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DOI 10.1093/jamia/ocw168

Медицинская библиотека · Journal of the American Medical Informatics Association : JAMIA · 2017

Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records.

Lee Suehyun, Choi Jiyeob, Kim Hun-Sung, Kim Grace Juyun, Lee Kye Hwa, Park Chan Hee, Han Jongsoo, Yoon Dukyong, Park Man Young, Park Rae Woong, Kang Hye-Ryun, Kim Ju Han

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Аннотация

OBJECTIVE

We propose 2 Medical Dictionary for Regulatory Activities-enabled pharmacovigilance algorithms, MetaLAB and MetaNurse, powered by a per-year meta-analysis technique and improved subject sampling strategy.

MATRIALS AND

METHODS

This study developed 2 novel algorithms, MetaLAB for laboratory abnormalities and MetaNurse for standard nursing statements, as significantly improved versions of our previous electronic health record (EHR)-based pharmacovigilance method, called CLEAR. Adverse drug reaction (ADR) signals from 117 laboratory abnormalities and 1357 standard nursing statements for all precautionary drugs ( n   = 101) were comprehensively detected and validated against SIDER (Side Effect Resource) by MetaLAB and MetaNurse against 11 817 and 76 457 drug-ADR pairs, respectively.

RESULTS

We demonstrate that MetaLAB (area under the curve, AUC = 0.61 ± 0.18) outperformed CLEAR (AUC = 0.55 ± 0.06) when we applied the same 470 drug-event pairs as the gold standard, as in our previous research. Receiver operating characteristic curves for 101 precautionary terms in the Medical Dictionary for Regulatory Activities Preferred Terms were obtained for MetaLAB and MetaNurse (0.69 ± 0.11; 0.62 ± 0.07), which complemented each other in terms of ADR signal coverage. Novel ADR signals discovered by MetaLAB and MetaNurse were successfully validated against spontaneous reports in the US Food and Drug Administration Adverse Event Reporting System database.

DISCUSSION: The present study demonstrates the symbiosis of laboratory test results and nursing statements for ADR signal detection in terms of their system organ class coverage and performance profiles.

CONCLUSION

Systematic discovery and evaluation of the wide spectrum of ADR signals using standard-based observational electronic health record data across many institutions will affect drug development and use, as well as postmarketing surveillance and regulation.

Для цитирования: Lee Suehyun, Choi Jiyeob, Kim Hun-Sung, Kim Grace Juyun, Lee Kye Hwa, Park Chan Hee, Han Jongsoo, Yoon Dukyong, Park Man Young, Park Rae Woong, Kang Hye-Ryun, Kim Ju Han. Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records.. Journal of the American Medical Informatics Association : JAMIA. 2017. DOI: 10.1093/jamia/ocw168.

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