Mortality Reporting Modeling in Healthcare Facilities in Indonesia
Abstract
Healthcare facilities in Indonesia, such as hospitals and public health centers, play a crucial role in recording and reporting mortality data necessary for health policy development and quality assessment. Although various reporting methods are available, ranging from manual to electronic systems, the primary focus has often been on morbidity rather than mortality. External reporting processes typically involve basic coding for morbidity and mortality, and the application of the International Classification of Diseases (ICD) for cause-of-death determination in electronic medical records is still underdeveloped. This study employs a qualitative descriptive approach with a system modeling framework to design a comprehensive mortality reporting model that incorporates data mining techniques. By analyzing secondary data from integrated mortality reporting systems in Indonesian healthcare facilities, the study proposes a model that enhances data processing and presentation, offering a structured approach for utilizing mortality data for policy development and future forecasting. The results demonstrate that this model significantly improves data management processes and provides a valuable framework for advancing health policy. Future research should explore the implementation of this model and assess its impact on health policy outcomes in Indonesia.
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[2] A. J. Rusdi, R. D. Prisusanti, and R. A. R. Ularan, “Systematic review keakuratan underlying cause of death (UCOD) pada sertifikat kematian di fasilitas pelayanan kesehatan,” INOHIM, vol. 10, no. 1, 2022.
[3] Kementerian Kesehatan, Peraturan Menteri Kesehatan Nomor 24 Tahun 2022 tentang Rekam Medis. Jakarta, Indonesia: Kementerian Kesehatan, 2022.
[4] A. Marfuatin, T. Lestari, and S. Mulyono, “Tinjauan Data Kematian di Rumah Sakit Umum Daerah dr. Soediran Mangun Sumarso Kabupaten Wonogiri Tahun 2012,” Jurnal Rekam Medis, vol. 2, no. 8, pp. 22–30, 2014.
[5] D. P. Sari, Sudiro, and C. Suryawati, “Evaluasi Sistem Pengolahan Data Mortalitas Pasien Rawat Inap Berbasis Komputer di RSUD Dr. Moewardi,” Jurnal Manajemen Kesehatan Indonesia, vol. 1, no. 5, pp. 1–5, 2017.
[6] Y. T. Utami, N. Wikan, and V. Shabetini, “Pelaksanaan pelaporan data mortalitas rawat inap di rumah sakit,” in Prosiding Seminar Informasi Kesehatan Nasional (SIKesNas), Fakultas Ilmu Kesehatan Universitas Duta Bangsa Surakarta, 2023, pp. 444–457.
[7] B. Riedl, N. Than, and M. Hogarth, “Using the UMLS and simple statistical methods to semantically categorize causes of death on death certificates,” in AMIA Annu. Symp. Proc., Washington D.C., USA, 2010, pp. 677–681.
[8] M. I. Mawardi, H. Rohman, I. Mardiyoko, and I. P. Latarissa, “Analisis Pengelolaan Pelaporan Pada Data Morbiditas Pasien Rawat Jalan di Rumah Sakit,” J. Community Empowement, vol. 1, no. 1, pp. 12–17, 2019.
[9] R. N. Anderson, A. M. Miniño, D. L. Hoyert, and H. M. Rosenberg, “Comparability of cause of death between ICD-9 and ICD-10: Preliminary estimates,” Natl Vital Stat Rep, vol. 49, pp. 1–32, 2001.
[10] World Health Organization, International Statistical Classification of Disease and Related Health Problems, Tenth Revision Version for 2016, 2016.
[11] H. Booth and L. Tickle, “Mortality modelling and forecasting: A review of methods,” A.A.S., vol. 3, no. I/II, pp. 3–43, 2008.
[12] J. Perez, E. Iturbide, V. Olivares, M. Hidalgo, A. Martínez, and N. Almanza, “A data preparation methodology in data mining applied to mortality population databases,” J. Med. Syst., vol. 39, pp. 151–156, 2015, doi: 10.1007/s10916-015-0312-5.
[13] W. Gao and Y. Yang, “Innovations in mortality data reporting and analysis,” J. Public Health Policy, vol. 42, no. 3, pp. 348–361, 2021, doi: 10.1057/s41271-021-00255-2.
[14] H. Meyer and Y. Zhang, “Application of data mining techniques in healthcare: A systematic review,” Health Informatics J., vol. 27, no. 4, pp. 1000–1025, 2021, doi: 10.1177/1460458220954893.
[15] J. R. García and A. Singh, “The use of mortality data for health policy development,” Health Policy Plan., vol. 32, no. 3, pp. 302–310, 2017, doi: 10.1093/heapol/czw130.
[16] M. Jiang and J. Li, “Natural language processing for clinical data: A review,” J. Biomed. Inform., vol. 104, p. 103408, 2020, doi: 10.1016/j.jbi.2020.103408.
[17] J. Goh and H. Lee, “Predictive modeling for mortality risk using big data,” Big Data Res., vol. 14, pp. 100–111, 2019, doi: 10.1016/j.bdr.2018.11.002.
[18] R. Elakkiya and S. Mohan, “Data mining for health care management: A review,” Health Inf. Sci. Syst., vol. 8, no. 1, p. 20, 2020, doi: 10.1186/s13755-020-00300-3.
[19] E.-H.W. Kluge and J. F. Peterson, “Health data analytics for improving patient outcomes: A review,” J. Healthc. Inform. Res., vol. 2, no. 1, pp. 10–22, 2018, doi: 10.1007/s41666-018-0005-5.
[20] B. Hollingsworth and J. Wildman, “The role of health information systems in monitoring mortality trends,” Int. J. Health Serv., vol. 50, no. 2, pp. 195–210, 2020, doi: 10.1177/0020731420906518.
[21] C. Guevara and J. Campbell, “Advanced techniques for mortality data analysis in public health,” Public Health Rev., vol. 40, p. 9, 2019, doi: 10.1186/s40985-019-0105-4.
[22] S. Williams and M. Williams, “Health policy planning and evaluation: An overview,” J. Health Policy, vol. 24, no. 1, pp. 12–22, 2020, doi: 10.1093/heapol/czz045.
[23] World Health Organization, Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019, 2020.
[24] K. S. Reddy and V. Patel, “Mortality trends and forecasts: The role of vital registration systems,” J. Glob. Health, vol. 8, no. 1, 2018, doi: 10.7189/jogh.08.010101.
[25] J. Smith and A. Lee, “Using mortality data for health policy planning: A review of practices in developed countries,” J. Health Data Manag., vol. 15, no. 2, pp. 123–134, 2018.
[26] A. E. W. Johnson and R. G. Mark, “The impact of health data analytics on policy making in healthcare systems,” Health Policy, vol. 122, no. 5, pp. 584–591, 2018, doi: 10.1016/j.healthpol.2018.03.009.
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