Evidence map›Paper›PMID 28815480›Full record

ArticleDrug safety2018

Evaluation of Electronic Healthcare Databases for Post-Marketing Drug Safety Surveillance and Pharmacoepidemiology in China.

Yu Yang, Xiaofeng Zhou, Shuangqing Gao, Hongbo Lin, Yanming Xie, Yuji Feng, Kui Huang, Siyan Zhan

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. [Epidemiological study on the incidence of inflammatory bowel disease in Yinzhou District, Ningbo City from 2011 to 2020].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2022
    Article
  17. Observational
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yu YangDepartment of Epidemiology and Bio-Statistics, School of Public Health, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Xiaofeng ZhouEpidemiology, Pfizer Inc., New York, NY, USA.
Shuangqing GaoBeijing Brainpower Pharmacy Consulting Co. Ltd, Beijing, China.
Hongbo LinCenter for Disease Control of Yinzhou, Ningbo, China.
Yanming XieInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Yuji FengChinese Medical Doctor Association, Beijing, China.
Kui HuangEpidemiology, Pfizer Inc., New York, NY, USA.
Siyan ZhanDepartment of Epidemiology and Bio-Statistics, School of Public Health, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China. siyan-zhan@bjmu.edu.cn.

Funding

Major Project of Science and Technology Planning of Beijing D151100002215002National Natural Science Foundation of China 81473067
6 · The paper itself

Abstract

introductionElectronic healthcare databases (EHDs) are used increasingly for post-marketing drug safety surveillance and pharmacoepidemiology in Europe and North America. However, few studies have examined the potential of these data sources in China.

methodsThree major types of EHDs in China (i.e., a regional community-based database, a national claims database, and an electronic medical records [EMR] database) were selected for evaluation. Forty core variables were derived based on the US Mini-Sentinel (MS) Common Data Model (CDM) as well as the data features in China that would be desirable to support drug safety surveillance. An email survey of these core variables and eight general questions as well as follow-up inquiries on additional variables was conducted. These 40 core variables across the three EHDs and all variables in each EHD along with those in the US MS CDM and Observational Medical Outcomes Partnership (OMOP) CDM were compared for availability and labeled based on specific standards.

resultsAll of the EHDs' custodians confirmed their willingness to share their databases with academic institutions after appropriate approval was obtained. The regional community-based database contained 1.19 million people in 2015 with 85% of core variables. Resampled annually nationwide, the national claims database included 5.4 million people in 2014 with 55% of core variables, and the EMR database included 3 million inpatients from 60 hospitals in 2015 with 80% of core variables. Compared with MS CDM or OMOP CDM, the proportion of variables across the three EHDs available or able to be transformed/derived from the original sources are 24-83% or 45-73%, respectively.

conclusionsThese EHDs provide potential value to post-marketing drug safety surveillance and pharmacoepidemiology in China. Future research is warranted to assess the quality and completeness of these EHDs or additional data sources in China.

Indexed as

Outcome Assessment, Health CareAdolescentAdultAdverse Drug Reaction Reporting SystemsAgedAged, 80 and overChildChild, PreschoolChinaDrug-Related Side Effects and Adverse ReactionsElectronic Health RecordsFemaleHumansInfantInfant, NewbornMale

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.