Evidence map›Paper›PMID 34911976›Full record

ArticleScientific reports2021

Preliminary feasibility assessment of CDM-based active surveillance using current status of medical device data in medical records and OMOP-CDM.

Sooin Choi, Soo Jeong Choi, Jin Kuk Kim, Ki Chang Nam, Suehyun Lee, Ju Han Kim, You Kyoung Lee

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
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  5. Using automated methods to detect safety problems with health information technology: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
    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

7 authors.

Sooin ChoiDepartment of Laboratory Medicine and Genetics, Center for Medical Device Safety Monitoring, Soonchunhyang University College of Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea.
Soo Jeong ChoiDepartment of Internal Medicine, Center for Medical Device Safety Monitoring, Soonchunhyang University College of Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea.
Jin Kuk KimDepartment of Internal Medicine, Center for Medical Device Safety Monitoring, Soonchunhyang University College of Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea.
Ki Chang NamDepartment of Medical Engineering, Dongguk University College of Medicine, Gyeongju, 38066, Republic of Korea.
Suehyun LeeDepartment of Biomedical Informatics, College of Medicine, Konyang University, Daejeon, 35365, Republic of Korea.
Ju Han KimDivision of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, 08826, Republic of Korea. juhan@snu.ac.kr.
You Kyoung LeeDepartment of Laboratory Medicine and Genetics, Center for Medical Device Safety Monitoring, Soonchunhyang University College of Medicine, Soonchunhyang University Bucheon Hospital, 170 Jomaru-ro, Bucheon, 14584, Republic of Korea. cecilia@schmc.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, there has been an emerging interest in the use of claims and electronic health record (EHR) data for evaluation of medical device safety and effectiveness. In Korea, national insurance electronic data interchange (EDI) code has been used as a medical device data source for common data model (CDM). This study performed a preliminary feasibility assessment of CDM-based vigilance. A cross-sectional study of target medical device data in EHR and CDM was conducted. A total of 155 medical devices were finally enrolled, with 58.7% of them having EDI codes. Femoral head prosthesis was selected as a focus group. It was registered in our institute with 11 EDI codes. However, only three EDI codes were converted to systematized nomenclature of medicine clinical terms concept. EDI code was matched in one-to-many (up to 104) with unique device identifier (UDI), including devices classified as different global medical device nomenclature. The use of UDI rather than EDI code as a medical device data source is recommended. We hope that this study will share the current state of medical device data recorded in the EHR and contribute to the introduction of CDM-based medical device vigilance by selecting appropriate medical device data sources.

Identifiers

PMID34911976
PMCPMC8674329

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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.