Stunting remains one of the major public health issues at the national level in Indonesia. As an archipelagic country, Indonesia faces unique challenges in tackling stunting, particularly in regions with limited access to healthcare services. Advances in information technology offer new opportunities to support stunting prevention efforts, including through the utilization of health data. Such data can be used to detect stunting risks early and to monitor children's nutritional status more effectively. The use of health data applications or systems by Posyandu cadres is influenced by various factors, including availability of time, cost, level of trust, and perceptions of ease of use and usefulness. This study aims to identify the determinants of health data utilization by Posyandu cadres for toddlers as a stunting prevention effort in Geneng Subdistrict, Ngawi Regency. This research is an analytical quantitative study with a cross-sectional approach. A sample of 80 Posyandu cadres for toddlers in Geneng Subdistrict was selected using purposive sampling. Data were collected through questionnaires and analyzed using univariate, bivariate, and multivariate logistic regression tests to identify the factors influencing the use of health data in stunting prevention. The results show that the significant determinants include the age of the Posyandu cadre, their education level, and the amount of time they dedicate to Posyandu activities. The determinants of age, education level, and time significantly influence the utilization of health data and thereby affect the optimization of stunting prevention. Strengthening cadre capacity in these aspects is necessary to support more effective stunting prevention.

Indonesia's healthcare system continues to face significant challenges in delivering equitable services across diverse and remote regions. The digital transformation of healthcare—through the integration of Artificial Intelligence (AI), big data, and telemedicine—offers promising solutions to overcome disparities in access, infrastructure, and service delivery. This study aims to comprehensively analyze global and national research trends related to the digital transformation of healthcare using a Systematic Literature Review (SLR) approach, supported by bibliometric analysis through the VOSviewer software. Following the PRISMA protocol, a total of 30 relevant articles published between 2020 and 2025 were identified and analyzed. The network and overlay visualizations generated reveal four major thematic clusters: digital transformation and service quality, big data and pandemic response, AI and data privacy, and community engagement in digital health services. Overlay visualization also shows a clear shift in research focus—from early pandemic responses toward system optimization, ethical governance, and technological inclusivity in recent years. The study concludes that the integration of AI, big data, and telemedicine not only enhances healthcare efficiency but also requires strong regulatory frameworks, infrastructure readiness, and public engagement. Future research should incorporate co-citation and cross-country comparative analyses to enrich the understanding of digital health transformation in a global context.

The inaccuracy of the disease diagnosis code is one of the problem affecting the quality of health services. Based on the preliminary result, 89 outpatient diagnosis codes in a medical record found 30 inaccuracies data from SIMPUS result of general poly at Purwoharjo Health Center. The impact of this inaccuracy has been influenced by the accuracy of disease data that resulted from making report data. The purpose of this study was to analyze the inaccuracy of disease diagnosis codes for outpatient medical records with SIMPUS at Purwoharjo Public Health Center. It was a descriptive study with observation, interviews, and documentation data collection. The object of this study was 95 outpatient medical records with simple random sampling. The result of this research was found 42% inaccuracy code of outpatient medical records with SIMPUS. The cause of these problems was the coder less careful in enforcing the disease diagnosis code because of the high workload of the coder and there’s no job description in SOP, so the advice that can be given to Purwoharo Health Center is to hold a division of tasks evenly and can be written in the SOP job description.

Stunting indicates a high prevalence of nutritional deficiencies that have not yet reached reduction targets, as seen in Geneng District, Ngawi Regency. Maternal knowledge and attitudes are crucial factors in preventing stunting and can influence mothers' behaviors in ensuring nutrition for toddlers. Manajemen Nutrisi Balita Stunting (MNBS) is an innovative intervention designed to address specific nutritional needs. It was developed into a smartphone application that serves as an educational tool to prevent stunting issues. This study aims to analyze the impact of MNBS on maternal knowledge and attitudes towards stunting prevention. This study used a one-group pretest-post-test design approach. Sampling was conducted using simple random sampling involving 30 respondents. Inclusion criteria for this research included mothers with toddlers experiencing malnutrition, owning a smartphone, and being willing to participate in the study until completion. The research results indicate that maternal knowledge and attitudes towards preventing stunting improved after receiving education through Manajemen Nutrisi Balita Stunting (MNBS) smartphone application. Manajemen Nutrisi Balita Stunting (MNBS) Smartphone Application has an impact as an educational medium on maternal knowledge and attitudes toward preventing stunting.