نادر عالیشان کرمی

This study aims to monitor the scientific productions of the faculty members at Hormozgan University of Medical Sciences (HUMS) during the COVID-19 pandemic indexed by Scopus using the citation and altmetrics indexes.

This is a descriptive-analytical study using a scientometric approach in 2023. The study population consists of the articles of the HUMS faculty members during the pandemic (2020-2022) indexed by Scopus. The search was conducted using the affiliation identifier form of the Scopus database with no restrictions on the type of study. The search yielded 956 articles (152 articles related to COVID-19). Altmetrics extension was used in Google Scholar search engine to check the status of works in social networks. Bibliographic information, citations and altmetrics index of the articles were entered in Excel software and then analyzed using descriptive and analytical methods in SPSS software, version 26.

The rate of attention paid to all articles and COVID-19-related articles was 90.27% and 46%, respectively. The attention was mostly paid by capture (68.89%), social media (8.8%) and view (8.4%), according to the altmetric indicators. There was a strong and positive correlation between the citation index and the altmetrics index of the COVID-19-related articles. These articles were mostly visible on Mendeley, followed by Twitter and Facebook.

Information about the visibility of articles in different social networks along with the number of citations can lead to efficient competition among faculty members in social networks.

Clinical coding is a complex and error-prone process. Correct clinical coding requires high-quality documentation of medical records. This study aimed to identify the quality of medical records documentation and the accuracy of coding with ICD-10 compared to ICD-11.

This cross-sectional descriptive study was conducted in 2022. The samples were chosen from 11638 medical records of patients admitted at the Shahid Mohammadi teaching hospital with the diagnosis of injury, poisoning, and certain other consequences of external causes. Using Cochran's formula, 500 medical records were evaluated. The research was conducted in two stages to check the accuracy of coding and the defects in the documentation of medical records for coding. The research data collection tools were separate checklists for each stage. Data were analyzed using descriptive statistics in SPSS software.

The number of codes allocated to the studied medical records was 1673 and 1468 codes based on ICD-10 and ICD-11 classification systems, respectively. The majority of records (98%) had at least one type of major or minor error, 23% had only major errors, 46% had only minor errors, and 31% had both types of ICD-10 coding errors. Moreover, 81% and 26% of the medical records contained adequate information to fully or relatively fully describe the codes using ICD-10 and ICD-11 classification systems, respectively.

Compared to ICD-10, there were more defects in the documentation of medical records for coding with ICD-11. Development written documentation guidelines by ICD-11, using templates and reminders, and providing feedback to healthcare providers. Using automated coding support tools, coding audits, and continuous training of coders are essential for coding quality improvement.

Timely donation of transplantable organs of brain dead patients is the main source for supplying organs needed by patients waiting for a transplant. Training healthcare staff involved in managing brain dead patients is a major priority of the Iranian Society of Organ Donation. This study determined the effectiveness of the training course of organ donation following brain death on the Knowledge, Attitude, and Practice (KAP) of healthcare staff in Hormozgan.

This quasi-experimental (single group pre-post test) study was conducted in Bandar Abbas in autumn of 2018. Totally, 117 staff involved in managing brain dead patients participated in the study. KAP was assessed by a researcher-made questionnaire in three stages: before and after training, and 2 months later. We used t-independent parametric tests for two-group comparison, repeated measurement for a three-step comparison of KAP, and post-hoc analysis for pairwise comparison of the stages

Eighty-five participants (72.6%) returned the questionnaires in all the stages. They included 67% female, 75.3% married, and 88.2% with bachelor degrees. The mean age was 36.95±7.71 years old. KAP assessed in the 2nd and 3rd stages were significantly higher than the 1st stage. The KAP of men and women improved but not significantly. KAP of participants with bachelor degrees improved significantly, but not for those with higher degrees.

The assessment in the three stages proved that the training course effectively improved KAP of the participants

Ontologies facilitate data integration, exchange, searching and querying. Open Biomedical Ontologies (OBO) Foundry is a solution for creating reference ontologies. In this foundry, the design of ontologies is based on established principles which allow for their interactions as a single system. The purpose of this study is to determine the main features of ontologies developed based on foundry principles. This descriptive cross-sectional study (2017) retrieved data about the ontology components, subject, language and tool from the OBO foundry website, and OntoBee (the default linked data server for the foundry ontologies). The frequency of classes, instances, Object Properties, DataType Properties and Annotation Properties are classified by the use of descriptive statistics. The main subjects of 151 ontologies were Anatomy, Health and Phenotype. Most languages and tools were, respectively, OBO and OBO-edit versions used for the development of ontologies. Five percent of ontologies contained more than 78977 classes, 150 object relations, 39 DataType relations, 110 annotation relations, and 356 instances. Increasing the number of ontologies developed based on OBO foundry principles as well as using OBO language and OBO-Edit is indicative of the fact that ontology developers have accepted the principles and tools.

Ontologies improve the quality of information retrieval (IR). Therefore, it is important to better know the process of ontology engineering and their application in IR. The aim of this research was to identify the engineering methods of ontologies and also their application in biomedical IR.
This review was done through library research method with an analytical approach. Required information for the review was retrieved from Pubmed, Scopus and Web of Science using keywords: "Ontology-based biomedical Information Retrieval", "Information Retrieval", "Biomedical Information Retrieval", "Ontology engineering", "Ontology construction", "Biomedical Ontology" and "Ontology building" without time limit. Five articles addressing an ontology-based biomedical IR system were reviewed.
Studies on ontology based biomedical IR, started in 2004, are not limited to a single country. In general, ontologies are used to manage the semantic metadata. Although most IRs try to develop their own ontologies, reuse of earlier ontologies is a priority. The material for developing ontologies is taken from the literature in the domain. The studied ontologies have been produced by centralized approaches and decentralized approaches and different groups have not been used.
The main purpose of systems for applying ontologies is using them to develop semantic metadata for helping machine reasoning.

To get updated, nurses need to attend in-service training courses. E-learning is a promising solution for providing courses to busy nurses in teaching hospitals. This study aims to evaluate the readiness of teaching hospitals for e-learning implementation specialized for nurse's in-service trainings.
This descriptive-analytical survey was carried out in Bandar Abbas (Iran) teaching hospitals affiliated to Hormozgan University of Medical Sciences (HUMS) from March to June 2016. It included nursing staff, trainers, and related hospital and HUMS authorities. Questionnaires and checklists adopted from earlier studies and customized for this study were used for data collection. Appropriate descriptive and inferential statistical formulas were applied using SPSS version 19.
Data showed that HUMS; in general, was in an optimum situation for e-learning implementation regarding manpower, financial support, technical equipment, strategic plan, content authoring and access to the internet. However, access to information resources and digital library was not good. Hospital authorities stated that they had lack of manpower and required infrastructure. Some of them doubted the appropriateness of e-learning for clinical trainings. Apart from knowledge dimension, nurses reported significantly higher than the average on other study dimensions.
To implement e-learning for nurse's in-service trainings, HUMS must hire experts for authoring and producing content; and technical staff for maintenance the infrastructure. Moreover, e-learning knowledge and skills of people involved in e-learning needs to be improved.

One of the most important branches of scientometrics is citation analysis which offers patterns showing authors’ information searching behavior and authors’ authorship. Citation Analysis provides a pattern of authors’ Information-seeking behavior and also Content Analysis provides a pattern of authorship. This study aimed to analyze the citations and content of published articles in the Hormozgan Medical Journal (HMJ) from 2006 to 2011. In this descriptive study، the citation and content of 211 published articles in the HMJ during 2006-2011 were analyzed. Data analysis was done by SPSS-16 using descriptive statistical methods. Out of 4168 citations in 211 published articles from the view point of citations to the type، the shape and the language of the resources، the maximum were for journals (78. 55%)، print material (98. 27%) and English language (83. 5%). The mean of citations for each article was 19. 7 and authors‘ self-citation was (1. 63%). Out of 746 authors in 211 published articles most of them were male (64. 45%)، most of corresponding -authors were assistant – professors (36. 96%) and most of them were affiliated to HUMS (85 tittles). Most type of articles were original articles (96. 68%)، maximum number of articles were published in 2006 (49 tittles) and most of them were written by more than one author (95. 7%). Although published articles in HMJ have had an acceptable condition from the view point of authorship pattern، considering limited usage of up-to-date and electronic resources، it seems the affiliated organization needs to take measures for improving the authors’ pattern of information–seeking behavior.