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Showing 4 results for Data Elements
A Comparative Study Of The Athlete Health Records’ Minimum Data Set In Selected Countries And Presenting A Model For Iran
Reza Safdari, Hossein Dargahi, Farzin Halabchi, Kamran Shadanfar, Robab Abdolkhani,
Volume 8, Issue 2 (7-2014)
Abstract

 Background and Aim: The quality of health record depends on the quality of its content and proper documentation. Minimum data set makes a standard method for collecting key data elements that make them easy to understand and enable comparison. The aim of this study was to determine the minimum data set for Iranian athletes’ health records.

 Materials and Methods: This study is an applied research of a descriptive - comparative type which was carried out in 2013. By using internal and external forms of documentation, a checklist was created that included data elements of athletes health record and was subjected to debate in Delphi method by experts in the field of sports medicine and health information management.

 Results: From 97 elements which were subjected to discussion, 85 elements by more than 75 percent of the participants (as the main elements) and 12 elements by 50 to 75 percent of the participants (as the proposed elements) were agreed upon. In about 97 elements of the case, there was no significant difference between responses of alumni groups of sport pathology and sports medicine specialists with medical record, medical informatics and information management professionals.

 Conclusion: Minimum data set of Iranian athletes’ health record with four information categories including demographic information, health history, assessment and treatment plan was presented. The proposed model is available for manual and electronic medical records.

 


Determining the Minimum Data Set for Uveitis Patients’ Electronic Health Records in Iran 
Minoo Shahbazi, Reza Safdari, Mohammad Zarei,
Volume 12, Issue 2 (7-2018)
Abstract
Background and Aim: The quality of Electronic Health Records (EHRs) depends on the quality of its content and proper documentation. Determining the Minimum Data Set (MDS) to enhance the quality of electronic health records’ content and helping to improve the quality of health care provision to uveitis patients are essential matters. The aim of this study is to determine the essential MDS for uveitis patients’ electronic health records.
Materials and Methods: In this descriptive-analytical study, data collection tools for collecting the Minimum Data Set were library resources and internet-based database. The MDS was obtained through Likert scale questionnaire and was surveyed by 22 ophthalmologists and retina subspecialists.
Results: Among the elements of the survey, all cases with over 90% approval were considered as main elements. Regarding the importance of presented data elements, no significant difference was found between the responses of ophthalmologists who participated in this study. 
Conclusion: The Minimum Data Set of uveitis patients’ electronic health records can be represented by five groups of demographic information: patients’ clinical records, laboratory information, type of uveitis, treatment guidelines, and the information of ophthalmic pictures. A suggested model for manual systems and electronic medical records is available. 

Determining Data Elements to Develop a Self-Care Application for Biliary Patients
Reza Safdari, Seyyed Farshad Allameh, Ms Fariba Shabani,
Volume 15, Issue 6 (3-2022)
Abstract
Background and Aim: Many risk factors can cause biliary system diseases. Hence, this category of diseases is amongst the most common ones. Active patient cooperation is very important in disease management, self-care, and clinical outcomes improvement. A mobile phone application has a high potential in supporting the patients’ self-management. Therefore, this study was conducted to recognize and define data elements to develop a self-care application for biliary patients.
Materials and Methods: The current descriptive study was conducted in 2 stages, resource investigation, and data elements’ need assessment. In the first stage, scientific articles available in databases were used for defining required data elements to develop the application for biliary patients, and a checklist of data elements was prepared. In the second stage, a questionnaire was made based on the checklist. Content and face validity were accepted by the research team and the reliability was calculated 87.2%, using the Cronbach’s alpha test. The mentioned questionnaire was given to Gastroenterologists at Imam Khomeini Hospital complex, and the elected data elements were recognized.
Results: In this application, data elements were categorized into seven sections, including demographic and clinical information, data related to the biliary system diseases, postoperative lifestyle information of the biliary patients, reminders, disease management, and informing. Sixty point five percent of the responders gave the highest importance to data elements in the demographic and clinical data section. Data elements related to patients’ education were considered highly important by 54.2% of the responders. Forty three point eight percent gave the highest importance to data elements in interventional applications’ sections, and only 4.2% gave the least importance to this section.
Conclusion: Based on the identified data elements, a self-care application was designed and developed and can be used as a supplement to specialized care for biliary patients.


Data Elements for Screening Major Depression in Ages 10 To 25 Using a Clinical Decision Support System
Leila Shahmoradi, Niloofar Kheradbin, Ahmad Reza Farzanehnejad, Niloofar Mohammadzadeh, Atefeh Ghanbari Jolfaei,
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Identifying risk factors is recommended as the first step for depression management in children and adolescents. This study aims to determine the data elements required for developing a clinical decision support system for screening major depression in young people.
Materials and Methods: This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool. 
Results:  According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial
Conclusion: Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.

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