A Bibliometric Analysis of the Development of ICD-11 in Medical Informatics

A Korean field trial of ICD-11 classification under practical clinical coding rules to clarify the reasons for inconsistencies

Background: The World Health Organization (WHO) announced the release of the 11th edition of the International Classification of Diseases (ICD) in May 2019. Although Statistics Korea has been involved in the ongoing research on ICD-11 since 2017, we have been unable to achieve agreement on the gold standards for case scenario clinical coding in previous studies due to high levels of variance in the coding results of participants. Objective: The purpose of this study was to enhance clinical coding accuracy and consistency in ICD-11 by identifying and clarifying the reasons for these inconsistencies through the use of clear clinical coding rules. Method: A pre-experimental design was applied. Two clinical coding field trials (FTs) were conducted in 'ICD-11 for Mortality and Morbidity Statistics (2022 Mar)' targeting diagnostic terms and case scenarios. In the first FT, clinical coding rules were derived by analysing the results, while the second FT was performed under the clinical coding rules set by the first FT. Results: Across the two FTs, accuracy rates for diagnostic terms (75.8% and 71.8%, respectively) were higher than for case scenarios (62.5% and 71.9%). The main reason for the low accuracy levels was post-coordination. Conclusion: For case scenario clinical coding, low accuracy could be explained by variance in clustering methods between participants. This suggests that the accuracy of ICD-11 clinical coding could be increased if the variance between clustering methods can be reduced through the use of a clear coding guide. A guide for various ambiguous cases in each institution and the provision of a proper post-coordination list in the stem code could also be effective.

Impact of the ICD-11 on the accuracy of clinical coding in Korea

Background: ICD-11 was officially released at the World Health Assembly on 25 May 2019. Objective: To find effective ways to increase the accuracy of coding for diagnostic terms in Korea for a stable transition from Korean modification of ICD-10 (7th Revision of Korean Classification of Disease, KCD-7) to ICD-11. Method: A total of 27 skilled Korean health information managers performed KCD-7 and ICD-11 coding simultaneously (line coding [56]; case coding [17]). Accuracy rates and percentage agreements were calculated, and granularity and difficulty of the ICD-11 were rated by participants. Results: The average accuracy rate of line coding was 71.6 % in ICD-11 and 80.2% in KCD-7, which was similar to results in other studies. The mean percentage agreements for ICD-11 and KCD-7 for line coding were 64.2% and 72.1%, respectively; while for case coding it was 15.3% and 26.6%. Selection criteria for the case scenarios may have influenced the low agreements in case coding. Cluster coding, changes of terms in ICD-11 and removal of codes used in ICD-10 contributed to low agreement in ICD-11 (46.6% of participants reported that granularity of ICD-11 was similar to ICD-10, while 36.9% reported that ICD-11 had finer granularity). In terms of difficulty, 15.3% of participants found line coding difficult and 10.9% found case coding difficult. Conclusion: Provision of more detailed reference guidelines and efficient training for coding professionals by the World Health Organization would enable ICD-11 to be an excellent tool for gathering relevant information about diseases in Korea.

ParsBERT topic modeling of Persian scientific articles about COVID-19

Purpose

The COVID-19 pandemic has indisputably impacted every aspect of human life, and a host of studies have investigated its different aspects. This paper models the contents of Persian literature on COVID-19.

Method

This is a descriptive-exploratory study in which 815 articles were collected from the Magiran database. The articles were published before March 2022. The abstracts and titles were used in the modeling. The modeling was performed by combining the latent Dirichlet allocation (LDA) algorithm with ParsBERT.

Findings

Topic modeling indicated ten major topics, including medicine, psychology, humanities, politics, management, biology, economics, culture, engineering, and religion. The articles under the category of medicine had the largest cluster (42.3%), while engineering and religion had the smallest clusters (1.1% each).

Conclusion

The found topics in the created clusters have structural relationships. The COVID-19 effect on physical and mental health (medical and psychological topics) is the most crucial factor. These clusters provide evidence that COVID-19 affects all facets of human society at three levels: the individual, family, and society. Aside from the ten critical clusters in the humanities field, the utmost disorder is related to teaching and learning. For the first time, this research has presented a model of scientific communication in the field of COVID-19 based on the data collected from a Persian database - Magiran.

Health Information System and Health Care Applications Performance in the Healthcare Arena: A Bibliometric Analysis

There have been several studies centred on health information systems with many insights provided to enhance health care applications globally. These studies have provided theoretical schemes for fortifying the enactment and utilisation of the Health Information System (HIS). In addition, these research studies contribute greatly to the development of HIS in alignment with major stakeholders such as health practitioners and recipients of health care. Conversely, there has been trepidation about HIS' sustainability and resilience for healthcare applications in the era of digitalization and globalization. Hence, this paper investigates research on HIS with a primary focus on health care applications to ascertain its sustainability and resilience amidst the transformation of the global healthcare space. Therefore, using a bibliometric approach, this paper measures the performance of health information systems and healthcare for health care applications using bibliometric data from the web of science database. The findings reveal solid evidence of the constructive transformation of health information systems and health care applications in the healthcare arena, providing ample evidence of the adaptation of HIS and health care applications within the healthcare arena to the fourth industrial revolution and, additionally, revealing the resilient alignment of health care applications and health information systems.

ICD-11: an international classification of diseases for the twenty-first century

BACKGROUND

The International Classification of Diseases (ICD) has long been the main basis for comparability of statistics on causes of mortality and morbidity between places and over time. This paper provides an overview of the recently completed 11th revision of the ICD, focusing on the main innovations and their implications.

MAIN TEXT

Changes in content reflect knowledge and perspectives on diseases and their causes that have emerged since ICD-10 was developed about 30 years ago. Changes in design and structure reflect the arrival of the networked digital era, for which ICD-11 has been prepared. ICD-11's information framework comprises a semantic knowledge base (the Foundation), a biomedical ontology linked to the Foundation and classifications derived from the Foundation. ICD-11 for Mortality and Morbidity Statistics (ICD-11-MMS) is the primary derived classification and the main successor to ICD-10. Innovations enabled by the new architecture include an online coding tool (replacing the index and providing additional functions), an application program interface to enable remote access to ICD-11 content and services, enhanced capability to capture and combine clinically relevant characteristics of cases and integrated support for multiple languages.

CONCLUSIONS

ICD-11 was adopted by the World Health Assembly in May 2019. Transition to implementation is in progress. ICD-11 can be accessed at icd.who.int.

MAPPING ICD-11 (THE 11TH INTERNATIONAL CLASSIFICATION OF DISEASE) TO ICD-10-KM-7TH (THE KOREAN MODIFICATION 7TH OF THE ICD-10) FOR FLEXIBLE TRANSITION TO ICD-11

In the World Health Congress in May 2019, ICD-11 was approved, This study aims to analyze the classification system of the 11th revision of the International Classification of Disease mapping with the ICD-10-KM-7th (ICD-10 Korean Modification 7th) to identify the characteristics of ICD-11 so that it can be flexibly linked to KCD-7 when introduced in Korea. The mapping was conducted based on the ICD-11 frozen version (April 2019). Most of the ICD-11 codes were mapped to a single ICD-10 or KCD-7 code. However, for the diabetes code, more than 80 percent of KCD-7 codes needed to be mapped to one or two post-coordination codes, along with one stem code in ICD-11. ICD-11 is a great classification that has an excellent taxonomy system to express detailed information. For the codes that have been changed or removed, a proper guideline might also be useful for users to understand the changes made in KCD-7 or ICD-10 code.

Towards a systematic description of the field using bibliometric analysis: malware evolution

Malware is a blanket term for Trojan, viruses, spyware, worms, and other files that are purposely created to harm computers, mobile devices, or computer networks. Malware commonly steals, encrypts, damages, and causes a mess in these devices. The growth of malware attacks has a consequence on the growth and attractiveness of mobile features in mobile devices. Most malware research aims to probe the different methods of preventing, analysing, and detecting malware attacks. This paper aims to demonstrate an exhaustive knowledge map of the Android malware by collecting a ten (10) year dataset from the Web of Science database. A bibliometric analysis was employed for analysing articles published between 2010 and 2019. Using the keyword "malware", 5622 articles were retrieved. After scrutinising with the keywords of "Android malware", 1278 articles were then collected. This study provides an overview of the articles, productivity, research area, the Web of Science categories, authors, high-cited articles, institutions, and impact journals examining malware. Research activities are continued by placing terms in the classification of malware detection systems that outline important areas in malware research. From the analysis, it can be concluded that the highest number of publications focusing on malware studies came from the continent of Asia. Additionally, this study discusses the challenges of malware studies in the recent research studies as well as the future direction.

Topic Evolution and Emerging Topic Analysis Based on Open Source Software

Purpose

We present an analytical, open source and flexible natural language processing and text mining method for topic evolution, emerging topic detection and research trend forecasting for all kinds of data-tagged text.

Design/methodology/approach

We make full use of the functions provided by the open source VOSviewer and Microsoft Office, including a thesaurus for data clean-up and a LOOKUP function for comparative analysis.

Findings

Through application and verification in the domain of perovskite solar cells research, this method proves to be effective.

Research limitations

A certain amount of manual data processing and a specific research domain background are required for better, more illustrative analysis results. Adequate time for analysis is also necessary.

Practical implications

We try to set up an easy, useful, and flexible interdisciplinary text analyzing procedure for researchers, especially those without solid computer programming skills or who cannot easily access complex software. This procedure can also serve as a wonderful example for teaching information literacy.

Originality/value

This text analysis approach has not been reported before.