Evidence map›Paper›PMID 30841006›Full record

ArticleApplied clinical informatics2019

Understanding Health Information Technology Induced Medication Safety Events by Two Conceptual Frameworks.

Ju Wang, Hongyuan Liang, Hong Kang, Yang Gong

Abstract read
In one paragraph

Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  14. Human Factors and Organizational Issues.Yearbook of medical informatics · 2020
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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

4 authors.

Ju WangSchool of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, United States.
Hongyuan LiangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Hong KangSchool of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, United States.
Yang GongSchool of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, United States.

Funding

Learning from patient safety events: A case base tool kitR01HS022895 · AHRQ · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI GONG, YANG · 2014 to 2018
$1.2M
AHRQ HHS R01 HS022895
6 · The paper itself

Abstract

backgroundWhile health information technology (health IT) is able to prevent medication errors in many ways, it may also potentially introduce new paths to errors. To understand the impact of health IT induced medication errors, this study aims to conduct a retrospective analysis of medication safety reports.

methodsFrom the U.S. Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience database, we identified reports in which health IT is a contributing factor to medication errors. We applied two conceptual frameworks, Sittig and Singh's sociotechnical model and Coiera's information value chain, to examine the identified reports.

resultsWe identified 152 unique reports on health IT induced medication errors as the final report set for review. The majority (65.13%) of the reports involved multiple contributing factors according to the sociotechnical model. Three dimensions, that is, clinical content, human-computer interface, and people, were involved in more reports than the others. The transition of the effects of health IT on medication practice was summarized using information value chain. Health IT related contributing factors may lead to receiving wrong information, missing information, receiving partial information and delayed information, and receiving wrong information and missing information tend to cause the commission errors in decision-making.

conclusionThe two frameworks provide an opportunity to understand a comprehensive context of safety event and the impact of health IT induced errors on medication safety. The sociotechnical model helps identify the aspects causing medication safety issues. The information value chain helps uncover the effect of the health IT induced medication errors on health care process and patient outcomes.

Indexed as

Health Information SystemsSafetyHumansMedication ErrorsResearch ReportRetrospective Studies

Identifiers

PMID30841006
PMCPMC6402944

What OpenQuestion holds

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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.