Determinan Lama Rawat Inap Pasien Diabetes Mellitus Berdasarkan Data Klaim JKN
DOI:
https://doi.org/10.25047/j-remi.v7i4.6829Keywords:
BPJS Health Claims Data, Diabetes Mellitus, INA-CBGs, Indonesia's National Health Insurance (JKN), Length of StayAbstract
The length of hospital stay (LOS) among patients with diabetes mellitus under Indonesia’s National Health Insurance (Jaminan Kesehatan Nasional, JKN) remains highly variable and may indicate inefficiencies in healthcare delivery. However, the population-based determinants of LOS have not been comprehensively identified. This study aimed to analyze the determinants of LOS among hospitalized patients with diabetes mellitus using the 2024 BPJS Kesehatan claims database. An analytical observational study with a cross-sectional design was conducted involving 28,576 inpatients treated at advanced referral healthcare facilities. LOS was categorized as ≤3 days and >3 days. Data were analyzed using descriptive statistics, the Chi-square test, and binary logistic regression. Overall, 42.5% of patients experienced an LOS of more than three days. Disease severity was the strongest determinant, with patients classified as severe having a substantially higher likelihood of prolonged hospitalization. Hospital ownership was also significantly associated with LOS. These findings indicate that both clinical and healthcare system factors influence LOS. Strengthening severity-based case management and improving service efficiency across healthcare facilities may support cost containment and optimize healthcare delivery within the JKN system.
References
[1] X. Lin et al., “Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025,” Sci. Rep., vol. 10, no. 1, pp. 1–11, Sep. 2020, doi: 10.1038/s41598-020-71908-9.
[2] R. Lozano et al., “Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019,” Lancet, vol. 396, no. 10258, pp. 1250–1284, Oct. 2020, doi: 10.1016/S0140-6736(20)30750-9.
[3] American Diabetes Association, “Economic Costs of Diabetes in the U.S. in 2017,” Diabetes Care, vol. 41, no. 5, pp. 917–928, May 2018, doi: 10.2337/dci18-0007.
[4] A. E. Micah et al., “Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990–2050,” Lancet, vol. 398, no. 10308, pp. 1317–1343, Oct. 2021, doi: 10.1016/S0140-6736(21)01258-7.
[5] K. Hajjar, L. Lillo, D. A. Martinez, M. Hermosilla, and N. Risko, “Association between universal health coverage and the disease burden of acute illness and injury at the global level,” BMC Public Health, vol. 23, no. 1, pp. 1–7, Apr. 2023, doi: 10.1186/s12889-023-15671-2.
[6] Y. Chen, X. Zhang, J. Yan, Xue-Tang, M. Qian, and X. Ying, “Impact of Diagnosis-Related Groups on Inpatient Quality of Health Care: A Systematic Review and Meta-Analysis,” Inq. J. Heal. Care Organ. Provision, Financ., vol. 60, pp. 1–16, Jan. 2023, doi: 10.1177/00469580231167011.
[7] S.-W. Cheng, C.-Y. Wang, and Y. Ko, “Costs and Length of Stay of Hospitalizations due to Diabetes-Related Complications,” J. Diabetes Res., vol. 2019, pp. 1–6, Sep. 2019, doi: 10.1155/2019/2363292.
[8] Y. Jiang, B. Rodgers, K. Damiris, C. Choi, and S. Ahlawat, “The effects of diabetes mellitus on clinical outcomes of hospitalized patients with acute diverticulitis,” Eur. J. Gastroenterol. Hepatol., vol. 33, no. 11, pp. 1354–1360, Nov. 2021, doi: 10.1097/MEG.0000000000001895.
[9] F. Akiboye et al., “Impact of the Diabetes Inpatient Care and Education (DICE) project on length of stay and mortality,” Diabet. Med., vol. 37, no. 2, pp. 277–285, Feb. 2020, doi: 10.1111/dme.14062.
[10] F. O. Syed, F. U. Rehman, I. Amin, S. A. Ali, B. J. Rind, and B. Ahmed, “Diabetes Mellitus Does Not Predict Discharge in Hospitalized Patients With Acute Pyelonephritis: A Study From Karachi, Pakistan,” Cureus, vol. 12, no. 10, pp. 1–9, Oct. 2020, doi: 10.7759/cureus.11024.
[11] L. Dulipsingh, H. Bakeri, D. Wakefield, B. Shanaman, and L. Cook, “Impact of Diabetes on Hospitalized Patients With Chronic Medical Conditions,” Diabetes Spectr., vol. 34, no. 3, pp. 283–291, Aug. 2021, doi: 10.2337/ds20-0088.
[12] M. A. Sajjad et al., “Comparison of incidence, rate and length of all-cause hospital admissions between adults with normoglycaemia, impaired fasting glucose and diabetes: a retrospective cohort study in Geelong, Australia,” BMJ Open, vol. 8, no. 3, pp. 1–11, Mar. 2018, doi: 10.1136/bmjopen-2017-020346.
[13] H. Fahlevi, I. Irsyadillah, M. Indriani, and R. S. Oktari, “DRG-based payment system and management accounting changes in an Indonesian public hospital: exploring potential roles of big data analytics,” J. Account. Organ. Chang., vol. 18, no. 2, pp. 325–345, Mar. 2022, doi: 10.1108/JAOC-10-2020-0179.
[14] R. R. Nugraha et al., “Predicting the cost of COVID-19 treatment and its drivers in Indonesia: analysis of claims data of COVID-19 in 2020-2021,” Health Econ. Rev., vol. 12, no. 1, pp. 1–10, Aug. 2022, doi: 10.1186/s13561-022-00392-w.
[15] H. E. Rogers, A. R. Akiteng, G. Mutungi, A. S. Ettinger, and J. I. Schwartz, “Capacity of Ugandan public sector health facilities to prevent and control non-communicable diseases: an assessment based upon WHO-PEN standards,” BMC Health Serv. Res., vol. 18, no. 1, pp. 1–13, Dec. 2018, doi: 10.1186/s12913-018-3426-x.
[16] S. G. Vyas, N. S. Badnerkar, N. A. Chhajed, and S. S. Vyas, “Clinical assessment of etiological risk factors of chronic kidney disease in patients admitted for dialysis to a tertiary care hospital,” Asian J. Med. Sci., vol. 14, no. 9, pp. 115–120, Sep. 2023, doi: 10.3126/ajms.v14i9.54428.
[17] E. J. Zhao et al., “A long wait: barriers to discharge for long length of stay patients,” Postgrad. Med. J., vol. 94, no. 1116, pp. 546–550, Oct. 2018, doi: 10.1136/postgradmedj-2018-135815.
[18] D. Aulia, S. F. Ayu, and N. H. Nasution, “Analisis Upaya Rumah Sakit dalam Menutupi Kekurangan Biaya Klaim Indonesia Case Base Group (INA-CBGs) Yang Dihitung dengan Metode Activities Base Costing pada Rumah Sakit Swasta Kelas C di Kota Medan Tahun 2017,” J. Ekon. Kesehat. Indones., vol. 1, no. 4, pp. 159–166, Nov. 2017, doi: 10.7454/eki.v1i4.1783.
[19] D. M. Wardhana, N. Widajanti, and J. Ichwani, “Hubungan Komponen Comprehensive Geriatric Assessment dan Sarkopenia pada Usia Lanjut,” J. Penyakit Dalam Indones., vol. 6, no. 4, pp. 188–195, Jan. 2019, doi: 10.7454/jpdi.v6i4.370.
[20] S. Satibi, T. M. Andayani, D. Endarti, I. P. T. Suwantara, N. P. Wintariani, and N. P. D. Agustini, “Comparison of Real Cost Versus the Indonesian Case Base Groups (INZ-CBGs) Tariff Rates Among Patients of High- Incidence Cancers Under the National Health Insurance Scheme,” Asian Pacific J. Cancer Prev., vol. 20, no. 1, pp. 117–122, Jan. 2019, doi: 10.31557/APJCP.2019.20.1.117.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Ismi Irfiyanti Fachruddin, Ulfa Diya Atiqa, Nur Asmi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
