Article Sidebar

Submitted
30 September 2022
Accepted
21 December 2023
Published
29 December 2023
Download
PDF
Statistic
Read Counter : 910 Download : 2567

Main Article Content

Abstract

Not all medical expenses were paid promptly in 2018, which resulted in a deficit for BPJS Kesehatan. If DJS cannot meet the costs of health services, it will have an impact on other people who need care. Kidney failure is one of the catastrophic diseases with the highest costs, costing up to 6.5 trillion rupiah in 2021, an increase of 190% compared to 2020. This is also due to the increase in the number of sufferers, followed by an increase in cases of kidney failure. Some of the procedures include CAPD, hemodialysis, and organ transplantation, which can cost up to hundreds of millions of rupiah per patient. This research aims to forecast the prevalence rate of kidney failure in Indonesia for 2023–2025 using the Exponential Smoothing method and the literature study method. The results showed that people aged >45 years were more likely to get kidney failure. Compared to women, the prevalence for men is higher, which serves as a warning to the community to maintain a healthy lifestyle. Following the hypothesis, the total cost of kidney failure will increase with the increase in hemodialysis patients and cases. The total cost of treatment is expected to be between 7 and 10 trillion rupiah in 2023-2025. It is known that the cost containment scheme has succeeded in overcoming the problem of cost control in several countries. The United States uses cost sharing as a cost control scheme for the treatment of ESRD (End-Stage Kidney Disease). Therefore, Indonesia can also implement a cost-sharing scheme that is based on the forecasting results of kidney failure costs. This scheme is appropriate to overcome the problem of controlling insurance costs.

Keywords

Kidney Failure Social Security Fund exponential smooting Gagal Ginjal Dana Jaminan Sosial BPJS Kesehatan Hemodialisis Biaya Kesehatan Katastropik

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Nurtandhee, M. (2023). Estimasi Biaya Pelayanan Kesehatan sebagai Upaya Pencegahan Defisit Dana Jaminan Sosial untuk Penyakit Gagal Ginjal. Jurnal Jaminan Kesehatan Nasional, 3(2), 84–101. https://doi.org/10.53756/jjkn.v3i2.104
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Ariyanto, R., Puspitasari, D., & Ericawati, F. (2017). Penerapan Metode Double Exponential Smoothing pada Peramalan Produksi Tanaman Pangan. Jurnal Informatika Polinema, 4(1), 57–62. https://doi.org/10.33795/jip.v4i1.145
  2. Assauri, S. (2016). Manajemen Operasi Produksi Pencapaian Sasaran Organisasi Berkesinambungan (3rd ed.). Rajawali Pers.
  3. Booranawong, T., & Booranawong, A. (2017a). An Exponentially Weighted Moving Average Method with Designed Input Data Assignments for Forecasting Lime Prices in Thailand. Teknologi, 79(6), 53–60. https://doi.org/10.11113/jt.v79.10096
  4. Booranawong, T., & Booranawong, A. (2017b). Simple and Double Exponential Smoothing Methods with Designed Input Data for Forecasting A Seasonal Time Series: In An Application For Lime Prices In Thailand. Suranaree Journal of Science and Technology, 24(3), 301–310.
  5. CNN Indonesia. (2022, March 10). Pengembangan Transplantasi Ginjal sebagai Model Pengembangan Kesehatan. https://www.cnnindonesia.com/ekonomi/20220310173739-78-769566/pengobatan-gagal-ginjal-kuras-uang-bpjs-kesehatan-rp65-t-di-2021
  6. Databoks. (2021, November 24). Jumlah Penderita Diabetes di Indonesia Diproyeksikan Capai 28,57 Juta pada 2045. https://databoks.katadata.co.id/datapublish/2021/11/24/jumlah-penderita-diabetes-di-indonesia-diproyeksikan-capai-2857-juta-pada-2045
  7. Heizer, J., & Render, B. (2017). Manajemen Operasi (11th ed.). Salemba Empat.
  8. Hendriani, T., Yamin, Muh., & Dewi, A. P. (2016). Sistem Peramalan Persediaan Obat Dengan Metode Weight Moving Average dan Reorder Point (Studi Kasus: Puskesmas Soropia). SemanTIK, 2(2), 207–214.
  9. Kementrian Kesehatan. (2022). Profil Kesehatan Indonesia 2021. Kementrian Kesehatan Republik Indonesia.
  10. Mardiansyah, E., Cahyono, D., & Shanty, R. N. T. (2016). Sistem Informasi Pengendali Persediaan Barang Menggunakan Metode Triple Exponential Smoothing untuk Peramalan Penjualan (Studi Kasus: Luna Pet Shop). INFORM, 1(2), 76–87. https://doi.org/10.25139/inform.v1i2.845
  11. Nurhamidah, N., Nusyirwan, N., & Faisol, A. (2020). Forecasting Seasonal Time Series Data using The Holt-Winters Exponential Smoothing Method of Additive Models. Matematika Integratif, 16(2), 151–157. https://doi.org/10.24198/jmi.v16.n2.29293.151-157
  12. Pakaya, D. A., Koniyo, Y., & Lamadi, A. (2022). Intensitas dan Prevalensi Ektoparasit pada Kepiting Bakau (Scylla Serrata) dalam Pengembangan Budidaya. Vokasi Sains Dan Teknologi, 2(1), 32–37. https://doi.org/10.56190/jvst.v2i1.15
  13. Pujiyanti, E., Setiawan, E., Ratna Sari, E., & Pratiwi Suwandi, I. (2019). Kajian Literatur Sistematis: Skema Pengendalian Biaya dalam Asuransi Kesehatan Nasional di Beberapa Negara Cost Containment Application in The National Health Insurance Scheme: A Systematic Review. Ekonomi Kesehatan Indonesia, 4(2). https://doi.org/10.7454/eki.v4i2.3460
  14. Setyawan, F. E. B. (2015). Sistem Pembiayaan Kesehatan. Saintika Medika, 11(2), 119–126. https://doi.org/10.22219/sm.v11i2.4206
  15. Walida, N., Wahyuningsih, S., & Amijaya, F. D. T. (2021). Pemilihan Parameter Optimum Menggunakan Exponential Smoothing dengan Metode Golden Section Untuk Peramalan Jumlah Titik Panas di Kalimantan Timur. Jambura Journal of Probability and Statistics, 2(2), 75–85. https://doi.org/10.34312/jjps.v2i2.10416