Analysis of ICD-9-CM Coding Accuracy in the Reimbursement Claim Process for INA-CBGs Compliance
DOI:
https://doi.org/10.62951/icistech.v5i1.215Keywords:
Claim accuracy, Health management, ICD coding, INA reimbursement, Medical complianceAbstract
This study aims to analyze the accuracy of ICD-9-CM coding in Cathlab procedure claims submitted to BPJS Kesehatan under the INA-CBGs reimbursement system at RSI Aisyiyah Malang. Accurate coding is critical for determining appropriate claim grouping and tariff calculation within Indonesia’s national health insurance scheme. The research employed a mixed-methods approach, combining quantitative analysis of 244 Cathlab claims from 2024 with qualitative insights obtained through document review, interviews, and direct observation. The results showed that 182 claims (74.59%) were accepted as accurate and complete, while 62 claims (25.41%) were returned as pending. Common causes of claim inaccuracy included missing supporting documents (37.10%), incorrect ICD-9-CM codes (27.42%), and nonspecific diagnoses (19.35%). Procedural miscoding, such as omitting dual catheterization codes or stent-related procedure codes, was identified as a frequent issue, significantly impacting claim grouping and reimbursement. The study highlights systemic challenges related to documentation quality, coder competency, and institutional claim verification processes. These challenges result in delays, incorrect payments, and administrative inefficiencies, posing barriers to effective reimbursement. The findings underscore the importance of implementing Clinical Documentation Improvement (CDI) strategies, improving coder training, and transitioning to newer coding systems such as ICD-10 or ICD-11. Upgrading to these systems will support better coding accuracy, enhance claim processing efficiency, and ensure more appropriate reimbursement. Strengthening these components is essential to ensure the integrity of Indonesia’s health financing system, improve operational workflows, and ensure that healthcare providers receive timely and accurate reimbursement for services rendered. This study provides a comprehensive evaluation of the current state of coding practices in Indonesian healthcare institutions and offers actionable recommendations for improving coding accuracy and claims processing.
References
Ascenção, R., Nogueira, P., Sampaio, F., Henriques, A., & Costa, A. (2023). Adverse drug reactions in hospitals: Population estimates for Portugal and the ICD-9-CM to ICD-10-CM crosswalk. BMC Health Services Research, 23(1), 1222. https://doi.org/10.1186/s12913-023-10225-z
Boosting, M., & Worldwide, A. (2014). Better health & social care volume 1: Report. International Summit of Cooperatives, Quebec.
Carneiro-Leão, L., Vasconcelos, M. J., & Cernadas, J. (2020). Identifying SJS/TEN using ICD-9-CM coding: Real or just fantasy? Allergology International, 69(1), 136-137. https://doi.org/10.1016/j.alit.2019.06.006
De Crescenzo, L. A., Gabella, B. A., & Johnson, J. (2021). Interrupted time series design to evaluate ICD-9-CM to ICD-10-CM coding changes on trends in Colorado emergency department visits related to traumatic brain injury. Injury Epidemiology, 8(1), 15. https://doi.org/10.1186/s40621-021-00308-y
Gao, Y., Fu, X., Liu, X., & Wu, J. (2021). Multi-features-based automatic clinical coding for Chinese ICD-9-CM-3. In Advances in Artificial Intelligence and Data Engineering (pp. 473-486). https://doi.org/10.1007/978-3-030-86383-8_38
Hsu, M., Wang, C., Huang, L., Lin, C., Lin, F., & Toh, S. (2021). Effect of ICD-9-CM to ICD-10-CM coding system transition on identification of common conditions: An interrupted time series analysis. Pharmacoepidemiology and Drug Safety, 30(12), 1653-1674. https://doi.org/10.1002/pds.5330
Kessler, R. C., et al. (2010). Childhood adversities and adult psychopathology in the WHO world mental health surveys. British Journal of Psychiatry, 13(2), 345-357. https://doi.org/10.1192/bjp.bp.110.080499
Lathifah, R., Chalidyanto, D., & Pudjirahardjo, W. J. (2020). Factors impacting the cost differences between INA-CBGs tariffs and hospital costs in JKN patients with appendicitis cases. Enferm Clínica, 30, 213-216. https://doi.org/10.1016/j.enfcli.2020.06.048
Lee, H. J., Kim, C. H., Han, I., & Kim, S. H. (2019). Comparative study of mental health states among adolescents in multicultural versus monocultural families, using the 13th Korean Youth Risk Behavior Web-Based Survey, 2017. Iranian Journal of Pediatrics, 29(5), 92192. https://doi.org/10.5812/ijp.92192
Lim, R., et al. (2020). Theory-based electronic learning intervention to support appropriate antibiotic prescribing by nurse and pharmacist independent prescribers: An acceptability and feasibility experimental study using mixed methods. BMJ Open, 10(6), e036181. https://doi.org/10.1136/bmjopen-2019-036181
Maryati, W., Yuliani, N., Susanto, A., Wannay, A. O., & Justika, A. I. (2021). Reduced hospital revenue due to error code diagnosis in the implementation of INA-CBGs. International Journal of Public Health Science (IJPHS), 10(2), 354. https://doi.org/10.11591/ijphs.v10i2.20690
Metcalfe, A., Sheikh, M., & Hetherington, E. (2021). Impact of the ICD-9-CM to ICD-10-CM transition on the incidence of severe maternal morbidity among delivery hospitalizations in the United States. American Journal of Obstetrics and Gynecology, 225(4), 422.e1-422.e11. https://doi.org/10.1016/j.ajog.2021.03.036
Moreland, B. L., Burns, E. R., & Haddad, Y. K. (2021). National rates of non-fatal emergency department visits and hospitalizations due to fall-related injuries in older adults 2010-2014 and 2016: Transitioning from ICD-9-CM to ICD-10-CM. Injury Prevention, 27(Suppl 1), i75-i78. https://doi.org/10.1136/injuryprev-2019-043516
Nilansari, A. F., Yasin, N. M., & Puspandari, D. A. (2023). Cost analysis of inpatient hypertension patients at Panembahan Senopati Hospital, Bantul, Yogyakarta, Indonesia: Comparison between INA-CBGs rates and hospitalized actual rate. Journal of Public Health and Development, 21(3), 153-167. https://doi.org/10.55131/jphd/2023/210312
Oktamianiza, O., Putra, D. M., Yulia, Y., Fahira, A., & Afridon, A. (2021). Analysis of differences in tariff for health service based on sustainability of diagnosis on admission and summary discharge form with INA-CBGs verification. International Journal of Engineering, Science and Information Technology, 1(3), 82-86. https://doi.org/10.52088/ijesty.v1i3.114
Phillips-Bell, G. S., et al. (2020). Assessing the burden of neonatal abstinence syndrome: Validation of ICD-9-CM data, Florida, 2010-2011. Journal of Public Health Management and Practice, 26(1), E1-E8. https://doi.org/10.1097/PHH.0000000000000897
Raskind-Hood, C., et al. (2020). Assessing pregnancy, gestational complications, and co-morbidities in women with congenital heart defects (Data from ICD-9-CM codes in 3 US surveillance sites). American Journal of Cardiology, 125(5), 812-819. https://doi.org/10.1016/j.amjcard.2019.12.001
Rodriguez, F. H., et al. (2022). How well do ICD-9-CM codes predict true congenital heart defects? A Centers for Disease Control and Prevention-based multisite validation project. Journal of the American Heart Association, 11(15). https://doi.org/10.1161/JAHA.121.024911
Sarayani, A., Wang, X., Thai, T. N., Albogami, Y., Jeon, N., & Winterstein, A. G. (2020). Impact of the transition from ICD-9-CM to ICD-10-CM on the identification of pregnancy episodes in US health insurance claims data. Clinical Epidemiology, 12, 1129-1138. https://doi.org/10.2147/CLEP.S269400
Satibi, S., Andayani, T. M., Endarti, D., Suwantara, I. P. T., Wintariani, N. P., & Agustini, N. P. D. (2019). 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 Journal of Cancer Prevention, 20(1), 117-122. https://doi.org/10.31557/APJCP.2019.20.1.117
Sebastião, Y. V., Metzger, G. A., Chisolm, D. J., Xiang, H., & Cooper, J. N. (2021). Impact of ICD-9-CM to ICD-10-CM coding transition on trauma hospitalization trends among young adults in 12 states. Injury Epidemiology, 8(1), 4. https://doi.org/10.1186/s40621-021-00298-x
Surya, R., Gani, A., & Saroyo, Y. B. (2023). Hospital cost vs INA-CBGs claim for obstetrics procedure in Soe Rural General Hospital, East Nusa Tenggara. Indonesian Journal of Obstetrics and Gynecology, 11(4), 2010. https://doi.org/10.32771/inajog.v11i4.2010
Wardhana, M. P., Gumilar, K. E., Rahmadhany, P., Dewi, E. R., & Laksana, M. A. C. (2020). Ina-CBGs claim versus total hospital cost: A vaginal delivery investigation at Airlangga University Academic Hospital, Indonesia. Journal of Public Health Research, 9(4), 1999. https://doi.org/10.4081/jphr.2020.1999
World Health Organization (WHO). (2020). Coronavirus disease (COVID-19) pandemic. [Website].
Yang, H., Pasalic, E., Rock, P., Davis, J. W., Nechuta, S., & Zhang, Y. (2021). Interrupted time series analysis to evaluate the performance of drug overdose morbidity indicators shows discontinuities across the ICD-9-CM to ICD-10-CM transition. Injury Prevention, 27(Suppl 1), i35-i41. https://doi.org/10.1136/injuryprev-2019-043522
Yuliastuti, F., Andayani, T. M., Endarti, D., & Kristina, S. A. (2023). Breast, cervical, and lung cancer: A comparison of real healthcare costs and INA-CBGs rates in the era of National Health Insurance. PharmacoPractice (Granada), 21(1), 01-07. https://doi.org/10.18549/PharmPract.2023.1.2768
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Proceeding of The International Conference of Inovation, Science, Technology, Education, Children, and Health
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
