EZ-Entry: A clinical data management system

Gao, Qing-Bin; Yu, Ke; Fu, Zheng; Lu, Jian Mei; Wu, Cheng; Jin, Zhichao; He, Jia

doi:10.1016/j.compbiomed.2008.07.008

Cited by 12 publications

(5 citation statements)

References 2 publications

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“…OpenClinica and REDCap have also considered similar rules [24][25][26]. While other systems, such as Ez-Entry, ObTiMA, and OnWARD, defined equal validation rules for all fields, our system has different validation rules for each field that we defined in the CRF [27][28][29].…”

Section: Discussionmentioning

confidence: 99%

The Development of a Clinical Registry Digital Database on Invasive Fungal Infections in India: Advancing Epidemiological Understanding and Patient Care

Kaur,

Singh,

Sharma

et al. 2024

JoF

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A well-structured digital database is essential for any national priority project as it can provide real-time data analysis and facilitate quick decision making. In recent times, particularly after the COVID-19 pandemic, invasive fungal infections (IFIs) have emerged as a significant public health challenge in India, affecting vulnerable population, including immunocompromised individuals. The lack of comprehensive and well-structured data on IFIs has hindered efforts to understand their true burden and optimize patient care. To address this critical knowledge gap, the ICMR has undertaken a Pan-India pioneer initiative to develop a network of Advanced Mycology Diagnostic research centres in different geographical zones of the country (ICMR-MycoNet). Under the aegis of this project, a clinical registry on IFIs in the ICUs is initiated. This process paper presents a detailed account of the steps involved in the establishment of a web-based data entering and monitoring platform to capture data electronically, ensuring robust and secure data collection and management. This system not only allows participating ICMR-MycoNet centres to enter patient information directly into the database using standardized Case Report Form (CRF) but also includes data validation checks to ensure the accuracy and completeness of entered data. It is complemented by a real-time, web-based, and adaptable data visualization platform. This registry aims to provide crucial epidemiological insights, promote evidence-based hospital infection control programs, and ultimately improve patient outcomes in the face of this formidable healthcare challenge.

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Section: Discussionmentioning

confidence: 99%

The Development of a Clinical Registry Digital Database on Invasive Fungal Infections in India: Advancing Epidemiological Understanding and Patient Care

Kaur,

Singh,

Sharma

et al. 2024

JoF

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“…These systems support various aspects of data management, reduce financial and manpower costs, and facilitate data collection and management by eliminating manual processes and reducing workload [32,35,36]. However, many systems have not been properly evaluated in terms of quality, usability, and impact [21,[37][38][39][40][41][42]. Therefore, conducting evaluation studies is of paramount importance [16].…”

Section: Discussionmentioning

confidence: 99%

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

Nourani

Ayatollahi²,

Solaymani‐Dodaran³

2023

BMC Med Inform Decis Mak

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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.

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“…Similar rules have also been considered in other systems such as OpenClinica and REDCap [ 39 , 56 ]. However, this function was not considered in the other systems such as Ez-Entry, ObTiMA, and OnWARD, and the rules were defined equally for all fields [ 34 , 41 , 42 ]. Some benefits of defining validation rules are reducing data entry time and increasing the accuracy of the entered data [ 57 ].…”

Section: Discussionmentioning

confidence: 99%

A Clinical Data Management System for Diabetes Clinical Trials

Nourani

Ayatollahi

Solaymani‐Dodaran

2022

Journal of Healthcare Engineering

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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.

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EZ-Entry: A clinical data management system

Cited by 12 publications

References 2 publications

The Development of a Clinical Registry Digital Database on Invasive Fungal Infections in India: Advancing Epidemiological Understanding and Patient Care

The Development of a Clinical Registry Digital Database on Invasive Fungal Infections in India: Advancing Epidemiological Understanding and Patient Care

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

A Clinical Data Management System for Diabetes Clinical Trials

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