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Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes

Data presented in this article relates to the research article entitled “Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data” (Peng et al. [1]) in preparation). We provided a set of ICD-10 coding association rules in the a...

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Autores principales: Peng, Mingkai, Sundararajan, Vijaya, Williamson, Tyler, Minty, Evan P., Smith, Tony C., Doktorchik, Chelsea T.A., Quan, Hude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995749/
https://www.ncbi.nlm.nih.gov/pubmed/29896537
http://dx.doi.org/10.1016/j.dib.2018.02.043
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author Peng, Mingkai
Sundararajan, Vijaya
Williamson, Tyler
Minty, Evan P.
Smith, Tony C.
Doktorchik, Chelsea T.A.
Quan, Hude
author_facet Peng, Mingkai
Sundararajan, Vijaya
Williamson, Tyler
Minty, Evan P.
Smith, Tony C.
Doktorchik, Chelsea T.A.
Quan, Hude
author_sort Peng, Mingkai
collection PubMed
description Data presented in this article relates to the research article entitled “Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data” (Peng et al. [1]) in preparation). We provided a set of ICD-10 coding association rules in the age group of 55 to 65. The rules were extracted from an inpatient administrative health data at five acute care hospitals in Alberta, Canada, using association rule mining. Thresholds of support and confidence for the association rules mining process were set at 0.19% and 50% respectively. The data set contains 426 rules, in which 86 rules are not nested. Data are provided in the supplementary material. The presented coding association rules provide a reference for future researches on the use of association rule mining for data quality assessment.
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spelling pubmed-59957492018-06-12 Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes Peng, Mingkai Sundararajan, Vijaya Williamson, Tyler Minty, Evan P. Smith, Tony C. Doktorchik, Chelsea T.A. Quan, Hude Data Brief Medicine and Dentistry    Data presented in this article relates to the research article entitled “Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data” (Peng et al. [1]) in preparation). We provided a set of ICD-10 coding association rules in the age group of 55 to 65. The rules were extracted from an inpatient administrative health data at five acute care hospitals in Alberta, Canada, using association rule mining. Thresholds of support and confidence for the association rules mining process were set at 0.19% and 50% respectively. The data set contains 426 rules, in which 86 rules are not nested. Data are provided in the supplementary material. The presented coding association rules provide a reference for future researches on the use of association rule mining for data quality assessment. Elsevier 2018-02-16 /pmc/articles/PMC5995749/ /pubmed/29896537 http://dx.doi.org/10.1016/j.dib.2018.02.043 Text en © 2018 Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Medicine and Dentistry   
Peng, Mingkai
Sundararajan, Vijaya
Williamson, Tyler
Minty, Evan P.
Smith, Tony C.
Doktorchik, Chelsea T.A.
Quan, Hude
Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title_full Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title_fullStr Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title_full_unstemmed Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title_short Data on coding association rules from an inpatient administrative health data coded by International classification of disease - 10th revision (ICD-10) codes
title_sort data on coding association rules from an inpatient administrative health data coded by international classification of disease - 10th revision (icd-10) codes
topic Medicine and Dentistry   
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995749/
https://www.ncbi.nlm.nih.gov/pubmed/29896537
http://dx.doi.org/10.1016/j.dib.2018.02.043
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