Optimization of a Decision Support System for Monitoring Growth and Development Using the Z-Score Method at Cempaka Health Post
Keywords:
Assessment, Cempaka Posyandu, Growth and Development, Optimation, Toddlers, Z-ScoreAbstract
Monitoring the growth and development of children during their first 1,000 days is crucial due to the rapid growth that occurs during this period.This study focuses on optimizing a Decision Support System (DSS) designed for monitoring the growth and development of children at the Cempaka Health Post using the Z-Score method. The system aims to provide a comprehensive and accurate assessment of children's health status by analyzing key growth parameters such as height, weight, and age. The Z-Score method allows for standardized comparisons against international growth standards, facilitating early detection of growth abnormalities. The research involved 63 toddler data entries at the Cempaka Posyandu, integrating these data into Z-Score calculations, monthly nutritional status assessments, and recommendations for parents. The results indicated that the Cempaka Posyandu had 73% of children with normal nutrition, 69.8% with normal height, and 47.6% with normal weight. This was due to the majority of Z-Score values remaining within the normal range of two elementary school. From these results, it was found that approximately 63.5% of toddlers maintained normal status over a period of 3 months. By implementing advanced data processing techniques and user-friendly interfaces, the optimized DSS enhances the efficiency and reliability of health monitoring, ensuring timely and appropriate interventions. This research underscores the significance of technological advancements in improving healthcare outcomes at community health centers.
References
Ali, S., Jan, M., & Khan, S. (2019). Role of Decision Support Systems in Health Care Sector. Pakistan Journal of Medical Sciences, 35(3), 799-804. https://doi.org/10.12669/pjms.35.3.44
Ashraf, H., & Ahmad, W. (2020). The Impact of Technological Innovation in Improving Child Health Monitoring. Journal of Child Health Care, 24(3), 303-312. https://doi.org/10.1177/1367493519867253
Biswas, T., Townsend, N., Magalhaes, R. J. S., & Islam, M. S. (2020). Nutrition Transition and Non-Communicable Disease in Bangladesh: A Mixed Method Approach Exploring Burden, Risk Factors, and Social Determinants. Public Health Nutrition, 23(1), 85-94. https://doi.org/10.1017/S136898001900256X
Campbell, H., Duke, T., Weber, M. W., English, M., Carai, S., & Tamburlini, G. (2008). Global Initiatives for Improving Hospital Care for Children: State of the Art and Future Prospects. Pediatrics, 121(4), e984-e992. https://doi.org/10.1542/peds.2007-1395
De Onis, M., & Branca, F. (2016). Childhood Stunting: A Global Perspective. Maternal & Child Nutrition, 12, 12-26. https://doi.org/10.1111/mcn.12231
Dewey, K. G., & Begum, K. (2011). Long-Term Consequences of Stunting in Early Life. Maternal & Child Nutrition, 7, 5-18. https://doi.org/10.1111/j.1740-8709.2011.00349.x
Haidar, J., & Haile Mariam, D. (2015). Malnutrition: A Significant Problem in Developing Countries. Ethiopian Journal of Health Development, 26(3), 143-147. https://doi.org/10.4314/ejhd.v26i3.2
Hassan, M., Mahmud, M., & Islam, A. (2017). An Overview of Decision Support Systems for Child Growth Monitoring. Journal of Biomedical Informatics, 68, 49-62. https://doi.org/10.1016/j.jbi.2017.02.012
Kementerian Kesehatan Republik Indonesia. (2018). Panduan Pelaksanaan Posyandu untuk Kesehatan Anak dan Gizi di Indonesia. Buletin Penelitian Sistem Kesehatan, 21(4), 241-250.
Li, Z., Kim, R., Vollmer, S., & Subramanian, S. V. (2020). Factors Associated with Child Stunting, Wasting, and Underweight in 35 Low- and Middle-Income Countries. JAMA Network Open, 3(4), e203386. https://doi.org/10.1001/jamanetworkopen.2020.3386
Lu, C., Black, M. M., & Richter, L. M. (2016). Risk of Poor Development in Young Children in Low-Income and Middle-Income Countries: An Estimation and Analysis at the Global, Regional, and Country Level. The Lancet Global Health, 4(12), e916-e922. https://doi.org/10.1016/S2214-109X(16)30266-2
Mwangome, M. K., Fegan, G., Fulford, T., Prentice, A. M., & Berkley, J. A. (2012). Mid-Upper Arm Circumference at Age of Routine Infant Vaccinations to Identify Infants at Risk of Malnutrition. Pediatrics, 130(4), e964-e971. https://doi.org/10.1542/peds.2012-1091
Onyango, A. W., De Onis, M., & Caroli, M. (2013). Anthropometric Standards for the Assessment of Growth and Nutritional Status of School-Age Children and Adolescents. Nutrition Reviews, 61(6), 68-74. https://doi.org/10.1301/nr.2003.jun.S68-S74
Rodríguez-Martínez, H., Zhou, B., Sophiea, M. K., Bentham, J., Paciorek, C. J., & Gutiérrez-Aguilar, R. (2020). Height and Body-Mass Index Trajectories of School-Aged Children and Adolescents from 200 Countries from 1985 to 2019: A Pooled Analysis of 2181 Population-Based Studies with 65 Million Participants. The Lancet, 396(10261), 1511-1524. https://doi.org/10.1016/S0140-6736(20)31859-6
Victora, C. G., Christian, P., Vidaletti, L. P., Gatica-Domínguez, G., Menon, P., & Black, R. E. (2021). Revisiting Maternal and Child Undernutrition in Low-Income and Middle-Income Countries: Variable Progress towards an Unfinished Agenda. The Lancet, 397(10282), 1388-1399. https://doi.org/10.1016/S0140-6736(21)00394-9
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Naomi Tiomas Simorangkir (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
