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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedOng TC, Kahn MG, Kwan BM
Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.
The researchers designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code. Their results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets.
AHRQ-funded; HS019908; HS022956.
Citation: Ong TC, Kahn MG, Kwan BM .
Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.
BMC Med Inform Decis Mak 2017 Sep 13;17(1):134. doi: 10.1186/s12911-017-0532-3.
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Keywords: Comparative Effectiveness, Data, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Outcomes Research
Ong T, Pradhananga R, Holve E
A framework for classification of electronic health data extraction-transformation-loading challenges in data network participation.
The researchers conducted key-informant interviews with data partner representatives to survey the Extract, Transform, Load (ETL) process challenges faced in clinical data research networks (CDRNs) and registries. The paper concluded that overcoming ETL technical challenges requires significant investments in a broad array of information technologies and human resources. Identifying these technical obstacles can inform optimal resource allocation to minimize the barriers and cost of entry for new data partners into extant networks, which in turn can expand data networks' inclusiveness and diversity.
AHRQ-funded; HS019564.
Citation: Ong T, Pradhananga R, Holve E .
A framework for classification of electronic health data extraction-transformation-loading challenges in data network participation.
eGEMS 2017 Jun 13;5(1):10. doi: 10.5334/egems.222..
Keywords: Comparative Effectiveness, Data, Health Information Technology (HIT), Patient-Centered Outcomes Research, Registries