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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.
Results
1 to 4 of 4 Research Studies DisplayedAngraal S, Ross JS, Dhruva SS
Merits of data sharing: The Digitalis Investigation Group Trial.
This letter discusses the merits of data sharing, such as its importance in maximizing what can be learned from clinical trials. The letter describes The DIG (Digitalis Investigation Group) trial as an ideal o assess the effects of data sharing.
AHRQ-funded; HS023000.
Citation: Angraal S, Ross JS, Dhruva SS .
Merits of data sharing: The Digitalis Investigation Group Trial.
J Am Coll Cardiol 2017 Oct 3;70(14):1825-27. doi: 10.1016/j.jacc.2017.07.786..
Keywords: Data, Patient-Centered Outcomes Research, Research Methodologies
Ong 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
LeRouge C, Hasselquist MB, Kellogg L
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
A human-centered design (HCD) approach to understanding the data visualization needs for patient-reported outcomes (PRO) in clinical practice can optimize the visual design of an interactive PRO system. Beyond iterative methods, the authors explored the additive value of other HCD methods such as heuristic evaluation. Their evaluation led to several recommendations to improve the display, accessibility, and interpretability of the dashboard’s data.
AHRQ-funded; HS023785.
Citation: LeRouge C, Hasselquist MB, Kellogg L .
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
eGEMS 2017 Apr 20;5(2):Article 6. doi: 10.13063/2327-9214.1283.
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Keywords: Patient-Centered Healthcare, Patient-Centered Outcomes Research, Health Information Technology (HIT), Data, Shared Decision Making