A Model for the National Mental Health Information Network

Reza Rabiei; Farkhonde Aasdi; Hamid  Moghaddasi; Mahdie  Shojaei Baghini

doi:10.18502/ahit.v2i1.6166

Reza Rabiei Ph.D. in Medical Informatics, Department of Information Management and Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farkhonde Aasdi Ph.D. in Health Information Management, Department of Information Management and Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Hamid Moghaddasi Ph.D. in Medical Informatics, Department of Information Management and Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mahdie Shojaei Baghini Ph.D. in Health information management, Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

DOI: https://doi.org/10.18502/ahit.v2i1.6166

Abstract

Aim: Accurate information can be accessed in a timely manner through the Integrated Mental Health Information Network (MHIN). As Iran has no MHIN, this study was undertaken to propose an architectural model.

Method: This research is a sequential mixed method. The organizational structure and database structure of the MHIN was identified, and the architectural model of the NMHIN was presented in two main phases. In the first phase, a quantitative study was conducted in a scoping review with an extensive review of the background, documents, information, and available resources about the mental health information network. In the second phase, to validate the proposed architecture, the Delphi technique was implemented. Questionnaires were distributed and collected both in person and by e-mail, and finally, the data were analyzed using SPSS-19.

Results: The model of national MHIN was provided in five dimensions: MH entities, organizational ownership of databases, data elements of each database, linkage among databases, and exchangeable data elements among the databases.

Conclusion: This model can be applied as a suitable platform to effectively and efficiently store and use mental health information. So, the available information can be used for providing mental health services more comfortably and appropriately. The results showed that connecting mental health entities can create a flow of information, coordinate MHIN activities, and improve performance, efficiency, and quality of mental health.