Abstract:
BACKGROUND:In 2015, the German Federal Ministry of Education and Research initiated a large data integration and data sharing research initiative to improve the reuse of data from patient care and translational research. The Observational Medical Outcomes Partnership (OMOP) common data model and the Observational Health Data Sciences and Informatics (OHDSI) tools could be used as a core element in this initiative for harmonizing the terminologies used as well as facilitating the federation of research analyses across institutions. OBJECTIVE:To realize an OMOP/OHDSI-based pilot implementation within a consortium of eight German university hospitals, evaluate the applicability to support data harmonization and sharing among them, and identify potential enhancement requirements. METHODS:The vocabularies and terminological mapping required for importing the fact data were prepared, and the process for importing the data from the source files was designed. For eight German university hospitals, a virtual machine preconfigured with the OMOP database and the OHDSI tools as well as the jobs to import the data and conduct the analysis was provided. Last, a federated/distributed query to test the approach was executed. RESULTS:While the mapping of ICD-10 German Modification succeeded with a rate of 98.8% of all terms for diagnoses, the procedures could not be mapped and hence an extension to the OMOP standard terminologies had to be made.Overall, the data of 3 million inpatients with approximately 26 million conditions, 21 million procedures, and 23 million observations have been imported.A federated query to identify a cohort of colorectal cancer patients was successfully executed and yielded 16,701 patient cases visualized in a Sunburst plot. CONCLUSION:OMOP/OHDSI is a viable open source solution for data integration in a German research consortium. Once the terminology problems can be solved, researchers can build on an active community for further development.
journal_name
Appl Clin Informjournal_title
Applied clinical informaticsauthors
Maier C,Lang L,Storf H,Vormstein P,Bieber R,Bernarding J,Herrmann T,Haverkamp C,Horki P,Laufer J,Berger F,Höning G,Fritsch HW,Schüttler J,Ganslandt T,Prokosch HU,Sedlmayr Mdoi
10.1055/s-0037-1617452subject
Has Abstractpub_date
2018-01-01 00:00:00pages
54-61issue
1issn
1869-0327journal_volume
9pub_type
杂志文章abstract:BACKGROUND:Effective communication is essential to safe and efficient patient care. Additionally, many health information technology (HIT) developments, innovations, and standards aim to implement processes to improve data quality and integrity of electronic health records (EHR) for the purpose of clinical information ...
journal_title:Applied clinical informatics
pub_type: 杂志文章
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更新日期:2011-06-08 00:00:00
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pub_type: 杂志文章,多中心研究
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更新日期:2018-10-01 00:00:00
abstract:BACKGROUND:Kidney disease is under-documented in physician notes. The use of template-guided notes may improve physician recognition of kidney disease early in training. OBJECTIVE:The objective of this study was to determine whether a computerized inpatient renal template note with clinical decision support improves r...
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pub_type: 杂志文章
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更新日期:2013-11-13 00:00:00
abstract:BACKGROUND:We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. OBJECTIVE:To evaluate the ability of VaeTM to classify reports to th...
journal_title:Applied clinical informatics
pub_type: 杂志文章
doi:10.4338/ACI-2012-11-RA-0049
更新日期:2013-02-27 00:00:00
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journal_title:Applied clinical informatics
pub_type: 杂志文章
doi:10.4338/ACI-2014-12-RA-0114
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pub_type: 杂志文章
doi:10.4338/ACI-2016-10-RA-0168
更新日期:2017-05-10 00:00:00
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journal_title:Applied clinical informatics
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doi:10.4338/ACI-2012-06-RA-0024
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更新日期:2018-07-01 00:00:00
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