SCALPEL3: A scalable open-source library for healthcare claims databases.
Objective: This article introduces SCALPEL3 (Scalable Pipeline for Health Data), a scalable open-source framework for studies involving Large Observational Databases (LODs). It focuses on scalable medical concept extraction, easy interactive analysis, and helpers for data flow analysis to accelerate...
| Publicado en: | International Journal of Medical Informatics Vol. 141 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Elsevier B.V.
Sep2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146537477&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146537477 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13865056 JR4 jtl: International Journal of Medical Informatics issn: 13865056 maglogo: N pubinfo: dt: Sep2020 vid: 141 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 146537477 146537477 NLM32485553 146537477 10.1016/j.ijmedinf.2020.104203 NLM32485553 146537477 ppct: 1 formats: tig: atl: SCALPEL3: A scalable open-source library for healthcare claims databases. aug: au: Bacry, Emmanuel Gaïffas, Stéphane Leroy, Fanny Morel, Maryan Nguyen, Dinh-Phong Sebiat, Youcef Sun, Dian affil: CEREMADE, Université Paris-Dauphine, PSL, Paris, France sug: subj: Health Care Delivery Reproducibility of Results Resource Databases France ab: Objective: This article introduces SCALPEL3 (Scalable Pipeline for Health Data), a scalable open-source framework for studies involving Large Observational Databases (LODs). It focuses on scalable medical concept extraction, easy interactive analysis, and helpers for data flow analysis to accelerate studies performed on LODs.Materials and Methods: Inspired from web analytics, SCALPEL3 relies on distributed computing, data denormalization and columnar storage. It was compared to the existing SAS-Oracle SNDS infrastructure by performing several queries on a dataset containing a three years-long history of healthcare claims of 13.7 million patients.Results and Discussion: SCALPEL3 horizontal scalability allows handling large tasks quicker than the existing infrastructure while it has comparable performance when using only a few executors. SCALPEL3 provides a sharp interactive control of data processing through legible code, which helps to build studies with full reproducibility, leading to improved maintainability and audit of studies performed on LODs.Conclusion: SCALPEL3 makes studies based on SNDS much easier and more scalable than the existing framework [1]. It is now used at the agency collecting SNDS data, at the French Ministry of Health and soon at the National Health Data Hub in France [2]. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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