Using a Data Quality Framework to Clean Data Extracted from the Electronic Health Record: A Case Study. Article Swipe
Oliwier Dziadkowiec
,
Tiffany J. Callahan
,
Mustafa Ozkaynak
,
Blaine Reeder
,
John Welton
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.13063/2327-9214.1201
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.13063/2327-9214.1201
Objectives: Examine (1) the appropriateness of using a data quality (DQ) framework developed for relational databases as a data-cleaning tool for a dataset extracted from two EPIC databases; and (2) the differences in statistical parameter estimates on a dataset cleaned with the DQ framework and dataset not cleaned with the DQ framework.Background: The use of data contained within electronic health records (EHRs) has the potential to open doors for a new wave of innovative research. Without adequate preparation of such large datasets for analysis, the results might be erroneous, which might affect clinical decision making or results of Comparative Effectives Research studies.Methods: Two Emergency Department (ED) datasets extracted from EPIC databases (adult ED and children ED) were used as examples for examining the five concepts of DQ based on a DQ assessment framework designed for EHR databases. The first dataset contained 70,061 visits, and the second dataset contained 2,815,550 visits. SPSS Syntax examples as well as step-by-step instructions of how to apply the five key DQ concepts these EHR database extracts are provided.Conclusions: SPSS Syntax to address each of DQ concepts proposed by Kahn et al. (2012) was developed. The dataset cleaned using Kahn’s framework yielded more accurate results than the dataset cleaned without this framework. Future plans involve creating functions in R language for cleaning data extracted from the EHR as well as an R package the combines DQ checks with missing data analysis functions.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.13063/2327-9214.1201
- http://egems.academyhealth.org/articles/10.13063/2327-9214.1201/galley/132/download/
- OA Status
- diamond
- Cited By
- 40
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2466978013
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2466978013Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.13063/2327-9214.1201Digital Object Identifier
- Title
-
Using a Data Quality Framework to Clean Data Extracted from the Electronic Health Record: A Case Study.Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-06-24Full publication date if available
- Authors
-
Oliwier Dziadkowiec, Tiffany J. Callahan, Mustafa Ozkaynak, Blaine Reeder, John WeltonList of authors in order
- Landing page
-
https://doi.org/10.13063/2327-9214.1201Publisher landing page
- PDF URL
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https://egems.academyhealth.org/articles/10.13063/2327-9214.1201/galley/132/download/Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://egems.academyhealth.org/articles/10.13063/2327-9214.1201/galley/132/download/Direct OA link when available
- Concepts
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Computer science, Set (abstract data type), Data set, Syntax, Data mining, Data quality, Missing data, Relational database, Information retrieval, Database, Natural language processing, Artificial intelligence, Machine learning, Engineering, Programming language, Operations management, Metric (unit)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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40Total citation count in OpenAlex
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2025: 3, 2024: 4, 2023: 8, 2022: 2, 2021: 9Per-year citation counts (last 5 years)
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27Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.source.display_name | eGEMs (Generating Evidence & Methods to improve patient outcomes) |
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| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
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| primary_location.raw_source_name | eGEMs (Generating Evidence & Methods to improve patient outcomes) |
| primary_location.landing_page_url | https://doi.org/10.13063/2327-9214.1201 |
| publication_date | 2016-06-24 |
| publication_year | 2016 |
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