Literature DB >> 22223059

Using a statistical process control chart during the quality assessment of cancer registry data.

Zachary M Myles1, Robert R German, Reda J Wilson, Manxia Wu.   

Abstract

Statistical process control (SPC) charts may be used to detect acute variations in the data while simultaneously evaluating unforeseen aberrations that may warrant further investigation by the data user. Using cancer stage data captured by the Summary Stage 2000 (SS2000) variable, we sought to present a brief report highlighting the utility of the SPC chart during the quality assessment of cancer registry data. Using a county-level caseload for the diagnosis period of 2001-2004 (n=25,648), we found the overall variation of the SS2000 variable to be in control during diagnosis years of 2001 and 2002, exceeded the lower control limit (LCL) in 2003, and exceeded the upper control limit (UCL) in 2004; in situ/localized stages were in control throughout the diagnosis period, regional stage exceeded UCL in 2004, and distant stage exceeded the LCL in 2001 and the UCL in 2004. Our application of the SPC chart with cancer registry data illustrates that the SPC chart may serve as a readily available and timely tool for identifying areas of concern during the data collection and quality assessment of central cancer registry data.

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Year:  2011        PMID: 22223059      PMCID: PMC4498248     

Source DB:  PubMed          Journal:  J Registry Manag        ISSN: 1945-6131


  3 in total

Review 1.  The analysis of disease clusters, Part II: Introduction to techniques.

Authors:  G M Jacquez; R Grimson; L A Waller; D Wartenberg
Journal:  Infect Control Hosp Epidemiol       Date:  1996-06       Impact factor: 3.254

2.  The use of statistical process control charts in hospital epidemiology.

Authors:  J A Sellick
Journal:  Infect Control Hosp Epidemiol       Date:  1993-11       Impact factor: 3.254

3.  [Use of statistical process control charts in the epidemiological surveillance of nosocomial infections].

Authors:  Aglai Arantes; Eduardo da Silva Carvalho; Eduardo Alexandrino Servolo Medeiros; Calil Kairalla Farhat; Orlando César Mantese
Journal:  Rev Saude Publica       Date:  2003-11-27       Impact factor: 2.106

  3 in total
  1 in total

1.  Control charts for chronic disease surveillance: testing algorithm sensitivity to changes in data coding.

Authors:  Naomi C Hamm; Depeng Jiang; Ruth Ann Marrie; Pourang Irani; Lisa M Lix
Journal:  BMC Public Health       Date:  2022-02-28       Impact factor: 3.295

  1 in total

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