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Abdolahad Nabiolahi, Nasser Keikha,
Volume 19, Issue 4 (11-2025)
Volume 19, Issue 4 (11-2025)
Abstract
Background and Aim: Point of Care Tests (POCTs) are a laboratory diagnostic system that can be performed at the patient care location and help diagnose diseases quickly. Due to the increase in population, the prevalence of contagious diseases, none access of society members to laboratories, the global need for the availability of modern diagnostic and health technologies at the place of patient care, the aim of research was to explore new aspects of the application of Point of Care Tests to patients as well as the process of developing these technologies in the field of healthcare.
Materials and Methods: A scoping review method were applied by determining the key words through medical subject headings and related articles, searching in the databases of Web of Science, Scopus and PubMed databases as well as Google Scholar, Google and Magiran and Scientific information database. Furthermore to preserve the variety of sources and articles, the criteria for entering the study were English-language articles and no time limit was applied.
Results: Most of the 17 related articles were reviews. The most common technologies in POCTs were lateral flow assays (LFA) that applied to diagnosis of Cryptococcus fungal infection, tuberculosis, hepatitis, legionella, malaria and covid-19, and nucleic acid amplification tests have helped to detect viruses and bacteria using DNA and RNA. From NAAT (Nucleic Acid Amplification Tests) based on microsialate, it can be referred to RT-PCR (Reverse transcription- polymerase chain reactio) and LAMP oop-Mediated- Isothermal Amplification (LAMP), where in recent years are widely used for detection of infectious diseases specially SARS-CoV-19. Additional basic diagnostic tools have focused on Small handheld, POCT devices with a monitoring device, cartridge, and other devices; whereas in the new generations, special focus were on quality assurance, microfluidics, Nano-biosensors and smart phones.
Conclusion: The analysis of published studies showed that the diagnostic tools of tests on POCTs are expanding and have been able to provide better clinical and economic results. In addition to the extensive use of two advanced types of lateral flow assays and nucleic acid amplification tests to diagnose tests at the patient’s bedside; Microfluidics, Nano biosensors and smart phones have also expanded. Quality assurance also requires the determination of accurate quality management procedures, policy programming and necessary policy formulation by officials to achieve reliable results for patient care.
Materials and Methods: A scoping review method were applied by determining the key words through medical subject headings and related articles, searching in the databases of Web of Science, Scopus and PubMed databases as well as Google Scholar, Google and Magiran and Scientific information database. Furthermore to preserve the variety of sources and articles, the criteria for entering the study were English-language articles and no time limit was applied.
Results: Most of the 17 related articles were reviews. The most common technologies in POCTs were lateral flow assays (LFA) that applied to diagnosis of Cryptococcus fungal infection, tuberculosis, hepatitis, legionella, malaria and covid-19, and nucleic acid amplification tests have helped to detect viruses and bacteria using DNA and RNA. From NAAT (Nucleic Acid Amplification Tests) based on microsialate, it can be referred to RT-PCR (Reverse transcription- polymerase chain reactio) and LAMP oop-Mediated- Isothermal Amplification (LAMP), where in recent years are widely used for detection of infectious diseases specially SARS-CoV-19. Additional basic diagnostic tools have focused on Small handheld, POCT devices with a monitoring device, cartridge, and other devices; whereas in the new generations, special focus were on quality assurance, microfluidics, Nano-biosensors and smart phones.
Conclusion: The analysis of published studies showed that the diagnostic tools of tests on POCTs are expanding and have been able to provide better clinical and economic results. In addition to the extensive use of two advanced types of lateral flow assays and nucleic acid amplification tests to diagnose tests at the patient’s bedside; Microfluidics, Nano biosensors and smart phones have also expanded. Quality assurance also requires the determination of accurate quality management procedures, policy programming and necessary policy formulation by officials to achieve reliable results for patient care.
Pezhman Sadeghi, Nader Jahanmehr, Reza Rabiei,
Volume 19, Issue 5 (12-2025)
Volume 19, Issue 5 (12-2025)
Abstract
Background and Aim: Information systems serve different purposes in organizational and management hierarchies. The hospital intelligent management system is an analytical and decision-support management information system that provides information and important performance indicators for managers in hospitals. Considering the role of this system in increasing the efficiency and effectiveness and the lack of academic hospitals having the desired level of productivity, this research was conducted to investigate the effective factors in improving the acceptance of the intelligent hospital management system in the hospitals of Shahid Beheshti University of Medical Sciences (SBMU).
Materials and Methods: This descriptive and correlational research was conducted in 19 hospitals (12 teaching hospitals and 7 non-teaching hospitals) of Shahid Beheshti University of Medical Sciences in 2022. In this study, 126 senior and middle managers and experts of the productivity committee participated. The data of this study were collected Using the Unified Theory of Acceptance and Use of Technology(UTAUT) Questionnaire and for statistical analysis, SPSS software (statistical table and linear and multiple regression tests, sequencing, and chi-square) was used. The validity of the questionnaire was determined using the opinion of research experts and its reliability was also determined using Cronbach’s alpha coefficient (0.824).
Results: Most of the participants in the study were from teaching hospitals (63.2%) and were middle managers (50.8%). Behavioral intentions were identified as the most important factors in the use of system by senior and middle managers and experts of productivity committee (P<0.001). The effort expectancy had the greatest impact on the intention to use the system as compared to the expected components of Performance expectancy and social influence. Also, training and having educational programs on how to use the HIM and its applications can increase the intention and use of the HIM by employees (P<0.001).
Conclusion: Based on the results, the effect of the moderating variables in this study was insignificant. If senior managers and influential people encourage working with the system, and employees also make more effort to learn the system, and working with the system meets their expectations, employees will be willing to use the system. In other words, employees use the system when they believe that this system is user-friendly, valuable, and useful for them.
Materials and Methods: This descriptive and correlational research was conducted in 19 hospitals (12 teaching hospitals and 7 non-teaching hospitals) of Shahid Beheshti University of Medical Sciences in 2022. In this study, 126 senior and middle managers and experts of the productivity committee participated. The data of this study were collected Using the Unified Theory of Acceptance and Use of Technology(UTAUT) Questionnaire and for statistical analysis, SPSS software (statistical table and linear and multiple regression tests, sequencing, and chi-square) was used. The validity of the questionnaire was determined using the opinion of research experts and its reliability was also determined using Cronbach’s alpha coefficient (0.824).
Results: Most of the participants in the study were from teaching hospitals (63.2%) and were middle managers (50.8%). Behavioral intentions were identified as the most important factors in the use of system by senior and middle managers and experts of productivity committee (P<0.001). The effort expectancy had the greatest impact on the intention to use the system as compared to the expected components of Performance expectancy and social influence. Also, training and having educational programs on how to use the HIM and its applications can increase the intention and use of the HIM by employees (P<0.001).
Conclusion: Based on the results, the effect of the moderating variables in this study was insignificant. If senior managers and influential people encourage working with the system, and employees also make more effort to learn the system, and working with the system meets their expectations, employees will be willing to use the system. In other words, employees use the system when they believe that this system is user-friendly, valuable, and useful for them.
Fatemeh Beiranvand, Elham Maserat,
Volume 20, Issue 1 (4-2026)
Volume 20, Issue 1 (4-2026)
Abstract
Background and Aim: The rise in chronic diseases is one of the major challenges facing healthcare systems in the 21st century. Developed countries have turned to health-related quality of life recommender systems to address this issue. This study aims to review and evaluate these systems in the context of chronic diseases.
Materials and Methods: A rapid review method was used in this study. The search was performed using a combination of keywords chronic disease, recommender system, health-related quality of life, and evaluation. The most frequently reviewed systems were related to the endocrine and metabolic diseases group with 15 cases (27.3%), which included diabetes (13 cases) and obesity (2 cases). This was followed by cardiovascular diseases with 9 cases (16.4%), including heart failure (7 cases), coronary artery disease (1 case), and hypertension (1 case), as well as respiratory diseases with 7 cases (12.7%), including chronic lung disease (4 cases), asthma (2 cases), and lung transplantation (1 case). Based on the inclusion criteria, some other chronic diseases including blood diseases and immune mechanism-related disorders with 2 cases (3.6%) including AIDS and hemophilia, cancers with 2 cases (3.6%), digestive diseases with 1 case (1.8%) including hepatitis and urinary tract diseases with 1 (1.8%) were investigated in this study, but they did not have a significant contribution. In order to assess the information needs, a search was conducted in library resources in three databases "Google Scholar", "PubMed" and "Scopus", with the aim of extracting articles of recommender systems in the field of health-related quality of life in chronic diseases, assessment tools and frameworks. The studies included 55 articles published in the period from 2003 to 2022.
Results: The extracted systems in the present studies included 15 general mobile-based applications (27.3%), 16 mobile-based self-management and self-care applications (29.1%), 15 general internet platforms, sites and portals (27.3%), and 9 internet self-management and self-care platforms, sites and portals (16.4%). The studies used 4 methods of usability, effectiveness, satisfaction and technical evaluation. In most studies, usability evaluation was used with the aim of usability in 32 cases (58.2%) and effectiveness with the aim of health-related quality of life (behavior, knowledge and attitude) in 25 cases (45.45%). Ease of use features were used in 18 cases (32.7%), user-friendliness in 14 cases (25.45%), and usefulness in 10 cases (18.18%). In the second phase of the study, 98 assessment tools in the form of interviews and questionnaires from 55 studies were extracted and categorized. Ultimately, 50 usability tools, 26 effectiveness tools, 18 satisfaction tools, and 3 technical tools resulted from this study.
Conclusion: With the growing number of mobile health applications and health-related quality of life systems, choosing the most suitable and effective option for users has become a challenging task. Paying attention to standard and evidence-based components of evaluation of these recommended systems can be effective in improving the quality of life related to patients’ health.
Materials and Methods: A rapid review method was used in this study. The search was performed using a combination of keywords chronic disease, recommender system, health-related quality of life, and evaluation. The most frequently reviewed systems were related to the endocrine and metabolic diseases group with 15 cases (27.3%), which included diabetes (13 cases) and obesity (2 cases). This was followed by cardiovascular diseases with 9 cases (16.4%), including heart failure (7 cases), coronary artery disease (1 case), and hypertension (1 case), as well as respiratory diseases with 7 cases (12.7%), including chronic lung disease (4 cases), asthma (2 cases), and lung transplantation (1 case). Based on the inclusion criteria, some other chronic diseases including blood diseases and immune mechanism-related disorders with 2 cases (3.6%) including AIDS and hemophilia, cancers with 2 cases (3.6%), digestive diseases with 1 case (1.8%) including hepatitis and urinary tract diseases with 1 (1.8%) were investigated in this study, but they did not have a significant contribution. In order to assess the information needs, a search was conducted in library resources in three databases "Google Scholar", "PubMed" and "Scopus", with the aim of extracting articles of recommender systems in the field of health-related quality of life in chronic diseases, assessment tools and frameworks. The studies included 55 articles published in the period from 2003 to 2022.
Results: The extracted systems in the present studies included 15 general mobile-based applications (27.3%), 16 mobile-based self-management and self-care applications (29.1%), 15 general internet platforms, sites and portals (27.3%), and 9 internet self-management and self-care platforms, sites and portals (16.4%). The studies used 4 methods of usability, effectiveness, satisfaction and technical evaluation. In most studies, usability evaluation was used with the aim of usability in 32 cases (58.2%) and effectiveness with the aim of health-related quality of life (behavior, knowledge and attitude) in 25 cases (45.45%). Ease of use features were used in 18 cases (32.7%), user-friendliness in 14 cases (25.45%), and usefulness in 10 cases (18.18%). In the second phase of the study, 98 assessment tools in the form of interviews and questionnaires from 55 studies were extracted and categorized. Ultimately, 50 usability tools, 26 effectiveness tools, 18 satisfaction tools, and 3 technical tools resulted from this study.
Conclusion: With the growing number of mobile health applications and health-related quality of life systems, choosing the most suitable and effective option for users has become a challenging task. Paying attention to standard and evidence-based components of evaluation of these recommended systems can be effective in improving the quality of life related to patients’ health.
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