Economic Aspects of the Missing Data Problem - the Case of the Patient Registry

Hatice Uenal and David Hampel
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Hatice Uenal: Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2017, vol. 65, issue 5, 1779-1791

Abstract: Registries are indispensable in medical studies and provide the basis for reliable study results for research questions. Depending on the purpose of use, a high quality of data is a prerequisite. However, with increasing registry quality, costs also increase accordingly. Considering these time and cost factors, this work is an attempt to estimate the cost advantages of applying statistical tools to existing registry data, including quality evaluation. Results for quality analysis showed that there are unquestionable savings of millions in study costs by reducing the time horizon and saving on average € 523,126 for every reduced year. Replacing additionally the over 25 % missing data in some variables, data quality was immensely improved. To conclude, our findings showed dearly the importance of data quality and statistical input in avoiding biased conclusions due to incomplete data.

Keywords: Benford law; data source quality; missing-at-random mechanism; missing data problem; reducing study costs (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:mup:actaun:actaun_2017065051779

DOI: 10.11118/actaun201765051779

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