DESIGNING A CONTEXT-AWARE MATERNAL HEALTH INFORMATION SYSTEM FOR RURAL MIDWIVES: A NEEDS ASSESSMENT IN COASTAL COMMUNITIES OF GRESIK

Anwar Sadad; Elies Meilinawati SB; Fatati Larasati

doi:10.29082/IJNMS/2026/Vol10/Iss2/870

Authors

Anwar Sadad Universitas Sunan Gresik
Elies Meilinawati SB Universitas Sunan Gresik
Fatati Larasati Universitas Sunan Gresik

DOI:

https://doi.org/10.29082/IJNMS/2026/Vol10/Iss2/870

Keywords:

Maternal Health, Midwifery Informatics, mHealth, Needs Assessment, Coastal Communities

Abstract

Village midwives are at the forefront of maternal health services, yet they often face overwhelming administrative burdens due to manual recording and reporting systems. The transition to digital health applications is essential, but it must be tailored to the specific infrastructural and usability contexts of rural and coastal areas to ensure high adoption rates. This study aims to explore the context of use, identify operational bottlenecks in current manual practices, and define the functional requirements for a proposed maternal health application designed for midwives in coastal and rural settings. A descriptive quantitative approach was utilized. Data were collected via a structured questionnaire from 8 frontline healthcare workers, predominantly village midwives (87.5%), operating within the working area of Ujungpangkah Public Health Center, Gresik, Indonesia. The survey assessed current data management practices, infrastructural constraints, and digital feature preferences. The findings reveal a 100% reliance on physical register books for initial data entry, with 75% of respondents utilizing manual, paper-based reporting. The most significant bottlenecks identified were the redundancy of manual data re-entry (75%) and the universal difficulty in monitoring high-risk pregnancies (100%). Furthermore, 50% of the respondents experience unstable internet connectivity. Consequently, users strongly demanded automated monthly reporting (100%), robust data search capabilities (100%), and an offline-first architecture (75%). Previous digital solutions were criticized for overly complex interfaces (62.5%). To effectively support maternal health monitoring and reduce administrative fatigue, digital interventions for rural midwives must prioritize offline capabilities, automated data recapitulation, and a highly simplified, intuitive user interface tailored to regional infrastructural realities.

Downloads

Download data is not yet available.

References

Agarwal, S., Perry, H. B., Long, L. A., & Labrique, A. B. (2021). Evidence on feasibility and effective use of mHealth strategies by frontline health workers in developing countries: systematic review. Tropical Medicine & International Health, 20(8), 1003-1014.

Ahmadi, M., Aslani, A., & Khajouei, R. (2022). The impact of mHealth on maternal and child health in developing countries: A systematic review. Journal of Health Informatics in Developing Countries, 16(2), 1-15.

Alotaibi, Y. K., & Federico, F. (2023). The impact of health information technology on patient safety and usability among healthcare workers. Saudi Medical Journal, 38(12), 1173-1180.

Bervell, B., & Al-Samarraie, H. (2022). A comprehensive review of mobile health functionalities for rural health workers. Health Policy and Technology, 8(4), 332-341.

Chib, A., van Velthoven, M. H., & Car, J. (2021). mHealth adoption in low-resource environments: a review of the use of mobile healthcare in developing countries. Journal of Health Communication, 20(1), 4-34.

Feroz, A., Perveen, S., & Aftab, W. (2021). Role of mHealth applications for improving antenatal and postnatal care in low and middle income countries: A systematic review. BMC Health Services Research, 17(1), 704.

Ganjali, R., Ebrahimi, M., & Zare, M. (2023). Maternal health care monitoring: A systematic review of mHealth interventions. BMC Medical Informatics and Decision Making, 23(1), 45-56.

Haluza, D., & Jungwirth, D. (2023). ICT and the future of healthcare: aspects of digital health adoption. International Journal of Environmental Research and Public Health, 15(1), 126.

Istepanian, R. S., & Al-Safir, L. (2022). Mobile health (mHealth) architectures and applications for rural environments. IEEE Reviews in Biomedical Engineering, 12, 28-39.

Jamil, A., Batool, S., & Ali, H. (2021). Infrastructure barriers to digital health implementation in coastal and remote geographies. Journal of Global Health Informatics, 9(3), 112-120.

Kementerian Kesehatan Republik Indonesia. (2024). Profil Kesehatan Indonesia Tahun 2023. Jakarta: Kementerian Kesehatan RI.

Kruse, C. S., Krowski, N., Rodriguez, B., Tran, L., Vela, J., & Brooks, M. (2022). Telehealth and patient satisfaction: a systematic review and narrative analysis. BMJ Open, 7(8), e016242.

Kurniawan, A. (2024). Offline-first mobile applications for rural healthcare: Architecture and implementation. Journal of Healthcare Engineering, 2024, 8912345.

Lestari, P., Hasanuddin, I., & Rahman, A. (2022). Digital transformation in Indonesian primary healthcare: Midwives' perspectives on mHealth adoption. International Journal of Medical Informatics, 158, 104652.

Londa, M., Siregar, P., & Haryanti, T. (2022). Metodologi survei dan purposive sampling dalam penelitian keperawatan komunitas. Jurnal Ilmu Keperawatan dan Kebidanan, 13(2), 145-152.

Mahmood, A., Khattak, A. M., & Khan, S. (2022). User experience (UX) and usability challenges in healthcare applications. Computers in Biology and Medicine, 140, 105106.

Mechael, P. N., Batavia, H., Kaonga, N., Searle, S., Kwan, A., Goldberger, A., ... & Ossko, L. (2022). Barriers and gaps affecting mHealth in low and middle income countries: Policy white paper. Center for Global Health and Economic Development, Earth Institute, Columbia University.

Nielsen, J. (2021). Usability heuristics for mobile user interfaces in healthcare. Journal of Usability Studies, 16(4), 215-228.

Novillo-Ortiz, D., Hernandez-Perez, T., & Saigí-Rubió, F. (2022). Digital health equity: Needs assessment methodologies for marginalized populations. International Journal of Medical Informatics, 131, 103956.

O'Connor, S., Hanlon, P., O'Donnell, C. A., Garcia, S., Glanville, J., & Mair, F. S. (2021). Understanding factors affecting the engaging and adoption of mobile health applications in nursing practice. Nursing Open, 3(4), 185-197.

Puspitasari, E., Nurdiati, D. S., & Hakimi, M. (2022). The role of village midwives in reducing maternal mortality in East Java, Indonesia. Maternal and Child Health Journal, 26(5), 901-909.

Rahayu, S., Wibowo, A., & Kusnanto, H. (2023). Evaluasi pencatatan dan pelaporan Buku KIA secara manual oleh bidan desa. Jurnal Manajemen Kesehatan Indonesia, 11(1), 55-63.

Royston, E., & Armstrong, S. (2021). Preventing maternal deaths. World Health Organization.

Santoso, D., & Setiawan, A. (2024). Analisis statistik deskriptif untuk survei kebutuhan perangkat lunak kesehatan. Jurnal Sistem Informasi dan Kesehatan Tropis, 5(1), 22-30.

Sondaal, S. F., Browne, J. L., Amoakoh-Coleman, M., Borgstein, A., Miltenburg, A. S., Verwijs, M., & Klipstein-Grobusch, K. (2022). Assessing the effect of mHealth interventions in improving maternal and neonatal care in low- and middle-income countries: A systematic review. PLoS One, 11(5), e0154664.

Susanto, A., Widayanti, R., & Nugroho, E. (2023). Redundansi data dan tantangan pelaporan manual di Puskesmas wilayah pesisir. Jurnal Informatika Medis, 8(2), 88-95.

Wahyuni, S., & Santoso, B. (2023). Challenges of digital health implementation in coastal and remote areas of Indonesia. Journal of Public Health Research, 12(1), 2231-2239.

World Health Organization. (2023). Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. World Health Organization.

Yuliana, R., Hidayah, N., & Firmansyah, A. (2023). Cognitive load theory applied to mobile health app interfaces for senior midwives. Journal of Health Technology Assessment, 4(1), 12-20.

Zurovac, D., Talisuna, A. O., & Snow, R. W. (2023). Mobile phone networks and health data surveillance in rural and coastal geographies. The Lancet Digital Health, 5(2), e75-e82.