Mobile health application for self-care of patients with diabetic retinopathy: Development and validation of the required minimum data set

سال انتشار: 1404
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 85

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شناسه ملی سند علمی:

AIMS02_302

تاریخ نمایه سازی: 29 تیر 1404

چکیده مقاله:

Background and Aims: One of the most common complications of diabetes mellitus is diabetic retinopathy, which is the fifth most common cause of moderate to severe visual impairment in people ۵۰ years of age and older. Mobile health applications enable continuous monitoring, provide patient-centered care, and enhance the participation and independence of patients with diabetic retinopathy. The development of mobile health applications can play an effective role in the management and monitoring of diabetic retinopathy. Still, the development of these applications first requires the identification of the required minimum data set. Therefore, the purpose of this study is to identify and determine the minimum required data set as the first step in designing a self-care mobile application for patients with diabetic retinopathy. Methods: This descriptive-analytical study was conducted in ۲۰۲۵ in two phases including the development and validation of the minimum data set required for the development of a self-care mobile application for patients with diabetic retinopathy. In the first phase, a comprehensive review of the research literature was conducted and electronic databases such as PubMed, Web of Science, Scopus, and Google Scholar were searched until October ۲۰۲۴. Then, data elements were extracted and identified. In the second phase, these elements were validated by ۲۰ experts from the fields of endocrine metabolism, ophthalmology, medical informatics, and health information management using the Delphi technique. Results: ۵۵ MDSs were validated in three administrative, clinical, and functional data areas using two rounds of the Delphi technique. The minimum data set that received more than ۷۵% of expert approval was selected as the final minimum data set. Finally, after two rounds of the Delphi technique, ۱۳ data elements in the administrative section, ۱۹ data elements in the clinical section, and ۱۹ data elements in the functional section were selected as the final minimum data set. Conclusion: In future studies,

نویسندگان

Atefeh Pagheh

Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Hossein Valizadeh Laktrashi

Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

Amir Hossein Daeechini

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran