of Health Information Management & Medical Informatics, Department of Health Information Management and Technology, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Abstract: (46 Views)
Background: Effective performance of artificial intelligence, particularly in the field of machine learning, requires the availability of high-quality databases. Considering the current state of the country’s health system, which indicates weaknesses in databases within healthcare organizations and clinical research centers, and based on the premise that strengthening databases is essential for the effective utilization of machine learning, this study aimed to present a model for strengthening healthcare databases. Methods: This applied qualitative study was conducted using two questionnaires. The first questionnaire was administered to 10 experts in Health Information Management (faculty members of medical universities), and the second to 10 experts in Informatics (faculty members from medical and non-medical universities). Data were analyzed using descriptive statistics, including cumulative frequency and mean scores. Results: Overall, two models were developed in this study: one model for strengthening data in healthcare centers across the country, consisting of two sub-models, and another model for strengthening data in clinical research centers. The validity of both models was confirmed by experts. Conclusion: The Ministry of Health and Medical Education should establish and implement regulations and standards for electronic health records, data quality, and interoperability to facilitate external data strengthening mechanisms. Furthermore, revising hospital accreditation checklists in the field of information management and issuing guidelines to clinical research centers to improve data quality can institutionalize internal data strengthening mechanisms.