Optimizing Surveillance for Early Detection of High-Risk Pregnancy, Neonatal, and Child Risks with Tinamila.com Application
Abstract
Introduction: In 2021, Indonesia recorded 2,982 maternal deaths related to Covid-19, highlighting a pressing health issue. The high maternal mortality rate underscores the need for innovation in the early detection of health risks for pregnant women and children. This study aims to evaluate the effectiveness of the tinamila.com application in the early detection of high-risk pregnant women, neonates, and high-risk children at the Mandala Community Health Center in 2023.
Methods: This study combines both quantitative and qualitative data. Quantitative data is collected through a cross-sectional approach using chi-square tests and secondary data from weekly reports submitted by Community Health Workers (Kader), while qualitative data is gathered through in-depth interviews and Focus Group Discussions (FGD) with healthcare professionals and Kader. The research population consists of ten respondents from the healthcare sector, including the Head of the Community Health Center, Puskesmas Administrative Staff, Surveillance Personnel, the Coordinator Midwife, and six Village Midwives, with 96 Kader selected as the sample. Data were analyzed using the Chi-Square test.
Results: Findings reveal cadre characteristics, with 76% demonstrating good to very good knowledge and 90.6% using the application. Bivariate analysis indicates a significant correlation between knowledge and application effectiveness (p-value = 0.000, OR value = 10.5) and between training and application effectiveness (p-value = 0.001, OR value = 12.5).
Conclusion:The study concludes that the tinamila.com application is effective in early detection, recommending its continued use for reporting morbidity and mortality rates. Suggestions include processing and analyzing reported data, providing feedback and rewards to cadres, and ensuring ongoing support for sustained application use.
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