Alireza Heidari1, Mohammad Arab2, Behzad Damari3. 1. Health Management and Social Development Research Center, Golestan University of Medical Sciences (GOUMS), Golha Alley, Gorgan, Iran. alirezaheidari7@gmail.com. 2. Department of Management and Health Economic, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran. 3. Governance and Health Department, Neuroscience Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Abstract
BACKGROUND: Phenylketonuria (PKU) screening is a public health measure taken to diagnose and treat the patients with PKU to prevent severe neurological disorders in them. The present study was aimed at analyzing the policies of the national PKU screening (NaPS) program in Iran. METHODS: PKU screening program policies were analyzed in compliance with the policy triangle model. Document review and 38 semi-structured interviews were used for data collection. Document review data were analyzed using content analysis, and interview data were analyzed using framework analysis. RESULTS: The national PKU screening (NaPS) program was a decision made at the genetics department of Ministry of Health and Medical Education (MOHME) in Iran. Many internal and external stakeholders were involved in it and valid evidence was used to formulate the policies. Despite some opposition and insufficient support, the program was implemented due to the continuous persistence of parents, interested executives, formulated valid content and a top-down approach. The main barriers included rapid substitution of managers, shortage of Phe-free milk, little awareness of patients' families, social stigma, and inadequate co-operation of some hospital administrators. CONCLUSIONS: The policy triangle framework contributed to explaining the different components of the PKU screening program. A successful PKU screening program requires more stability of senior managers in MOHME, enough human resources and Phe-free milk, educating patients' families, and commitment of hospitals administrators. Meanwhile, all the stakeholders need to be involved in the program effectively.
BACKGROUND:Phenylketonuria (PKU) screening is a public health measure taken to diagnose and treat the patients with PKU to prevent severe neurological disorders in them. The present study was aimed at analyzing the policies of the national PKU screening (NaPS) program in Iran. METHODS:PKU screening program policies were analyzed in compliance with the policy triangle model. Document review and 38 semi-structured interviews were used for data collection. Document review data were analyzed using content analysis, and interview data were analyzed using framework analysis. RESULTS: The national PKU screening (NaPS) program was a decision made at the genetics department of Ministry of Health and Medical Education (MOHME) in Iran. Many internal and external stakeholders were involved in it and valid evidence was used to formulate the policies. Despite some opposition and insufficient support, the program was implemented due to the continuous persistence of parents, interested executives, formulated valid content and a top-down approach. The main barriers included rapid substitution of managers, shortage of Phe-free milk, little awareness of patients' families, social stigma, and inadequate co-operation of some hospital administrators. CONCLUSIONS: The policy triangle framework contributed to explaining the different components of the PKU screening program. A successful PKU screening program requires more stability of senior managers in MOHME, enough human resources and Phe-free milk, educating patients' families, and commitment of hospitals administrators. Meanwhile, all the stakeholders need to be involved in the program effectively.
Authors: Habiba Ben Romdhane; Faten Tlili; Afef Skhiri; Shahaduz Zaman; Peter Phillimore Journal: Int J Public Health Date: 2014-11-16 Impact factor: 3.380
Authors: Taraneh Yousefinezhadi; Ali Mohammad Mosadeghrad; Mohammad Arab; Mozhdeh Ramezani; Ali Akbari Sari Journal: Iran J Public Health Date: 2017-10 Impact factor: 1.429