A NoSQL document based eCRF system for study of vaccines with variable adverse events case study on COVID19 vaccines
In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for e...
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| Published in: | Scientific reports Vol. 15; no. 1; pp. 20453 - 17 |
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| Language: | English |
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Nature Publishing Group UK
01.07.2025
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| ISSN: | 2045-2322, 2045-2322 |
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| Abstract | In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for eCRF, which has the nature of a form, is the document-oriented model. This paper develops and evaluates a reporting system for drug intervention studies with high variability in adverse events that utilizes a document-based NoSQL data model and the eCRF nature, allowing for the management of structured and unstructured data. The main objective of the research is to create a flexible, fast, and efficient system for collecting and analyzing data related to drug/vaccine adverse events, especially the COVID-19 vaccine, for stakeholders. This research is of an applied-descriptive type. In this research, first, after studying library resources, the requirements and requirements for the design of the proposed system were determined in the form of the Software requirements specification (SRS) standard. Then, the design and implementation included modeling and creating a prototype of the web-based system. To evaluate usability, the User Experience Questionnaire (UEQ) was used, system security was assessed using the Application Security Verification Standard (ASVS) questionnaire, and a comparative evaluation of the performance between MongoDB and SQLServer was performed. This research was conducted with the aim of designing and evaluating a reporting system for COVID-19 vaccine side effects, based on a document-oriented data model. It includes key components such as the information and side effects collection module, the document management module, and the reporting module. The results indicated that the user experience of the system, in terms of attractiveness, transparency, efficiency, reliability, motivation, and innovation, had an average score of 2.31, placing it within the top 10% of results. Additionally, the evaluations showed that the system employs effective security controls; however, improvements were needed in certain areas such as meeting management and authentication. A comparative assessment of the performance between the document-oriented data model and the relational data model demonstrated that the proposed system was able to provide better performance in response time and management of unstructured data. Evaluations have shown that utilizing case report forms, along with the advantages of a document-oriented data model, can be effective in collecting the minimum necessary data set for interventional studies, particularly those related to drug side effects such as the COVID-19 vaccine. Given the variable nature of the virus and the potential for unknown side effects, this requires flexible and precise approaches. Additionally, the use of the existing system, considering the results of the security and usability assessment, could be effective if access to external systems is improved. |
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| AbstractList | In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for eCRF, which has the nature of a form, is the document-oriented model. This paper develops and evaluates a reporting system for drug intervention studies with high variability in adverse events that utilizes a document-based NoSQL data model and the eCRF nature, allowing for the management of structured and unstructured data. The main objective of the research is to create a flexible, fast, and efficient system for collecting and analyzing data related to drug/vaccine adverse events, especially the COVID-19 vaccine, for stakeholders. This research is of an applied-descriptive type. In this research, first, after studying library resources, the requirements and requirements for the design of the proposed system were determined in the form of the Software requirements specification (SRS) standard. Then, the design and implementation included modeling and creating a prototype of the web-based system. To evaluate usability, the User Experience Questionnaire (UEQ) was used, system security was assessed using the Application Security Verification Standard (ASVS) questionnaire, and a comparative evaluation of the performance between MongoDB and SQLServer was performed. This research was conducted with the aim of designing and evaluating a reporting system for COVID-19 vaccine side effects, based on a document-oriented data model. It includes key components such as the information and side effects collection module, the document management module, and the reporting module. The results indicated that the user experience of the system, in terms of attractiveness, transparency, efficiency, reliability, motivation, and innovation, had an average score of 2.31, placing it within the top 10% of results. Additionally, the evaluations showed that the system employs effective security controls; however, improvements were needed in certain areas such as meeting management and authentication. A comparative assessment of the performance between the document-oriented data model and the relational data model demonstrated that the proposed system was able to provide better performance in response time and management of unstructured data. Evaluations have shown that utilizing case report forms, along with the advantages of a document-oriented data model, can be effective in collecting the minimum necessary data set for interventional studies, particularly those related to drug side effects such as the COVID-19 vaccine. Given the variable nature of the virus and the potential for unknown side effects, this requires flexible and precise approaches. Additionally, the use of the existing system, considering the results of the security and usability assessment, could be effective if access to external systems is improved. In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for eCRF, which has the nature of a form, is the document-oriented model. This paper develops and evaluates a reporting system for drug intervention studies with high variability in adverse events that utilizes a document-based NoSQL data model and the eCRF nature, allowing for the management of structured and unstructured data. The main objective of the research is to create a flexible, fast, and efficient system for collecting and analyzing data related to drug/vaccine adverse events, especially the COVID-19 vaccine, for stakeholders. This research is of an applied-descriptive type. In this research, first, after studying library resources, the requirements and requirements for the design of the proposed system were determined in the form of the Software requirements specification (SRS) standard. Then, the design and implementation included modeling and creating a prototype of the web-based system. To evaluate usability, the User Experience Questionnaire (UEQ) was used, system security was assessed using the Application Security Verification Standard (ASVS) questionnaire, and a comparative evaluation of the performance between MongoDB and SQLServer was performed. This research was conducted with the aim of designing and evaluating a reporting system for COVID-19 vaccine side effects, based on a document-oriented data model. It includes key components such as the information and side effects collection module, the document management module, and the reporting module. The results indicated that the user experience of the system, in terms of attractiveness, transparency, efficiency, reliability, motivation, and innovation, had an average score of 2.31, placing it within the top 10% of results. Additionally, the evaluations showed that the system employs effective security controls; however, improvements were needed in certain areas such as meeting management and authentication. A comparative assessment of the performance between the document-oriented data model and the relational data model demonstrated that the proposed system was able to provide better performance in response time and management of unstructured data. Evaluations have shown that utilizing case report forms, along with the advantages of a document-oriented data model, can be effective in collecting the minimum necessary data set for interventional studies, particularly those related to drug side effects such as the COVID-19 vaccine. Given the variable nature of the virus and the potential for unknown side effects, this requires flexible and precise approaches. Additionally, the use of the existing system, considering the results of the security and usability assessment, could be effective if access to external systems is improved.In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for eCRF, which has the nature of a form, is the document-oriented model. This paper develops and evaluates a reporting system for drug intervention studies with high variability in adverse events that utilizes a document-based NoSQL data model and the eCRF nature, allowing for the management of structured and unstructured data. The main objective of the research is to create a flexible, fast, and efficient system for collecting and analyzing data related to drug/vaccine adverse events, especially the COVID-19 vaccine, for stakeholders. This research is of an applied-descriptive type. In this research, first, after studying library resources, the requirements and requirements for the design of the proposed system were determined in the form of the Software requirements specification (SRS) standard. Then, the design and implementation included modeling and creating a prototype of the web-based system. To evaluate usability, the User Experience Questionnaire (UEQ) was used, system security was assessed using the Application Security Verification Standard (ASVS) questionnaire, and a comparative evaluation of the performance between MongoDB and SQLServer was performed. This research was conducted with the aim of designing and evaluating a reporting system for COVID-19 vaccine side effects, based on a document-oriented data model. It includes key components such as the information and side effects collection module, the document management module, and the reporting module. The results indicated that the user experience of the system, in terms of attractiveness, transparency, efficiency, reliability, motivation, and innovation, had an average score of 2.31, placing it within the top 10% of results. Additionally, the evaluations showed that the system employs effective security controls; however, improvements were needed in certain areas such as meeting management and authentication. A comparative assessment of the performance between the document-oriented data model and the relational data model demonstrated that the proposed system was able to provide better performance in response time and management of unstructured data. Evaluations have shown that utilizing case report forms, along with the advantages of a document-oriented data model, can be effective in collecting the minimum necessary data set for interventional studies, particularly those related to drug side effects such as the COVID-19 vaccine. Given the variable nature of the virus and the potential for unknown side effects, this requires flexible and precise approaches. Additionally, the use of the existing system, considering the results of the security and usability assessment, could be effective if access to external systems is improved. Abstract In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database, necessitating the use of an unstructured data model, specifically NoSQL. Therefore, the most important and optimal unstructured data model for eCRF, which has the nature of a form, is the document-oriented model. This paper develops and evaluates a reporting system for drug intervention studies with high variability in adverse events that utilizes a document-based NoSQL data model and the eCRF nature, allowing for the management of structured and unstructured data. The main objective of the research is to create a flexible, fast, and efficient system for collecting and analyzing data related to drug/vaccine adverse events, especially the COVID-19 vaccine, for stakeholders. This research is of an applied-descriptive type. In this research, first, after studying library resources, the requirements and requirements for the design of the proposed system were determined in the form of the Software requirements specification (SRS) standard. Then, the design and implementation included modeling and creating a prototype of the web-based system. To evaluate usability, the User Experience Questionnaire (UEQ) was used, system security was assessed using the Application Security Verification Standard (ASVS) questionnaire, and a comparative evaluation of the performance between MongoDB and SQLServer was performed. This research was conducted with the aim of designing and evaluating a reporting system for COVID-19 vaccine side effects, based on a document-oriented data model. It includes key components such as the information and side effects collection module, the document management module, and the reporting module. The results indicated that the user experience of the system, in terms of attractiveness, transparency, efficiency, reliability, motivation, and innovation, had an average score of 2.31, placing it within the top 10% of results. Additionally, the evaluations showed that the system employs effective security controls; however, improvements were needed in certain areas such as meeting management and authentication. A comparative assessment of the performance between the document-oriented data model and the relational data model demonstrated that the proposed system was able to provide better performance in response time and management of unstructured data. Evaluations have shown that utilizing case report forms, along with the advantages of a document-oriented data model, can be effective in collecting the minimum necessary data set for interventional studies, particularly those related to drug side effects such as the COVID-19 vaccine. Given the variable nature of the virus and the potential for unknown side effects, this requires flexible and precise approaches. Additionally, the use of the existing system, considering the results of the security and usability assessment, could be effective if access to external systems is improved. |
| ArticleNumber | 20453 |
| Author | Safaei, Ali Asghar Nasiri Khoshroudi, Seyyed Hamzeh Soleimanjahi, Hoorieh |
| Author_xml | – sequence: 1 givenname: Seyyed Hamzeh surname: Nasiri Khoshroudi fullname: Nasiri Khoshroudi, Seyyed Hamzeh organization: Department of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University – sequence: 2 givenname: Ali Asghar surname: Safaei fullname: Safaei, Ali Asghar email: aa.safaei@modares.ac.ir organization: Department of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University – sequence: 3 givenname: Hoorieh surname: Soleimanjahi fullname: Soleimanjahi, Hoorieh organization: Department of Medical Virology, Faculty of Medical Sciences, Tarbiat Modares University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40594658$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1016/S0140-6736(20)32661-1 10.3233/SHTI210939 10.3390/vaccines9060556 10.3390/vaccines10030366 10.1186/1471-2288-7-23 10.1007/978-3-319-07668-3_37 10.1016/S0140-6736(20)31604-4 10.4103/2229-3485.140555 10.1111/bcp.13285 10.1177/1740774510391916 10.1056/NEJMoa2022483 10.3390/digital4020019 10.1016/j.mimet.2024.106998 10.1197/jamia.M2787 10.3390/ijms22041573 10.1017/S0950268822001418 10.1016/S2589-7500(21)00229-6 10.1093/jamiaopen/ooad068 10.1186/s12911-022-02076-1 10.1016/j.simpa.2024.100699 10.1016/j.diin.2016.03.003 |
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| Snippet | In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a database,... Abstract In case report studies (adverse effects of drugs/vaccines) that are unstructured, a structured relational model is not applicable for designing a... |
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| SubjectTerms | 631/553/117 631/553/2393 631/553/2695 631/553/794 Adverse Drug Reaction Reporting Systems COVID-19 - prevention & control COVID-19 Vaccines - adverse effects Databases, Factual Document-based ECRF (electronic case report Form) Humanities and Social Sciences Humans Information system design multidisciplinary NoSQL data model SARS-CoV-2 Science Science (multidisciplinary) Software Software development Vaccine side effects |
| Title | A NoSQL document based eCRF system for study of vaccines with variable adverse events case study on COVID19 vaccines |
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