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Minimum Data Set of Personal Health Record (PHR) for Patients with Chronic Respiratory Diseases
- Source :
- Frontiers in Health Informatics, Vol 11, Iss 1 (2022)
- Publication Year :
- 2022
- Publisher :
- Hamara Afzar, 2022.
-
Abstract
- Introduction: Chronic respiratory diseases are one of the four main groups of non-communicable diseases. People with these diseases need access to data to manage their disease and care plan. Personal health record (PHR) as a powerful health information technology tool can empower chronic patients to better manage their health status and become an active member of health care teams. This study is to determine the minimum data set (MDS) in personal health record for patients with chronic respiratory diseases. Materials and Method: This present applied research was done descriptively by Delphi method. First, the data sets of chronic respiratory diseases were extracted using a literature review. Then, using a researcher-made questionnaire and based on Delphi technique in two phases, it was evaluated by 5 pulmonologists. Results: The PHR data set for chronic respiratory diseases was classified into six categories, including physical examination and clinical observation, laboratory data, medications, specialized treatments, diagnostic procedures and vaccination. The 33 data element were identified as the main data elements with an agreement of more than 80% in the first phase of Delphi technique. Also, in the second phase, the four data elements proposed by the experts in the first phase were agreed upon above 80%. Conclusion: Given the role of PHR data in tracking the progress of chronic diseases, treating, and teamwork by physicians and other care providers, determining the minimum data set will be an effective step toward integrating and improving information management in these patients.
Details
- Language :
- English
- ISSN :
- 26767104
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Health Informatics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1689c52618744158b56542cc059bce24
- Document Type :
- article
- Full Text :
- https://doi.org/10.30699/fhi.v11i1.369