End-users' perspectives on factors affecting implementation and utilization of the Iranian electronic health record system: a qualitative study in a developing country.

BACKGROUND: As one of the most important information technologies for storing, managing, and exchanging health information, the electronic health record (EHR) plays a major role in the health system. However, these systems in developing countries have been associated with multidimensional issues. The purpose of the present study was the assessment of nonclinical end-users' points of view on the implementation and utilization of the Iranian electronic health record system. METHODS: This was a large qualitative study conducted in 2021 for 7 months from February to August. In this study, data were collected through in-depth semi-structured interviews with 70 non-clinical end-users in 22 public and six private hospitals of West Azerbaijan province in Iran. To analyze the data, the thematic analysis method was used. RESULTS: The study results indicated that technical, human, cultural, managerial, and financial readiness are the most important factors affecting the implementation of EHRs in Iran. Among the mentioned factors, technical and human readiness were emphasized more by the users. Also, technical, organizational, human, and managerial factors were identified as factors influencing EHRs utilization, and technical and organizational factors had a stronger role in the system utilization. CONCLUSIONS: According to the results, several factors influence EHR implementation and adequate utilization in Iran. To achieve the predetermined goals of this system, implementation issues and problems of using the system should be considered and solved.

Data management system for diabetes clinical trials: a pre-post evaluation study.

BACKGROUND: Data management system for diabetes clinical trials is used to support clinical data management processes. The purpose of this study was to evaluate the quality and usability of this system from the users' perspectives. METHODS: This study was conducted in 2020, and the pre-post evaluation method was used to examine the quality and usability of the designed system. Initially, a questionnaire was designed and distributed among the researchers who were involved in the diabetes clinical trials (n = 30) to investigate their expectations. Then, the researchers were asked to use the system and explain their perspectives about it by completing two questionnaires. RESULTS: There was no statistically significant differences between the users' perspectives about the information quality, service quality, achievements, and communication before and after using the system. However, in terms of the system quality (P = 0.042) and users' autonomy (P = 0.026), the users' expectations were greater than the system performance. The system usability was at a good level based on the users' opinions. CONCLUSION: It seems that the designed system largely met the users' expectations in most areas. However, the system quality and users' autonomy need further attentions. In addition, the system should be used in multicenter trials and re-evaluated by a larger group of users.

Staff and students' perceptions about using telehealth technology in a medical university: A qualitative study.

INTRODUCTION: The use of telehealth technology is a way to promote the health status of the community. The purpose of this study was to investigate staff and students' perceptions about using telehealth technology in a medical university. METHODS: This was a qualitative study completed in 2020. The research participants were 26 university staff and students who took part in semi-structured interviews. To analyze the data, the thematic analysis method was used. RESULTS: The findings of the present study included five themes, 20 subthemes and 58 categories. The main themes were the current status of providing healthcare services at the university, and the strengths, weaknesses, opportunities and threats of using telehealth technology for the university staff and students. CONCLUSION: According to the results, there are many opportunities for using telehealth technology in the medical university. The experiences of other institutes can be used to implement the technology successfully.

Data management in diabetes clinical trials: a qualitative study.

BACKGROUND: Clinical trials play an important role in expanding the knowledge of diabetes prevention, diagnosis, and treatment, and data management is one of the main issues in clinical trials. Lack of appropriate planning for data management in clinical trials may negatively influence achieving the desired results. The aim of this study was to explore data management processes in diabetes clinical trials in three research institutes in Iran. METHOD: This was a qualitative study conducted in 2019. In this study, data were collected through in-depth semi-structured interviews with 16 researchers in three endocrinology and metabolism research institutes. To analyze data, the method of thematic analysis was used. RESULTS: The five themes that emerged from data analysis included (1) clinical trial data collection, (2) technologies used in data management, (3) data security and confidentiality management, (4) data quality management, and (5) data management standards. In general, the findings indicated that no clear and standard process was used for data management in diabetes clinical trials, and each research center executed its own methods and processes. CONCLUSION: According to the results, the common methods of data management in diabetes clinical trials included a set of paper-based processes. It seems that using information technology can help facilitate data management processes in a variety of clinical trials, including diabetes clinical trials.

A Clinical Data Management System for Diabetes Clinical Trials.

BACKGROUND: The use of novel medications and methods to prevent, diagnose, treat, and manage diabetes requires confirmation of safety and efficacy in a well-designed study prior to widespread adoption. Diabetes clinical trials are the studies that examine these issues. The aim of the present study was to develop a web-based system for data management in diabetes clinical trials. METHODS: The present research was a mixed-methods study conducted in 2019. To identify the required data elements and functions to develop the system, 60 researchers completed a questionnaire. The designed system was evaluated using two methods. The usability of the system was initially evaluated by a group of researchers (n = 6) using the think-aloud method, and after system improvement, the system functions were evaluated by other researchers (n = 30) using a questionnaire. RESULTS: The main data elements which were required to develop a case report form included "study data," "participant's personal data," and "clinical data." The functional requirements of the system were "managing the study," "creating case report forms," "data management," "data quality control," and "data security and confidentiality." After using the system, researchers rated the system functions at a "good" level (6.3 ± 0.73) on a seven-point Likert scale. CONCLUSION: Given the complexity of the data management processes in diabetes clinical trials and the widespread use of information technologies in research, the use of clinical data management systems in diabetes clinical trials seems inevitable. The system developed in the current study can facilitate and improve the process of creating and managing case report forms as well as collecting data in diabetes clinical trials.

Nano-based methods for novel coronavirus 2019 (2019-nCoV) diagnosis: A review.

Today, tremendous attention has been devoted to a new coronavirus, SARS-CoV-2 (2019-nCoV), due to severe effects on the global public in all over the world. Rapid and accurate diagnosis of 2019-nCoV are important for early treatment and cutting off epidemic transmission. In this regard, laboratory detection protocols, such as polymerase chain reaction (PCR) and computed tomography (CT) examination, have been utilized broadly for 2019-nCoV detection. Recently, nano-based methods for 2019-nCoV diagnoses are rapidly expanding and declaring comparable results with PCR and CT. In this review, recent advances in nano-based techniques have been highlighted and compared briefly with PCR and CT as well-known methods for 2019-nCoV detection.

Potential small-molecule drugs as available weapons to fight novel coronavirus (2019-nCoV): A review.

Since the new coronavirus known as 2019-nCoV (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) has widely spread in Wuhan, China, with severe pneumonia, scientists and physicians have made remarkable efforts to use various options such as monoclonal antibodies, peptides, vaccines, small-molecule drugs and interferon therapies to control, prevent or treatment infections of 2019-nCoV. However, no vaccine or drug has yet been confirmed to completely treat 2019-nCoV. In this review, we focus on the use of potential available small-molecule drug candidates for treating infections caused by 2019-nCoV.

Clinical Trial Data Management Software: A Review of the Technical Features.

BACKGROUND: Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems. METHODS: Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study. RESULTS: Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development. CONCLUSION: It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.

A Review of Clinical Data Management Systems Used in Clinical Trials.

BACKGROUND: A clinical data management system is a software supporting the data management process in clinical trials. In this system, the effective support of clinical data management dimensions leads to the increased accuracy of results and prevention of diversion in clinical trials. The aim of this review article was to investigate the dimensions of data management in clinical data management systems. METHODS: This study was conducted in 2017. The used databases included Web of Science, Scopus, Science Direct, ProQuest, Ovid Medline and PubMed. The search was conducted over a period of 10 years from 2007 to 2017. The initial number of studies was 101 reaching 19 in the final stage. The final studies were described and compared in terms of the year, country and dimensions of the clinical data management process in clinical trials. RESULTS: The research findings indicated that none of the systems completely supported the data management dimensions in clinical trials. Although these systems were developed for supporting the clinical data management process, they were similar to electronic data capture systems in many cases. The most significant dimensions of data management in such systems were data collection or entry, report, validation, and security maintenance. CONCLUSION: Seemingly, not sufficient attention has been paid to automate all dimensions of the clinical data management process in clinical trials. However, these systems could take positive steps towards changing the manual processes of clinical data management to electronic processes.

Teleophthalmology in Practice: Lessons Learned from a Pilot Project.

INTRODUCTION: Ophthalmology is a medical specialty which may benefit from using telemedicine and teleophthalmology services. Such services are significantly important in the poor, remote, and impassable geographical areas, where there is no access to the ophthalmology services and ophthalmologists. This study aimed to design and implement a teleophthalmology system using the method of store-and-forward. METHODS: The study was conducted in 2015 and consisted of two main phases. The first phase was based requirement analysis, and in the second phase, after designing the prototype, an initial usability testing was undertaken in a teaching hospital. The participants of the study were 10 optometrists and 10 ophthalmologists (cornea specialists). For each phase of the research, a questionnaire was used to collect data, and the collected data were analyzed using descriptive statistics. RESULTS: In this study, users' requirements were initially investigated. Then, the teleophthalmology system was designed based on the literature review and the results derived from the requirements' analysis. Finally, usability testing showed that the users were relatively satisfied with the system. CONCLUSION: According to the results, it can be concluded that the teleophthalmology technology can be used in the country by optometrists and ophthalmologists to improve eye health care services and to prevent the prevalence of curable eye diseases.