This analysis investigates the key factors driving total program payments in healthcare, focusing on the impact of coinsurance payments and visit frequency per enrollee. Using a combination of linear regression modeling and scenario analysis, we explored how changes in these factors affect overall program costs. The goal was to provide actionable insights for effective cost management in the healthcare program. The analysis proves that Coinsurance payments are a significant driver of total program costs. With each dollar increase in coinsurance payments correlate with an increase in total program payments. In Scenario 1, where coinsurance payments increased by 10% with no change in utilization, total program payments rose significantly to $1.22 billion. This finding underscores the cost sensitivity of the program to changes in out-of-pocket coinsurance amounts. Visit frequency per enrollee also plays a critical role in cost dynamics, though it has a complex relationship with total payments. In Scenario 2, a 5% reduction in coinsurance payments accompanied by a 10% increase in visit frequency led to a decrease in total program payments to $1.01 billion. This result suggests that higher utilization may help in reducing overall costs if it aligns with efficient or preventive care. Conversely, in Scenario 3, a 5% increase in coinsurance payments with a 10% decrease in visits led to a moderate increase in total program payments to $1.17 billion, indicating that lower utilization can reduce costs but may depend on the care's effectiveness. Based on our findings we recommend the following prescriptive analysis. Managing visit frequency per enrollee through preventive care programs or other efficient measures can significantly impact on total program costs, potentially reducing the need for frequent high-cost interventions. Adjusting coinsurance rates offers a lever for managing program costs. Lowering coinsurance might encourage utilization but could increase total program expenses. Conversely, increasing coinsurance payments could offset costs but may raise financial burdens for enrollees. A balanced approach is recommended. Leveraging scenario analysis as shown in this study can support proactive policymaking. This analysis could be relevant to policy makers to evaluate the financial implication of proposed changes to cost sharing mechanisms or programs affecting public health and utilization management.
| Published in | International Journal of Economics, Finance and Management Sciences (Volume 14, Issue 1) |
| DOI | 10.11648/j.ijefm.20261401.11 |
| Page(s) | 1-20 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2026. Published by Science Publishing Group |
Coinsurance Payments, Healthcare Programs, Visit Frequency Per Enrollees, Preventive Care Programs, Policy Makers
| [1] | Centers for Medicare & Medicaid Services. (2024). Medicare Outpatient Facility Data: Summary statistics on use and payments by service type. CMS. |
| [2] | Government Accountability Office. (2024). Improper Payments: Fiscal year 2024 estimates and agency efforts to improve accuracy. GAO. |
| [3] | U.S. Department of Health and Human Services. (2023). Medicare program payment data overview. Office of Inspector General. |
| [4] | Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and practice (3rd ed.). OTexts. |
| [5] | Chernew, M. E., Sabik, L. M., Chandra, A., & Newhouse, J. P. (2020). Ensuring the affordability of employer-sponsored health insurance. Health Affairs, 39(12), 2153-2161. |
| [6] | Baicker, K., & Goldman, D. (2011). Patient cost-sharing and health care spending growth. Journal of Economic Perspectives, 25(2), 47-68. |
| [7] | Newhouse, J. P., & Garber, A. M. (2013). Geographic variation in Medicare services. New England Journal of Medicine, 368(16), 1465-1467. |
| [8] | Song, Z., & Wallace, J. (2020). Medicare spending patterns and utilization trends. JAMA Health Forum, 1(6), e200991. |
| [9] | Reschovsky, J. D., & Hadley, J. (2014). The effect of coinsurance on Medicare patients’ utilization. Health Services Research, 49(2), 435-458. |
| [10] | Riley, G. (2012). Trends in Medicare utilization and cost. Health Affairs, 31(5), 926-943. |
| [11] | White, C. (2016). Variation in Medicare spending by region. Health Affairs, 35(8), 1358-1365. |
| [12] | Duggan, M., & Scott Morton, F. (2010). The effect of Medicare Part D on pharmaceutical prices. American Economic Review, 100(1), 590-607. |
| [13] | Chandra, A., Gruber, J., & McKnight, R. (2010). Patient cost-sharing and healthcare outcomes. Quarterly Journal of Economics, 125(3), 1131-1163. |
| [14] | Ziedan, E., Simon, K., & Wing, C. (2019). The impact of healthcare cost-sharing on patient behavior. Journal of Health Economics, 68, 102234. |
| [15] | Stock, J. H., & Watson, M. W. (2012). Introduction to econometrics (3rd ed.). Pearson. |
APA Style
Ada, N., Prah, L. F., Bediako, E., Iredia, N. (2026). Medicare Utilization and Payment Analysis. International Journal of Economics, Finance and Management Sciences, 14(1), 1-20. https://doi.org/10.11648/j.ijefm.20261401.11
ACS Style
Ada, N.; Prah, L. F.; Bediako, E.; Iredia, N. Medicare Utilization and Payment Analysis. Int. J. Econ. Finance Manag. Sci. 2026, 14(1), 1-20. doi: 10.11648/j.ijefm.20261401.11
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Download@article{10.11648/j.ijefm.20261401.11,
author = {Nwaoko Ada and Linda Fynn Prah and Ekow Bediako and Number Iredia},
title = {Medicare Utilization and Payment Analysis},
journal = {International Journal of Economics, Finance and Management Sciences},
volume = {14},
number = {1},
pages = {1-20},
doi = {10.11648/j.ijefm.20261401.11},
url = {https://doi.org/10.11648/j.ijefm.20261401.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20261401.11},
abstract = {This analysis investigates the key factors driving total program payments in healthcare, focusing on the impact of coinsurance payments and visit frequency per enrollee. Using a combination of linear regression modeling and scenario analysis, we explored how changes in these factors affect overall program costs. The goal was to provide actionable insights for effective cost management in the healthcare program. The analysis proves that Coinsurance payments are a significant driver of total program costs. With each dollar increase in coinsurance payments correlate with an increase in total program payments. In Scenario 1, where coinsurance payments increased by 10% with no change in utilization, total program payments rose significantly to $1.22 billion. This finding underscores the cost sensitivity of the program to changes in out-of-pocket coinsurance amounts. Visit frequency per enrollee also plays a critical role in cost dynamics, though it has a complex relationship with total payments. In Scenario 2, a 5% reduction in coinsurance payments accompanied by a 10% increase in visit frequency led to a decrease in total program payments to $1.01 billion. This result suggests that higher utilization may help in reducing overall costs if it aligns with efficient or preventive care. Conversely, in Scenario 3, a 5% increase in coinsurance payments with a 10% decrease in visits led to a moderate increase in total program payments to $1.17 billion, indicating that lower utilization can reduce costs but may depend on the care's effectiveness. Based on our findings we recommend the following prescriptive analysis. Managing visit frequency per enrollee through preventive care programs or other efficient measures can significantly impact on total program costs, potentially reducing the need for frequent high-cost interventions. Adjusting coinsurance rates offers a lever for managing program costs. Lowering coinsurance might encourage utilization but could increase total program expenses. Conversely, increasing coinsurance payments could offset costs but may raise financial burdens for enrollees. A balanced approach is recommended. Leveraging scenario analysis as shown in this study can support proactive policymaking. This analysis could be relevant to policy makers to evaluate the financial implication of proposed changes to cost sharing mechanisms or programs affecting public health and utilization management.},
year = {2026}
}
TY - JOUR T1 - Medicare Utilization and Payment Analysis AU - Nwaoko Ada AU - Linda Fynn Prah AU - Ekow Bediako AU - Number Iredia Y1 - 2026/01/16 PY - 2026 N1 - https://doi.org/10.11648/j.ijefm.20261401.11 DO - 10.11648/j.ijefm.20261401.11 T2 - International Journal of Economics, Finance and Management Sciences JF - International Journal of Economics, Finance and Management Sciences JO - International Journal of Economics, Finance and Management Sciences SP - 1 EP - 20 PB - Science Publishing Group SN - 2326-9561 UR - https://doi.org/10.11648/j.ijefm.20261401.11 AB - This analysis investigates the key factors driving total program payments in healthcare, focusing on the impact of coinsurance payments and visit frequency per enrollee. Using a combination of linear regression modeling and scenario analysis, we explored how changes in these factors affect overall program costs. The goal was to provide actionable insights for effective cost management in the healthcare program. The analysis proves that Coinsurance payments are a significant driver of total program costs. With each dollar increase in coinsurance payments correlate with an increase in total program payments. In Scenario 1, where coinsurance payments increased by 10% with no change in utilization, total program payments rose significantly to $1.22 billion. This finding underscores the cost sensitivity of the program to changes in out-of-pocket coinsurance amounts. Visit frequency per enrollee also plays a critical role in cost dynamics, though it has a complex relationship with total payments. In Scenario 2, a 5% reduction in coinsurance payments accompanied by a 10% increase in visit frequency led to a decrease in total program payments to $1.01 billion. This result suggests that higher utilization may help in reducing overall costs if it aligns with efficient or preventive care. Conversely, in Scenario 3, a 5% increase in coinsurance payments with a 10% decrease in visits led to a moderate increase in total program payments to $1.17 billion, indicating that lower utilization can reduce costs but may depend on the care's effectiveness. Based on our findings we recommend the following prescriptive analysis. Managing visit frequency per enrollee through preventive care programs or other efficient measures can significantly impact on total program costs, potentially reducing the need for frequent high-cost interventions. Adjusting coinsurance rates offers a lever for managing program costs. Lowering coinsurance might encourage utilization but could increase total program expenses. Conversely, increasing coinsurance payments could offset costs but may raise financial burdens for enrollees. A balanced approach is recommended. Leveraging scenario analysis as shown in this study can support proactive policymaking. This analysis could be relevant to policy makers to evaluate the financial implication of proposed changes to cost sharing mechanisms or programs affecting public health and utilization management. VL - 14 IS - 1 ER -
Beacom Business School, University of South Dakota, Vermillion, USA
Department of Economics, Western Michigan University, Kalamazoo, USA
Department of Economics, Saint Cloud University, Saint Cloud, USA
Beacom Business School, University of South Dakota, Vermillion, USA
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