+ Site Statistics
References:
52,654,530
Abstracts:
29,560,856
PMIDs:
28,072,755
+ Search Articles
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ PDF Full Text
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn

+ Translate
+ Recently Requested

Application of a statistical software package for analysis of large patient dose data sets obtained from RIS



Application of a statistical software package for analysis of large patient dose data sets obtained from RIS



Radiation Protection Dosimetry 139(1-3): 455-458



For the purpose of patient dose audit, clinical audit and radiology workload analysis, data from Radiology Information Systems (RIS) at many hospitals are collected using a database and the analysis was automated using a statistical package and Visual Basic coding. The database is a Structured Query Language database, which can be queried using an off-the-shelf statistical package, Statistica. Macros were created to automatically format the data to a consistent format between different hospitals ready for analysis. These macros can also be used to automate further analysis such as detailing mean kV, mAs and entrance surface dose per room and per gender. Standard deviation and standard error of the mean are also generated. Graphs can also be generated to illustrate the trends in doses between different variables such as room and gender. Collectively, this information can be used to generate a report. A process that once could take up to 1 d to complete now takes around 1 h. A major benefit in providing the service to hospital trusts is that less resource is now required to report on RIS data, making the possibility of continuous dose audit more likely. Time that was spent on sorting through data can now be spent on improving the analysis to provide benefit to the customer. Using data sets from RIS is a good way to perform dose audits as the huge numbers of data available provide the bases for very accurate analysis. Using macros written in Statistica Visual Basic has helped sort and consistently analyse these data. Being able to analyse by exposure factors has provided a more detailed report to the customer.

(PDF emailed within 0-6 h: $19.90)

Accession: 051607726

Download citation: RISBibTeXText

PMID: 20304769

DOI: 10.1093/rpd/ncq105



Related references

Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets. Medical Physics 40(11): 111718, 2014

Statistical and computer analysis of large sets of exploration geochemical data; special application to the Southeast. Pages 65 1982, 1982

Statistical analysis using SAS software package for data of 2 x 2 contingency table. Zhong Xi Yi Jie He Xue Bao 7(7): 678-682, 2011

Statistical analysis using SAS software package for data of 2 x C and R x 2 contingency tables. Zhong Xi Yi Jie He Xue Bao 7(10): 991-994, 2016

Statistical analysis using SAS software package for data of RxC contingency table (Part two). Zhong Xi Yi Jie He Xue Bao 7(9): 878-882, 2016

Statistical analysis using SAS software package for data of RxC contingency table (Part one). Zhong Xi Yi Jie He Xue Bao 7(8): 784-787, 2011

Statistical mapping analysis of lesion location and neurological disability in multiple sclerosis: Application to 452 patient data sets. NeuroImage 19(3): 532-544, 2003

Statistical analysis for data of multidimensional contingency table with SAS software package (Part three). Zhong Xi Yi Jie He Xue Bao 8(1): 90-94, 2012

Statistical analysis for data of multidimensional contingency table with SAS software package (part two). Zhong Xi Yi Jie He Xue Bao 7(12): 1188-1192, 2016

Statistical analysis for data of multidimensional contingency table with SAS software package (Part four). Zhong Xi Yi Jie He Xue Bao 8(2): 186-189, 2012

Statistical analysis for data of multidimensional contingency table with SAS software package (Part one). Zhong Xi Yi Jie He Xue Bao 7(11): 1086-1089, 2013

Statistical analysis for data of multidimensional contingency table with SAS software package (Part six). Zhong Xi Yi Jie He Xue Bao 8(4): 385-391, 2012

A customizable software for fast reduction and analysis of large X-ray scattering data sets: applications of the new DPDAK package to small-angle X-ray scattering and grazing-incidence small-angle X-ray scattering. Journal of Applied Crystallography 47(Pt 5): 1797-1803, 2014

STXMPy: a new software package for automated region of interest selection and statistical analysis of XANES data. Chemistry Central Journal 4: 11, 2010

Utilizing R software package for dose-response studies: The concept and data analysis. Weed Technology 21(3): 840-848, 2007