RESUMEN
Retinopathy of prematurity (ROP) is a largely avoidable cause of blindness in children worldwide, requiring high-quality neonatal care, early detection and treatment. In middle-income countries throughout Latin America, Eastern Europe and South Asia, there has been a rise in ROP blindness due to a combination of increased survival of preterm infants, resource-scarce medical environments and lack of policies, training and human resources. However, Argentina is an example of country where rates of ROP blindness have declined and ROP programmes have been successfully and effectively embedded within the health and legal system. The purpose of this study is to describe the activities and stakeholders, including Ministry of Health (MoH) and UNICEF, involved in the process, from recognition of an epidemic of ROP blindness to the development of national guidelines, policies and legislation for control. Using a retrospective mixed methods case study design, data on rates of severe ROP was collected from 13 neonatal intensive care units from 1999 to 2012, and on the proportion of children blind from ROP in nine blind schools in seven provinces. Legislative document review, focus group discussions and key informant interviews were conducted with neonatologists, ophthalmologists, neonatal nurses, parents, MoH officials, clinical societies, legislators and UNICEF officials in seven provinces. Results are presented combining the stages heuristic policy framework and Shiffman including: agenda setting, policy formulation, implementation and evaluation. By 2012, ROP had declined as a cause of blindness in children in schools for the blind as had rates of severe ROP needing treatment in the NICUs visited. Multiple factors played a role in reducing blindness from ROP in Argentina and successfully coordinating its control including national advocacy, leadership, legislation and international collaboration. Lessons learned in Argentina can potentially be scaled to other LMICs in Latin America and beyond with further context-specific research.
Asunto(s)
Ceguera/prevención & control , Defensa del Niño , Conducta Cooperativa , Implementación de Plan de Salud , Política de Salud , Retinopatía de la Prematuridad/epidemiología , Argentina/epidemiología , Grupos Focales , Humanos , Lactante , Recién Nacido , Estudios RetrospectivosRESUMEN
PURPOSE: To develop and implement mechanisms to collect, report, and assess the World Health Organization (WHO) core eye health indicators in Chile, Honduras, Mexico, Peru, and Uruguay. METHODS: Simple templates for a situational analysis (of data collection and reporting processes), a national data collection strategy, and a national work plan to implement the core eye health indicators were developed. Public and private sector representatives from the ministries of health (MOHs), national vision committees, and national societies of ophthalmology of each country used these tools with 2013 baseline data to improve their data collection processes and collected 2015 data. Final analysis and cross-validation were performed using intraocular lens sales data and last observation carried forward imputation. RESULTS: Study tools were effectively implemented in all five countries and resulted in improved intersectoral stakeholder collaboration and communications, which improved the data collection and reporting processes. More complete and accurate data were reported by 2015 compared to the 2013 baseline. CONCLUSIONS: Multisectoral stakeholders, including national professional societies and national vision committees, should collaborate with MOHs to improve the quality of data that are reported to WHO. This study involved these stakeholders in the data collection processes to better understand the realities of indicator implementation, better manage their expectations, and improve data quality. WHO Member States across the globe can feasibly adapt the study tools and methodologies to strengthen their data collection processes. Overall, the reliability and validity of the indicators is hampered with limitations that prevent fully accurate data from being collected.