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  4. Quality assurance of integrative big data for medical research within a multihospital system
 
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Quality assurance of integrative big data for medical research within a multihospital system

Journal
Journal of the Formosan Medical Association
Journal Volume
121
Journal Issue
9
Pages
1728-1738
Date Issued
2022
Author(s)
YI-CHIA LEE  
Chao Y.-T.
Lin P.-J.
Yang Y.-Y.
Yang Y.-C.
Chu C.-C.
Wang Y.-C.
Chang C.-H.
Chuang S.-L.
Chen W.-C.
Sun H.-J.
Tsou H.-C.
Chou C.-F.
WEI-SHIUNG YANG  
DOI
10.1016/j.jfma.2021.12.024
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124554695&doi=10.1016%2fj.jfma.2021.12.024&partnerID=40&md5=402230679cc265b742a6522d8b98c2db
https://scholars.lib.ntu.edu.tw/handle/123456789/618760
Abstract
BACKGROUND: The need is growing to create medical big data based on the electronic health records collected from different hospitals. Errors for sure occur and how to correct them should be explored. METHODS: Electronic health records of 9,197,817 patients and 53,081,148 visits, totaling about 500 million records for 2006-2016, were transmitted from eight hospitals into an integrated database. We randomly selected 10% of patients, accumulated the primary keys for their tabulated data, and compared the key numbers in the transmitted data with those of the raw data. Errors were identified based on statistical testing and clinical reasoning. RESULTS: Data were recorded in 1573 tables. Among these, 58 (3.7%) had different key numbers, with the maximum of 16.34/1000. Statistical differences (P < 0.05) were found in 34 (58.6%), of which 15 were caused by changes in diagnostic codes, wrong accounts, or modified orders. For the rest, the differences were related to accumulation of hospital visits over time. In the remaining 24 tables (41.4%) without significant differences, three were revised because of incorrect computer programming or wrong accounts. For the rest, the programming was correct and absolute differences were negligible. The applicability was confirmed using the data of 2,730,883 patients and 15,647,468 patient-visits transmitted during 2017-2018, in which 10 (3.5%) tables were corrected. CONCLUSION: Significant magnitude of inconsistent data does exist during the transmission of big data from diverse sources. Systematic validation is essential. Comparing the number of data tabulated using the primary keys allow us to rapidly identify and correct these scattered errors.
SDGs

[SDGs]SDG3

[SDGs]SDG17

Publisher
Elsevier B.V.
Type
journal article

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To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

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開放取用是從使用者角度提升資訊取用性的社會運動,應用在學術研究上是透過將研究著作公開供使用者自由取閱,以促進學術傳播及因應期刊訂購費用逐年攀升。同時可加速研究發展、提升研究影響力,NTU Scholars即為本校的開放取用典藏(OA Archive)平台。(點選深入了解OA)

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