Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care
**Objectives:** We developed a Markov model to simulate a treatment flow of epilepsy patients who refer to specialized care from non-specialized care, and to surgery from specialized care for estimation of patient distributions and expenditures caused by increasing the referral rate for specialized...
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| Format: | Article |
| Language: | English |
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Columbia Data Analytics, LLC
2021-06-01
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| Series: | Journal of Health Economics and Outcomes Research |
| Online Access: | https://doi.org/10.36469/jheor.2021.24061 |
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| author | Masaki Iwasaki Takashi Saito Akiko Tsubota Tatsunori Murata Yuta Fukuoka Kazutaka Jin |
| author_facet | Masaki Iwasaki Takashi Saito Akiko Tsubota Tatsunori Murata Yuta Fukuoka Kazutaka Jin |
| author_sort | Masaki Iwasaki |
| collection | DOAJ |
| description | **Objectives:** We developed a Markov model to simulate a treatment flow of epilepsy patients who refer to specialized care from non-specialized care, and to surgery from specialized care for estimation of patient distributions and expenditures caused by increasing the referral rate for specialized care.
**Methods:** This budget impact analysis of treatment flow optimization in epilepsy patients was performed as a long-term simulation using the Markov model by comparing the current treatment flow and the optimized treatment flow. In the model, we simulated the prognosis of new onset 5-year-old epilepsy patients (assuming to represent epilepsy occurring between 0 and 10 years of age) treated over a lifetime period. Direct costs of pharmacotherapies, management fees and surgeries are included in the analysis to evaluate the annual budget impact in Japan.
**Results:** In the current treatment flow, the number of refractory patients treated with four drugs by non-specialized care were estimated as 8766 and yielded JPY5.8 billion annually. However, in the optimized treatment flow, the number of patients treated with four drugs by non-specialized care significantly decreased and who continued the monotherapy increased. The costs for the four-drug therapy by non-specialized care were eliminated. Hence cost-saving of JPY9.5 billion (-5% of the current treatment flow) in total national expenditures would be expected.
**Conclusion:** This study highlights that any policy decision-making for referral optimization to specialized care in appropriate epilepsy patients would be feasible with a cost-savings or very few budget impacts. However, important information in the decision-making such as transition probability to the next therapy or excuse for sensitive limitations is not available currently. Therefore, further research with reliable data such as big data analysis or a national survey with real-world treatment patterns is needed. |
| format | Article |
| id | doaj-art-5136535034b94ccaa8ca9c4451f351cd |
| institution | Kabale University |
| issn | 2327-2236 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Columbia Data Analytics, LLC |
| record_format | Article |
| series | Journal of Health Economics and Outcomes Research |
| spelling | doaj-art-5136535034b94ccaa8ca9c4451f351cd2025-02-10T16:13:20ZengColumbia Data Analytics, LLCJournal of Health Economics and Outcomes Research2327-22362021-06-0181Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized CareMasaki IwasakiTakashi SaitoAkiko TsubotaTatsunori MurataYuta FukuokaKazutaka Jin**Objectives:** We developed a Markov model to simulate a treatment flow of epilepsy patients who refer to specialized care from non-specialized care, and to surgery from specialized care for estimation of patient distributions and expenditures caused by increasing the referral rate for specialized care. **Methods:** This budget impact analysis of treatment flow optimization in epilepsy patients was performed as a long-term simulation using the Markov model by comparing the current treatment flow and the optimized treatment flow. In the model, we simulated the prognosis of new onset 5-year-old epilepsy patients (assuming to represent epilepsy occurring between 0 and 10 years of age) treated over a lifetime period. Direct costs of pharmacotherapies, management fees and surgeries are included in the analysis to evaluate the annual budget impact in Japan. **Results:** In the current treatment flow, the number of refractory patients treated with four drugs by non-specialized care were estimated as 8766 and yielded JPY5.8 billion annually. However, in the optimized treatment flow, the number of patients treated with four drugs by non-specialized care significantly decreased and who continued the monotherapy increased. The costs for the four-drug therapy by non-specialized care were eliminated. Hence cost-saving of JPY9.5 billion (-5% of the current treatment flow) in total national expenditures would be expected. **Conclusion:** This study highlights that any policy decision-making for referral optimization to specialized care in appropriate epilepsy patients would be feasible with a cost-savings or very few budget impacts. However, important information in the decision-making such as transition probability to the next therapy or excuse for sensitive limitations is not available currently. Therefore, further research with reliable data such as big data analysis or a national survey with real-world treatment patterns is needed.https://doi.org/10.36469/jheor.2021.24061 |
| spellingShingle | Masaki Iwasaki Takashi Saito Akiko Tsubota Tatsunori Murata Yuta Fukuoka Kazutaka Jin Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care Journal of Health Economics and Outcomes Research |
| title | Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care |
| title_full | Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care |
| title_fullStr | Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care |
| title_full_unstemmed | Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care |
| title_short | Budget Impact Analysis of Treatment Flow Optimization in Epilepsy Patients: Estimating Potential Impacts with Increased Referral Rate to Specialized Care |
| title_sort | budget impact analysis of treatment flow optimization in epilepsy patients estimating potential impacts with increased referral rate to specialized care |
| url | https://doi.org/10.36469/jheor.2021.24061 |
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