Informatics

22 pages, 353 KiB

Open AccessArticle

GPTs or Grim Position Threats? The Potential Impacts of Large Language Models on Non-Managerial Jobs and Certifications in Cybersecurity

by Raza Nowrozy

Informatics 2024, 11(3), 45; https://doi.org/10.3390/informatics11030045 - 11 Jul 2024

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Abstract

ChatGPT, a Large Language Model (LLM) utilizing Natural Language Processing (NLP), has caused concerns about its impact on job sectors, including cybersecurity. This study assesses ChatGPT’s impacts in non-managerial cybersecurity roles using the NICE Framework and Technological Displacement theory. It also explores its potential to pass top cybersecurity certification exams. Findings reveal ChatGPT’s promise to streamline some jobs, especially those requiring memorization. Moreover, this paper highlights ChatGPT’s challenges and limitations, such as ethical implications, LLM limitations, and Artificial Intelligence (AI) security. The study suggests that LLMs like ChatGPT could transform the cybersecurity landscape, causing job losses, skill obsolescence, labor market shifts, and mixed socioeconomic impacts. A shift in focus from memorization to critical thinking, and collaboration between LLM developers and cybersecurity professionals, is recommended. Full article

(This article belongs to the Topic AI Chatbots: Threat or Opportunity?)

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14 pages, 1122 KiB

Open AccessArticle

A Framework for Antecedents to Health Information Systems Uptake by Healthcare Professionals: An Exploratory Study of Electronic Medical Records

by Reza Torkman, Amir Hossein Ghapanchi and Reza Ghanbarzadeh

Informatics 2024, 11(3), 44; https://doi.org/10.3390/informatics11030044 - 9 Jul 2024

Viewed by 239

Abstract

Health information systems (HISs) are essential information systems used by organisations and individuals for various purposes. Past research has studied different types of HIS, such as rostering systems, Electronic Medical Records (EMRs), and Personal Health Records (PHRs). Although several past confirmatory studies have quantitatively examined EMR uptake by health professionals, there is a lack of exploratory and qualitative studies that uncover various drivers of healthcare professionals’ uptake of EMRs. Applying an exploratory and qualitative approach, this study introduces various antecedents of healthcare professionals’ uptake of EMRs. This study conducted 78 semi-structured, open-ended interviews with 15 groups of healthcare professional users of EMRs in two large Australian hospitals. Data analysis of qualitative data resulted in proposing a framework comprising 23 factors impacting healthcare professionals’ uptake of EMRs, which are categorised into ten main categories: perceived benefits of EMR, perceived difficulties, hardware/software compatibility, job performance uncertainty, ease of operation, perceived risk, assistance society, user confidence, organisational support, and technological support. Our findings have important implications for various practitioner groups, such as healthcare policymakers, hospital executives, hospital middle and line managers, hospitals’ IT departments, and healthcare professionals using EMRs. Implications of the findings for researchers and practitioners are provided herein in detail. Full article

(This article belongs to the Topic Theories and Applications of Human-Computer Interaction)

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11 pages, 228 KiB

Open AccessArticle

Impact of Hospital Employees’ Awareness of the EMR System Certification on Interoperability Evaluation: Comparison of Public and Private Hospitals

by Choyeal Park and Jikyeong Park

Informatics 2024, 11(3), 43; https://doi.org/10.3390/informatics11030043 - 3 Jul 2024

Viewed by 292

Abstract

This study examined the awareness of the EMR certification system among employees of public and private hospitals that have obtained EMR certification. It also assessed how this awareness impacted the evaluation of EMR interoperability. The objective of this study is to contribute to the stable adoption and further development of EMR system certification in Korea. Data were collected through 3600 questionnaires distributed over three years from 2021 to 2023. After excluding 24 questionnaires owing to missing values or insincere responses, 3576 responses were analyzed. The analysis involved descriptive statistics, cross-tabulation, t-tests, ANOVA, and multiple regression using SPSS 26.0. The significance level (α) for statistical tests was set at 0.05. This study revealed differences in awareness of EMR system certification and interoperability among hospital employees. In both public and private hospitals, awareness of the EMR system certification positively influences the evaluation of interoperability. Full article

(This article belongs to the Section Health Informatics)

18 pages, 1740 KiB

Open AccessArticle

The Mappability of Clinical Real-World Data of Patients with Melanoma to Oncological Fast Healthcare Interoperability Resources (FHIR) Profiles: A Single-Center Interoperability Study

by Jessica Swoboda, Moritz Albert, Catharina Lena Beckmann, Georg Christian Lodde, Elisabeth Livingstone, Felix Nensa, Dirk Schadendorf and Britta Böckmann

Informatics 2024, 11(3), 42; https://doi.org/10.3390/informatics11030042 - 28 Jun 2024

Viewed by 391

Abstract

(1) Background: Tumor-specific standardized data are essential for AI-based progress in research, e.g., for predicting adverse events in patients with melanoma. Although there are oncological Fast Healthcare Interoperability Resources (FHIR) profiles, it is unclear how well these can represent malignant melanoma. (2) Methods: We created a methodology pipeline to assess to what extent an oncological FHIR profile, in combination with a standard FHIR specification, can represent a real-world data set. We extracted Electronic Health Record (EHR) data from a data platform, and identified and validated relevant features. We created a melanoma data model and mapped its features to the oncological HL7 FHIR Basisprofil Onkologie [Basic Profile Oncology] and the standard FHIR specification R4. (3) Results: We identified 216 features. Mapping showed that 45 out of 216 (20.83%) features could be mapped completely or with adjustments using the Basisprofil Onkologie [Basic Profile Oncology], and 129 (60.85%) features could be mapped using the standard FHIR specification. A total of 39 (18.06%) new, non-mappable features could be identified. (4) Conclusions: Our tumor-specific real-world melanoma data could be partially mapped using a combination of an oncological FHIR profile and a standard FHIR specification. However, important data features were lost or had to be mapped with self-defined extensions, resulting in limited interoperability. Full article

(This article belongs to the Section Health Informatics)

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Informatics, Volume 11, Issue 3 (September 2024) – 4 articles

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