Evidence map›Paper›PMID 32130175›Full record

ArticleJMIR medical informatics2020

Expedited Safety Reporting to Sponsors Through the Implementation of an Alert System for Clinical Trial Management at an Academic Medical Center: Retrospective Design Study.

Yu Rang Park, HaYeong Koo, Young-Kwang Yoon, Sumi Park, Young-Suk Lim, Seunghee Baek, Hae Reong Kim, Tae Won Kim

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 34% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 1 country.

Yu Rang ParkDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-4210-2094
HaYeong KooClinical Research Center, Asan Institute of Life Sciences, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-9480-9350
Young-Kwang YoonClinical Research Center, Asan Institute of Life Sciences, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-7357-5724
Sumi ParkClinical Trial Center, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-8447-2077
Young-Suk LimClinical Trial Center, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-1544-577X
Seunghee BaekDepartment of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-7063-969X
Hae Reong KimDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-2079-0498
Tae Won KimClinical Research Center, Asan Institute of Life Sciences, Asan Medical Center, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-9522-1997
Asan Medical Center · KRUlsan College · KRYonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly detection or notification of adverse event (AE) occurrences during clinical trials is essential to ensure patient safety. Clinical trials take advantage of innovative strategies, clinical designs, and state-of-the-art technologies to evaluate efficacy and safety, however, early awareness of AE occurrences by investigators still needs to be systematically improved.

objectiveThis study aimed to build a system to promptly inform investigators when clinical trial participants make unscheduled visits to the emergency room or other departments within the hospital.

methodsWe developed the Adverse Event Awareness System (AEAS), which promptly informs investigators and study coordinators of AE occurrences by automatically sending text messages when study participants make unscheduled visits to the emergency department or other clinics at our center. We established the AEAS in July 2015 in the clinical trial management system. We compared the AE reporting timeline data of 305 AE occurrences from 74 clinical trials between the preinitiative period (December 2014-June 2015) and the postinitiative period (July 2015-June 2016) in terms of three AE awareness performance indicators: onset to awareness, awareness to reporting, and onset to reporting.

resultsA total of 305 initial AE reports from 74 clinical trials were included. All three AE awareness performance indicators were significantly lower in the postinitiative period. Specifically, the onset-to-reporting times were significantly shorter in the postinitiative period (median 1 day [IQR 0-1], mean rank 140.04 [SD 75.35]) than in the preinitiative period (median 1 day [IQR 0-4], mean rank 173.82 [SD 91.07], P≤.001). In the phase subgroup analysis, the awareness-to-reporting and onset-to-reporting indicators of phase 1 studies were significantly lower in the postinitiative than in the preinitiative period (preinitiative: median 1 day, mean rank of awareness to reporting 47.94, vs postinitiative: median 0 days, mean rank of awareness to reporting 35.75, P=.01; and preinitiative: median 1 day, mean rank of onset to reporting 47.4, vs postinitiative: median 1 day, mean rank of onset to reporting 35.99, P=.03). The risk-level subgroup analysis found that the onset-to-reporting time for low- and high-risk studies significantly decreased postinitiative (preinitiative: median 4 days, mean rank of low-risk studies 18.73, vs postinitiative: median 1 day, mean rank of low-risk studies 11.76, P=.02; and preinitiative: median 1 day, mean rank of high-risk studies 117.36, vs postinitiative: median 1 day, mean rank of high-risk studies 97.27, P=.01). In particular, onset to reporting was reduced more in the low-risk trial than in the high-risk trial (low-risk: median 4-0 days, vs high-risk: median 1-1 day).

conclusionsWe demonstrated that a real-time automatic alert system can effectively improve safety reporting timelines. The improvements were prominent in phase 1 and in low- and high-risk clinical trials. These findings suggest that an information technology-driven automatic alert system effectively improves safety reporting timelines, which may enhance patient safety.

Indexed as

adverse eventclinical trialearly detectionpatient safety

Identifiers

PMID32130175
PMCPMC7068534
OpenAlexW2995092269

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.