Health Education and Health Promotion

Framework for Designing a National Model of Depression Information System in Iran

Document Type : Original Article

Authors

S.E. Poorhashemi 1
F. Asadi 1
A.S. Hosseini 1
N. Ramezanghorbani 2
A.H. Daeechini 3

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

2 Department of Development & Coordination Scientific Information and Publications, Deputy of Research & Technology, Ministry of Health & Medical Education, Tehran, Iran

3 Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran

10.58209/hehp.13.4.743
Abstract
Aims: Depression is the most common mental disorder worldwide, affecting a range of age groups, including adolescents and youth. This study aimed to provide a national model for a depression information system in Iranian adolescents and youth.
Materials & Methods: This applied study was conducted in three stages. In the first stage, depression information systems in different countries were examined through a literature review, and Denmark, the United States of America, China, Indonesia, and India were selected as the countries for conducting a comparative study. In the second stage, after reviewing information sources and conducting a comparative study in the selected countries, and considering the geographical and social conditions of Iran, a proposed model for the national depression information system in Iran was presented. In the third stage, the proposed model was validated using expert opinion obtained from specialists in psychiatry, psychology, and health information management, and was finally approved after incorporating their feedback.
Findings: Two parts, the structural components and the key processes of the information system, were identified as the main components of the proposed model for the information system on depression in adolescents and youth in Iran.
Conclusion: By implementing a national information system on depression in adolescents and youth, systematic access to accurate data and statistics related to depression in this population group will be provided. The model in the present study can provide an appropriate information infrastructure for the implementation of a national information system on depression in adolescents and youth in Iran.

Keywords

Adolescent
Youths
Information System
Depression
Registry
Subjects
1- Singkhorn O, Hamtanon P, Moonpanane K, Pitchalard K, Sunsern R, Leaungsomnapa Y, et al. Evaluation of a depression care model for the hill tribes: A family and community-based participatory research. BMC Psychiatry. 2023;23(1):563.
2- Fariborzifar A, Hosseini H. A narrative review of prevalence of depression in patients with chronic medical illnesses in Mazandaran Province, Iran. J Mazandaran Univ Med Sci. 2018;28(162):187-201. [Persian]
3- Stringaris A. Editorial: What is depression?. J Child Psychol Psychiatry. 2017;58(12):1287-9.
4- Ahmed I, Brahmacharimayum A, Ali RH, Khan TA, Ahmad MO. Explainable AI for depression detection and severity classification from activity data: Development and evaluation study of an interpretable framework. JMIR Ment Health. 2025;12.
5- Gitterman AE. Handbook of social work practice with vulnerable populations. New York: Columbia University Press; 1991.
6- Kessing LV, Ziersen SC, Caspi A, Moffitt TE, Andersen PK. Lifetime incidence of treated mental health disorders and psychotropic drug prescriptions and associated socioeconomic functioning. JAMA Psychiatry. 2023;80(10):1000-8.
7- NICE. Depression in adults: Treatment and management. London: National Institute for Health and Care Excellence; 2022.
8- Graham E, Gariépy G, Orpana H. System dynamics models of depression at the population level: A scoping review. Health Res Policy Syst. 2023;21(1):50.
9- Ngata TW, Mvungu EN. Assessment of depressive symptoms severity among secondary school adolescents in Kiambu County, Kenya. J Sociol Psychol Relig Stud. 2023;3(3):13-21.
10- Loades ME, St Clair MC, Orchard F, Goodyer I, Reynolds S, Consortium I. Depression symptom clusters in adolescents: A latent class analysis in a clinical sample. Psychother Res. 2022;32(7):860-73.
11- Araya R, Zitko P, Markkula N, Rai D, Jones K. Determinants of access to health care for depression in 49 countries: A multilevel analysis. J Affect Disord. 2018;234:80-8.
12- Costantini L, Costanza A, Odone A, Aguglia A, Escelsior A, Serafini G, et al. A breakthrough in research on depression screening: From validation to efficacy studies. ACTA BIOMEDICA: ATENEI PARMENSIS. 2021;92(3):e2021215.
13- Razzak HA, Harbi A, Ahli S. Depression: Prevalence and associated risk factors in the United Arab Emirates. Oman Med J. 2019;34(4):274-82.
14- Geurgas R, Newman SJ, Akimova ET, Thompson KN, Wedow R. What machine learning teaches us about depression prediction across the life course: An exploratory comparison of predictive models. SSM Popul Health. 2025;32:101886.
15- Chen P. Understanding and addressing youth depression: Risk factors, resources, and promoting mental health and well-being. Psychology. 2023;14(8):1189-202.
16- Grossberg A, Rice T. Depression and suicidal behavior in adolescents. Med Clin North Am. 2023;107(1):169-82.
17- Carvalho JV, Rocha Á, Vasconcelos J, Abreu A. A health data analytics maturity model for hospitals information systems. Int J Inf Manag. 2019;46:278-85.
18- Damanabi S, Farahbakhsh M, Khalili Z. Presenting a model for mental health system within primary healthcare. Indo Am J Pharm Sci. 2017;4(9):2783-8.
19- Asadi F, Daeechini AH, Ramezanghorbani N. Developing a model for the national pediatric cancer registry. Iran J Pediatr Hematol Oncol. 2025;15(4):621-36.
20- Endriyas M, Alano A, Mekonnen E, Ayele S, Kelaye T, Shiferaw M, et al. Understanding performance data: Health management information system data accuracy in Southern Nations Nationalities and People's Region, Ethiopia. BMC Health Serv Res. 2019;19(1):175.
21- Kilbourne AM, McGinnis GF, Belnap BH, Klinkman M, Thomas M. The role of clinical information technology in depression care management. Adm Policy Ment Health. 2006;33(1):54-64.
22- Krzystanek M, Romańczyk M, Surma S, Koźmin-Burzyńska A. Whole body cryotherapy and hyperbaric oxygen treatment: new biological treatment of depression? A systematic review. Pharmaceuticals. 2021;14(6):595.
23- Bhati DK. Impact of technology on primary healthcare information management: A case of north India. Perspect Health Inf Manag. 2015;(1):1-9.
24- Joseph A. Information systems in healthcare: Improving patient care and efficiency. Bus Stud J. 2023;15(S3):1-3.
25- Yang M, Loeb DF, Sprowell AJ, Trinkley KE. Design and implementation of a depression registry for primary care. Am J Med Qual. 2019;34(1):59-66.
26- Bagherian H, Farahbakhsh M, Rabiei R, Moghaddasi H, Asadi F. National communicable disease surveillance system: A review on information and organizational structures in developed countries. Acta Inform Med. 2017;25(4):271-6.
27- Gliklich RE, Dreyer NA, Leavy MB. Registries for evaluating patient outcomes: A user's guide. Rockville: Agency for Healthcare Research and Quality (US); 2014.
28- Sabahi A, Asadi F, Shadnia S, Rabiei R, Hosseini A. Data infrastructure for a poisoning registry with designing data elements and a minimum data set. Shiraz E Med J. 2022;23(5):e116103.
29- Liu C, Talaei-Khoei A, Storey VC, Peng G. A review of the state of the art of data quality in healthcare. J Glob Inf Manag. 2023;31(1):1-18.
30- Rampisheh Z, Kameli ME, Zarei J, Barzaki AV, Meraji M, Mohammadi A. Developing a national minimum data set for hospital information systems in the Islamic Republic of Iran. East Mediterr Health J. 2020;26(4):400-9.
31- Asadi F, Ramezanghorbani N, Almasi S. Designing a national eye injury registry model for Iran. Med Sci. 2021;25(109):569-76.
32- Talebi B, Seyednazari N. Challenges of information systems in healthcare organizations. Health Manag Inf Sci. 2020;7(4):187-95.
Health Education and Health Promotion
Volume 13, Issue 4
Autumn 2025
Pages 743-750