Adverse drug reaction early warning using user search data
文献类型：期刊论文
| 作者 | Shang, Wei1 ; Chen, Hsinchun2; Livoti, Christine3
|
| 刊名 | ONLINE INFORMATION REVIEW
 |
| 出版日期 | 2017 |
| 卷号 | 41期号:4页码:524-536 |
| 关键词 | Pharmacovigilance Google Trends Adverse drug reaction Diabetes treatment User search |
| ISSN号 | 1468-4527 |
| DOI | 10.1108/OIR-10-2015-0341 |
| 英文摘要 | Purpose - The purpose of this paper is to propose a framework to detect adverse drug reactions (ADRs) using internet user search data, so that ADR events can be identified early. Empirical investigation of Avandia, a type II diabetes treatment, is conducted to illustrate how to implement the proposed framework. Design/methodology/approach - Typical ADR identification measures and time series processing techniques are used in the proposed framework. Google Trends Data are employed to represent user searches. The baseline model is a disproportionality analysis using official drug reaction reporting data from the US Food and Drug Administration's Adverse Event Reporting System. Findings - Results show that Google Trends series of Avandia side effects search reveal a significant early warning signal for the side effect emergence of Avandia. The proposed approach of using user search data to detect ADRs is proved to have a longer leading time than traditional drug reaction discovery methods. Three more drugs with known adverse reactions are investigated using the selected approach, and two are successfully identified. Research limitations/implications - Validation of Google Trends data's representativeness of user search is yet to be explored. In future research, user search in other search engines and in healthcare web forums can be incorporated to obtain a more comprehensive ADR early warning mechanism. Practical implications - Using internet data in drug safety management with a proper early warning mechanism may serve as an earlier signal than traditional drug adverse reaction. This has great potential in public health emergency management. Originality/value - The research work proposes a novel framework of using user search data in ADR identification. User search is a voluntary drug adverse reaction exploration behavior. Furthermore, user search data series are more concise and accurate than text mining in forums. The proposed methods as well as the empirical results will shed some light on incorporating user search data as a new source in pharmacovigilance. |
| WOS研究方向 | Computer Science ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000407682900006 |
| 出版者 | EMERALD GROUP PUBLISHING LTD |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/26280]  |
| 专题 | 系统科学研究所 |
| 通讯作者 | Shang, Wei |
| 作者单位 | 1.Acad Math & Syst Sci, Beijing, Peoples R China 2.Univ Arizona, Tucson, AZ USA 3.Deerfield Inst, New York, NY USA |
| 推荐引用方式 GB/T 7714 | Shang, Wei,Chen, Hsinchun,Livoti, Christine. Adverse drug reaction early warning using user search data[J]. ONLINE INFORMATION REVIEW,2017,41(4):524-536. |
| APA | Shang, Wei,Chen, Hsinchun,&Livoti, Christine.(2017).Adverse drug reaction early warning using user search data.ONLINE INFORMATION REVIEW,41(4),524-536. |
| MLA | Shang, Wei,et al."Adverse drug reaction early warning using user search data".ONLINE INFORMATION REVIEW 41.4(2017):524-536. |
入库方式： OAI收割
来源：数学与系统科学研究院
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