for microarray data

64%

Stępniak P., Maycock M., Wojdan K., Markowska M., Perun S., Srivastava A., Wyrwicz L., Świrski K.

Acta Biochimica Polonica

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2013

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vol. 60

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issue 4

647-655

EN

Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.

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2 Acta Biochimica Polonica

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3 Stępniak P.

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1 Żuk A.

Systemy automatycznej dystrybucji leków (unit dose) w szpitalach w Polsce oraz w wybranych krajach świata

Smooth muscle contamination analysis in clinical oncology gene expression research

Microarray Inspector: tissue cross contamination detection tool for microarray data