Evidence map›Paper›PMID 38749529›Full record

ArticleBMJ health & care informatics2024

Taipei Medical University Clinical Research Database: a collaborative hospital EHR database aligned with international common data standards.

Phung-Anh Nguyen, Min-Huei Hsu, Tzu-Hao Chang, Hsuan-Chia Yang, Chih-Wei Huang, Chia-Te Liao, Christine Y Lu, Jason C Hsu

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Phung-Anh NguyenClinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan.ORCID http://orcid.org/0000-0002-7436-9041
Min-Huei HsuOffice of Data Science, Taipei Medical University, Taipei, Taiwan.
Tzu-Hao ChangClinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.
Hsuan-Chia YangClinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.ORCID http://orcid.org/0000-0001-9198-0697
Chih-Wei HuangGraduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
Chia-Te LiaoDivision of Nephrology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.
Christine Y LuDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
Jason C HsuClinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan jasonhsu@tmu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources.

methodsTMUCRD was developed by integrating EHRs from three affiliated hospitals, including Taipei Medical University Hospital, Wan-Fang Hospital and Shuang-Ho Hospital. The data cover over 15 years and include diverse patient care information. The database was converted to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) for standardisation.

resultsTMUCRD comprises 89 tables (eg, 29 tables for each hospital and 2 linked tables), including demographics, diagnoses, medications, procedures and measurements, among others. It encompasses data from more than 4.15 million patients with various medical records, spanning from the year 2004 to 2021. The dataset offers insights into disease prevalence, medication usage, laboratory tests and patient characteristics. DISCUSSION: TMUCRD stands out due to its unique advantages, including diverse data types, comprehensive patient information, linked mortality and cancer registry data, regular updates and a swift application process. Its compatibility with the OMOP CDM enhances its usability and interoperability.

conclusionTMUCRD serves as a valuable resource for researchers and scholars interested in leveraging RWD for clinical research. Its availability and integration of diverse healthcare data contribute to a collaborative and data-driven approach to advancing medical knowledge and practice.

Indexed as

Databases, FactualElectronic Health RecordsHospitals, UniversityHumansTaiwandatabase management systemsevidence-based medicinehealth information managementInformation ManagementMedical Record Linkage

Identifiers

PMID38749529
PMCPMC11097871

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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.