Associate Professor earns IMIA Best Paper of 2020 recognition

The Editorial Board of the International Medical Informatics Association (IMIA) Yearbook of Medical Informatics 2020 recently recognized a paper co-authored by UTHealth School of Biomedical Informatics (SBMI) Associate Professor医学博士Yang Gong。IMIA named the paper one of the best papers published in 2019 in the Human Factors and Organizational Issues subfield.

Gong’s co-authored paper was one of three papers named “Best Paper” because it was both outstanding and advances the field. Additionally, the paper provides “examples of applying existing frameworks together in novel and highly illuminating ways, showing the value of theory development in human factors.” The winning paper, titled “Understanding health information technology induced medication safety events by two conceptual frameworks,” was co-authored by Gong, SBMI Postdoctoral Fellows Hong Kang, PhD and Ju Wang, PhD, and Visiting Scholar Hongyuan Liang, MD, PhD.

In order to be considered for the recognition, papers must make “original and high impact contributions in the area of human factors and organizational issues in biomedical informatics.” To find applicable papers, IMIA conducted a rigorous extraction process based on queries from Web of Science and PubMed/Medline. The query process resulted in 626 papers that included “interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces.” Next, titles and abstracts of the papers were independently screened by two IMIA editors and the list was reduced to 30 papers. Of the 30 papers evaluated, only 15 were selected as finalist papers that were then reviewed by the two editors and by three external reviewers from internationally renowned research teams. In the end, three papers were named the best.

In their research, the team of co-authors identified a lack of studies on medication errors that present systematic views on health IT in the context of medication errors. Their paper aimed to fill that knowledge gap.

“Medication errors can occur at any point within the medication-use system and can be a double-edged sword that results in the introduction of new paths to errors,” says Gong. “An effective way to prevent errors is to learn from the event reports, including unsafe conditions, near misses, and incidents.”

在论文中,研究人员调查了健康beplay苹果手机能用吗IT-specific safety reports related to medication errors through two views – a composite classification of contributing factors guided bySittig and Singh's sociotechnical model(written by SBMI ProfessorDean Sittig, PhD和Hardeep Singh，医学博士，MPH）和Coiera's information value chain。使用这两个概念框架为了解健康诱导的药物安全报告的背景和影响提供了一个机会。

Gong stated that “the sociotechnical model focuses on causal factors of event occurrence while the information value chain focuses on the health care process and patient outcomes that could be impacted by errors or unsafe conditions when health IT products are utilized.”

TheU.S. Food and Drug Administration (FDA)indicates that it “receives more than 100,000 U.S. reports each year associated with a suspected medication error.” The FDA’s制造商和用户设施设备体验（Maude）数据库包括由制造商，进口商和设备用户设施等强制性记者提交给FDA的大量医疗设备报告列表，以及医疗保健专业人员，患者和消费者等志愿记者。

“The FDA’s MAUDE database is a large, publicly accessible resource that is rich with diverse health IT-related medication error report data,” noted Gong. “We used the database to understand, identify, and prioritize the most significant risks to patient safety.”

Based on the research completed by Gong and his colleagues, they anticipate that the high number of health IT-related medication error reports will only increase, “based upon the observed increment of incoming reports and the pervasive application of health IT,” says Gong.

To learn more about their study, the full paper is available在线的。You can also find the complete IMIAYearbook of Medical Informatics for 2020在线的。

published on 10/05/2020 at 11:30 a.m.