RESEARCH PAPER
Application of advanced data collection and quality assurance methods in open prospective study – a case study of PONS project
 
More details
Hide details
1
Institute of Electronics Systems, Warsaw University of Technology, Warsaw, Poland
 
2
Faculty of Health Sciences, Medical University, Warsaw, Poland
 
3
Department of Cancer Epidemiology and Prevention, Maria Skłodowska-Curie Cancer Centre and Institute of Oncology, Warsaw, Poland
 
4
European Health Inequalities Observatory, Institute of Rural Health, Lublin, Poland
 
 
Ann Agric Environ Med. 2011;18(2):207-214
 
KEYWORDS
ABSTRACT
Introduction:
Large-scale epidemiologic studies can assess health indicators differentiating social groups and important health outcomes of the incidence and mortality of cancer, cardiovascular disease, and others, to establish a solid knowledge base for the prevention management of premature morbidity and mortality causes. This study presents new advanced methods of data collection and data management systems with current data quality control and security to ensure high quality data assessment of health indicators in the large epidemiologic PONS study (The Polish-Norwegian Study).

Material and Methods:
The material for experiment is the data management design of the large-scale population study in Poland (PONS) and the managed processes are applied into establishing a high quality and solid knowledge.

Results:
The functional requirements of the PONS study data collection, supported by the advanced IT web-based methods, resulted in medical data of a high quality, data security, with quality data assessment, control process and evolution monitoring are fulfilled and shared by the IT system. Data from disparate and deployed sources of information are integrated into databases via software interfaces, and archived by a multitask secure server.

Conclusions:
The practical and implemented solution of modern advanced database technologies and remote software/hardware structure successfully supports the research of the big PONS study project. Development and implementation of follow-up control of the consistency and quality of data analysis and the processes of the PONS sub-databases have excellent measurement properties of data consistency of more than 99%. The project itself, by tailored hardware/software application, shows the positive impact of Quality Assurance (QA) on the quality of outcomes analysis results, effective data management within a shorter time. This efficiency ensures the quality of the epidemiological data and indicators of health by the elimination of common errors of research questionnaires and medical measurements.

 
REFERENCES (35)
1.
Powles JW, Zatonski W, Vander HS, Ezzati M. Th e contribution of leading diseases and risk factors to excess losses of healthy life in Eastern Europe: burden of disease study. BMC Public Health 2005;5:116.
 
2.
Zatonski W. Th e East-West Health Gap in Europe--what are the causes? Eur J Public Health 2007;17(2):121.
 
3.
World Health Organization, Health Promotion Glossary, WHO, Geneva, 1998, available from: http://www.who.int/hpr/NPH/doc... hp_glossary_en.pdf.
 
4.
Smith BJ, Tang KC, Nutbeam D, WHO Health Promotion Glossary: new terms, Health Promotion International, 2006;21(4):340-345, doi:10.1093/heapro/dal033.
 
5.
Zatoński W, Didkowska J. Closing the gap: Cancer in Central and Eastern Europe (CEE). Eur J Cancer 2008; 44:1425-1437.
 
6.
Zatonski W, Campos H, Willett W. Rapid declines in coronary heart disease mortality in Eastern Europe are associated with increased consumption of oils rich in alpha-linolenic acid. Eur J Epidemiol 2008; 23(1):3-10.
 
7.
Bambra C, Eikemo TA. Welfare state regimes, unemployment and health: a comparative study of the relationship between unemployment and self-reported health in 23 European countries. J Epidemiol Community Health. 2009;63(2):92-8. Epub 2008 Oct 17, PMID: 18930981.
 
8.
Arber S. Social class, non-employment, and chronic illness: continuing the inequalities in health debate. Br Med J (Clin Res Ed). 1987;294(6579):1069-73, PMID: 3107698.
 
9.
Puig-Barrachina V, Malmusi D, Marténez JM, Benach J. Monitoring social determinants of health inequalities: the impact of unemployment among vulnerable groups. Int J Health Serv 2011;41(3):459-82, PMID: 21842573.
 
10.
Caiazzo A, Cardano M, Cois E, Costa G, Marinacci C, Spadea T, Vannoni F, Venturini L, [Inequalities in health in Italy]. Epidemiol Prev 2004;28(3Suppl):i-ix,1-161. PMID:15537046.
 
11.
Zatonski W, et al. (Eds.). Closing the health gap in European Union. Cancer Center and Institute of Oncology, Warsaw; 2008. www.hem. waw.pl.
 
12.
White A, de Sousa B, de Visser R, Hogston R, Aare S, Makara P, et al. (Eds). Th e State of Men’s Health in Europe, Luxembourg, Th e European Commission 2011 http://ec.europa.eu/health/pop... men_health_report_en.pdf.
 
13.
Zatonski WA, Willett W. Changes in dietary fat and declining coronary heart disease in Poland: population based study. BMJ 2005;331:187- 8.
 
14.
Zatonski W, Mikucka M, La Vecchia C, Boyle P. Infant mortality in Central Europe: eff ects of transition. Gac Sanit 2006;20:63-6.
 
15.
Zatonski WA, Manczuk M, Powles J, Negri E. Convergence of male and female lung cancer mortality at younger ages in the European Union and Russia. Eur J Public Health 2007; 17(5):450-4.
 
16.
Zatoński W, (Eds.) with: Mańczuk M, Sulkowska U, and the HEM Project team. Closing the health gap in European Union, Cancer Center and Institute of Oncology, Warsaw 2008.
 
17.
Didkowska J, Manczuk M, McNeill A, Powles J, Zatonski W. Lung cancer mortality at ages 35-54 in the European Union: ecological study of evolving tobacco epidemics. BMJ 2005;331:189-91.
 
18.
Bosetti C, Levi F, Lucchini F, Zatonski WA, Negri E, La Vecchia C. Worldwide mortality from cirrhosis: An update to 2002. J Hepatol 2007;46:827-39.
 
19.
Jha P, Peto R, Zatonski W, Boreham J, Jarvis MJ, Lopez AD. Social inequalities in male mortality, and in male mortality from smoking: indirect estimation from national death rates in England and Wales, Poland, and North America. Lancet 2006;368(9533): 367-70.
 
20.
Zatoński WA, Sulkowska U, Mańczuk M, Rehm J, Boff etta P, Lowenfels AB, La Vecchia C. Liver Cirrhosis Mortality in Europe, with Special Attention to Central and Eastern Europe. Eur Addict Res 2010;16:193- 201.
 
21.
Horn W, Buchstaller W, Trappl R. Knowledge structure defi nition for an expert system in primary medical care, Proceeding IJCAI’81 Proceedings of the 7th international joint conference on Artifi cial intelligence, Morgan Kaufmann Publishers Inc. San Francisco, CA, USA 1981;2:850-852.
 
22.
Swe T, Swea M, Sai N, Kham M. Case-based medical diagnostic knowledge structure using ontology, Th e 2nd International Conference on Computer and Automation Engineering (ICCAE), 2010:729 – 733.
 
23.
Lavrac N, Keravnou E, Zupan B. Intelligent Data Analysis in Medicine, 2000, 1-62, available from: http://citeseerx.ist.psu.edu/v... ary?doi=10.1.1.26.175.
 
24.
Wojtyła A, Biliński P, Jaworska-Łuczak B. Regulatory strategies to ensure food and feed safety in Poland – update review. Ann Agric Environ Med 2010;17:215–220.
 
25.
Raphael D. Shaping public policy and population health in the United States: why is the public health community missing in action? Int J Health Serv. 2008;38(1):63-94, PMID: 18341123.
 
26.
Prokscha S. Pract ical Guide to CLINICAL DATA MANAGEMENT, CRC Press, Boca Raton, 2007.
 
27.
Garcia-Molina H, Ullman JD, Widom J, Database Systems: Th e Complete Book, 2/E: Prentice Hall, 2009.
 
28.
U.S. Department of Health and Human Services, Food and Drug Administration, Guidance for Industry - Computerized Systems Used in Clinical Investigations, May 2007, available from: http://www.fda. gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/ Guidances/UCM070266.pdf.
 
29.
FDA, Good Clinical Practice VICH GL9, Guidance for Industry GOOD CLINICAL PRACTICE VICH GL9, June 2000, available from: http://w w w.fda.gov/downloads/AnimalVeterinar y/ GuidanceComplianceEnforcement/GuidanceforIndustry/UCM052417. Pdf.
 
30.
United States Environmental Protection Agency, Data Quality Assessment: Statistical Methods for Practitioners EPA QA/G-9S, Washington, DC 20460, EPA/240/B-06/003, February 2006, available from: http://www.epa.gov/QUALITY/qs-... nal.pdf.
 
31.
Project PONS, offi cial web-site, available from: http://www.projectpons. pl/en_pages.html,3,1,about-the-pons-project.
 
32.
European Medicines Agency, Guideline for Good Clinical Practice, ICH Topic E 6 (R1), July 2002, available from: http://www.emea.europa.eu/docs... Scientifi c_guideline/2009/09/WC500002874.pdf.
 
33.
Integrated computer system of clinic management KS-Somed, KAMSOFT SA, available from: http://www.kamsoft .pl/prod/somed/ info.htm.
 
34.
LimeSurvey project, LimeSurvey 1.91+ release, http://www.limesurvey. org.
 
35.
Gunter TD, Terry NP. Th e Emergence of National Electronic Health Record Architectures in the United States and Australia: Models, Costs, and Questions, J Med Internet Res 2005;7(1): Published online 2005 March 14. doi: 10.2196/jmir.7.1.e3, available online from: http://www. jmir.org/2005/1/e3/.
 
eISSN:1898-2263
ISSN:1232-1966
Journals System - logo
Scroll to top